a research database

Database Search

What is Database Search?

Harvard Library licenses hundreds of online databases, giving you access to academic and news articles, books, journals, primary sources, streaming media, and much more.

The contents of these databases are only partially included in HOLLIS. To make sure you're really seeing everything, you need to search in multiple places. Use Database Search to identify and connect to the best databases for your topic.

In addition to digital content, you will find specialized search engines used in specific scholarly domains.

Related Services & Tools

Explore millions of high-quality primary sources and images from around the world, including artworks, maps, photographs, and more.

Explore migration issues through a variety of media types

• Part of The Streets are Talking: Public Forms of Creative Expression from Around the World
• Part of The Journal of Economic Perspectives, Vol. 34, No. 1 (Winter 2020)
• Part of Cato Institute (Aug. 3, 2021)
• Part of University of California Press
• Part of Open: Smithsonian National Museum of African American History & Culture
• Part of Indiana Journal of Global Legal Studies, Vol. 19, No. 1 (Winter 2012)
• Part of R Street Institute (Nov. 1, 2020)
• Part of Leuven University Press
• Part of UN Secretary-General Papers: Ban Ki-moon (2007-2016)
• Part of Perspectives on Terrorism, Vol. 12, No. 4 (August 2018)
• Part of Leveraging Lives: Serbia and Illegal Tunisian Migration to Europe, Carnegie Endowment for International Peace (Mar. 1, 2023)
• Part of UCL Press

Harness the power of visual materials—explore more than 3 million images now on JSTOR.

Enhance your scholarly research with underground newspapers, magazines, and journals.

Explore collections in the arts, sciences, and literature from the world’s leading museums, archives, and scholars.

Finding Information

• Types of Information Resources

Introduction

What are databases, further reading, learning objectives.

• Find ebooks
• Find Articles
• Find Newspaper Articles
• Find Images
• Getting Copies of Articles and Books You Can't Find

This page is designed to help you:

• Identify at least two differences between the type of information available through general search engines and academic databases
• Understand what research databases are and why they are a valuable part of academic work

There are many types of databases that you can use for your research. The database you choose will depend on what type of information you want to find. 

Research databases, such as JSTOR and Academic Search Premier, uncover the world of scholarly information. Most of the content in these databases is only available through the library. The complete list of databases is on the Databases A-Z list. The Library has purchased access to hundreds of databases on your behalf. There is no charge to use these resources.

Search Engines 

Research databases.

Let us search for the same thing in Google and in a general academic database called Academic Search Premier.

Search for the impact of social media on teenagers

Results in Google

Notes about these results in Google:

• 81,500,000 results
• Advertisements are the first two results
• Highlighted article with images from a high school
• Ability to quickly sort based on top Google categories: News, Images, Videos, Shopping

Search results in Academic Search Premier

Notes about these results in the Academic Search Premier database:

• 3 are from academic journals
• Able to quickly sort by scholarly qualification and publication date
• Avdic, A., & Eklund, A. (2010). Searching reference databases: What students experience and what teachers believe that students experience. Journal of Librarianship and Information Science, 42 (4), 224–235. https://doi.org/10.1177/0961000610380119

This page was designed to help you:

• << Previous: Types of Information Resources
• Next: Find ebooks >>
• Last Updated: Feb 16, 2024 3:55 PM
• URL: https://libguides.brown.edu/findinginformation

Brown University Library  |  Providence, RI 02912  |  (401) 863-2165  |  Contact  |  Comments  |  Library Feedback  |  Site Map

Library Intranet

What is a Research Databases?

In the ever-evolving world of academia and research, staying ahead of the curve requires unfettered access to a vast wealth of knowledge.

As researchers, students, and knowledge-seekers, we strive to uncover groundbreaking insights, delve into the depths of human understanding, and contribute to the expanding boundaries of human intellect.

Amid this pursuit of knowledge, research databases stand as the unsung heroes, providing us with the key to unlocking the gates of an information goldmine.

In this digital age, the internet has transformed the way we access information, and research databases have emerged as the foundational pillars of academic exploration.

Offering a treasure trove of scholarly resources, these virtual repositories are meticulously curated to cater to the unique needs of researchers from diverse disciplines.

From peer-reviewed articles and conference proceedings to patents and historical archives, research databases are the beacons guiding us through the labyrinth of academic literature.

Join us as we embark on an illuminating journey to unravel the power of research databases. In this blog post, we will explore what research databases are, their vital role in supporting academic endeavors, and the remarkable advantages they present to the enquiring minds of the scholarly community.

Whether you are a seasoned researcher seeking a more efficient way to navigate through the sea of publications or a student eager to hone your skills in literature review, this blog will serve as your compass, pointing you towards the invaluable resources that lie just a few clicks away.

Step into the realm of research databases, where knowledge knows no bounds, and discoveries await those with the curiosity to seek them.

Let us dive into this digital realm of information and harness the potential that research databases hold in reshaping the future of knowledge acquisition and creation.

What is a research database?

A research database is a structured collection of digital information and resources that are specifically designed to support academic and scholarly research. These databases gather and organize a wide range of materials, such as academic journals, research papers, conference proceedings, books, theses, patents, and more, making it easier for researchers to access and retrieve relevant information on a particular topic.

Research databases play a crucial role in the academic community, as they provide a centralized and organized repository of high-quality, peer-reviewed, and reliable sources that researchers can use to find literature related to their research interests. These databases are typically accessible through online platforms and are searchable using various criteria, including keywords, author names, publication dates, and more.

What are the benefits of using research databases?

The benefits of using research databases include:

1. Comprehensive Coverage

Databases often cover a broad range of disciplines, making it easier to find information across different fields.

2. Peer-reviewed Content

Many databases only include content that has undergone rigorous peer review, ensuring the reliability and quality of the sources.

3. Reliable resources

4. searchability.

Databases offer advanced search features that allow researchers to narrow down their search and find highly relevant materials quickly.

5. Citation Information

Databases often provide citation details for each source, making it easier for researchers to properly cite and reference the works they use.

6. Access to Full Text

Many databases provide direct access to full-text articles, reducing the need to go through multiple websites or paywalls.

Some examples of well-known research databases include PubMed, Scopus, Web of Science, IEEE Xplore Digital Library, JSTOR, and Google Scholar.

Researchers, students, and academics often rely on research databases to stay up-to-date with the latest advancements in their fields, conduct literature reviews, and gather evidence for their research projects.

Related Guides

Reference management. Clean and simple.

How to efficiently search online databases for academic research

How to access academic databases

How to search academic databases, 1. use the campus network to access research databases, 2. find databases that are specifically related to your topic, 3. set up the search parameters within a database to be as narrow as possible, 4. ask a librarian for help, 5. slowly expand your search to get additional results, 6. use the pro features of the database, 7. try a more general database, if needed, 8. keep track of seminal works, frequently asked questions about searching online databases, related articles.

University libraries provide access to plenty of online academic databases that can yield good results when you use the right strategies. They are among the best sources to turn to when you need to find articles from scholarly journals, books, and other periodicals.

Searching an online research database is much like searching the internet, but the hits returned will be scholarly articles and other academic sources, depending on the subject. In this guide, we highlight 8 tips for searching academic databases.

• Use college and university library networks.
• Search subject-specific databases.
• Set up search parameters.
• Ask a librarian for help.
• Narrow or broaden your search, as needed.
• Use the pro features, where applicable.
• Try a more general database.
• Keep track of seminal works.

Tip: The best practice is to use the links provided on your library's website to access academic databases.

Most academic databases cannot be accessed for free. As authoritative resources, these multi-disciplinary databases are comprehensive collections of the current literature on a broad range of topics. Because they have a huge range of publications, public access is sometimes restricted.

College and university libraries pay for subscriptions to popular academic databases. As a student, staff, or faculty member, you can access these resources from home thanks to proxy connections.

➡️ Check out our list of EZProxy connections to see if your institution provides such a service.

Tip: Searching the right databases is key to finding the right academic journals.

Around 2.5 million articles are published EACH year. As a result, it's important to search the right database for the reference you need. Comprehensive databases often contain subject-specific resources and filters and these will help you narrow down your search results. Otherwise, you will have to screen too many unrelated papers that won't give you the reference you want.

Ask a librarian or check your library's A-Z resource list to find out which databases you can access. If you do not know where to start, you can check out the three biggest academic database providers:

➡️ Take a look at our compilations of research databases for computer science or healthcare .

Unlike in a Google search, typing in full sentences will not bring you satisfactory results. Some strategies for narrowing search parameters include:

• Narrowing your search terms in order to get the most pertinent information from the scholarly resources you are reviewing
• Narrowing results by filters like specific date range or source type
• Using more specific keywords

If your university library has a subject specialist in your field, you may want to contact them for guidance on keywords and other subject- and database-specific search strategies. Consider asking a librarian to meet you for a research consultation.

A specific search might not return as many results. This can be good because these results will most likely be current and applicable. If you do not get enough results, however, slowly expand the:

• type of journal

From there, you'll be able to find a wider variety of related technical reports, books, academic journals, and other potential results that you can use for your research.

Academic search engines and databases are getting smart! In the age of big data and text mining, many databases crunch millions of scientific papers to extract connections between them. Watch out for things like:

• related relevant articles
• similar academic resources
• list of "cited by" or "citations"
• list of references

When you have thoroughly finished searching a comprehensive database, you can move on to another to find more results. Some databases that cover the same topics might give you the same search results, but they might also cover an entire range of different journals or online resources.

You might prefer the search system of one database over another based on the results you get from keyword searches. One database might have more advanced search options than the other. You can also try a more general database like:

• Web Of Science

➡️ Visit our list of the best academic research databases .

There are experts in every field, people who have published a lot of scholarly content on your topic, people who get quoted or interviewed a lot and seem to be present almost everywhere. Pay attention to those names when searching a database and once you have found someone interesting, you can search for more from that person.

Also, take note of seminal articles, or those works that have been cited repeatedly within your field. Many major databases for academic journals have features that allow you to quickly determine which articles are cited most frequently.

➡️ Ready to start writing your paper? Visit our guide on how to start a research paper .

Your institution's library provides access to plenty of online research databases. They are among the best sources to turn to when you need to find articles from scholarly journals and periodicals.

Searching the right databases is key to finding the right articles. Ask a librarian or check your library's website to access details. If you do not know where to start, check out the three biggest academic database providers:

Or take a look at our compilation of research database for computer science or healthcare .

You can narrow your search by only including articles within a specific date range or unchecking certain types of journals or magazines that are included in the database but have nothing to do with your topic. Make sure to also use very specific keywords when searching.

Unlike in a Google search, typing in full sentences will not bring you satisfactory results. There are different methods to search different databases. Ask a librarian or do an internet search on how to best search your particular database.

Narrowing down a search might not return many results. If you do not get enough results, slowly expand the date range, type of journal, or keywords.

University of Houston Libraries

What’s the difference between a research database and google.

What’s the Difference between a Research Database and Google?

Brought to you by the University of Houston Libraries.

As part of your research, your instructor may sometimes require you to use articles or other resources from the library’s research databases . But what is a research database and why are they useful?

A research database is an organized, searchable collection of information that allows you to quickly search many resources simultaneously. Databases can be general, such as Academic Search Complete or ProQuest , or subject-specific, such as PsycInfo , which has resources related to psychology, or America, History and Life , which has resources related to history.

So what makes a research database different than other search engines, like Google? There are a few important distinctions to keep in mind when you’re using a research database instead of Google. First, the types of information you’re searching are usually different. Google searches for results across the internet, including websites, while research databases typically include scholarly journal articles, popular magazine articles and newspapers, books, and videos. The content of a research database is also reviewed and updated regularly.

Also, how you search is different. Google uses natural language searching, which allows you to search using complete sentences, such as “How many moons does Jupiter have?”. Google also searches the full text of resources, which usually means you get many results, but not all of them are relevant to your search query. Research databases use more precise, keyword searching, and most don’t automatically search the full text of a resource. Keywords are words or phrases that describe the topic you’re researching, and you’ll want to use them when searching databases to locate the most relevant resources on your topic.

Also, while Google offers some advanced searching options , most people don’t need to use them to find what they’re looking for. However, advanced search options in research databases, such as filtering by date, language, document format, and peer review status, can be effective in retrieving more relevant, precise results. Google also uses ads and tracks its users based on what they’re searching and clicking on, which the library doesn’t.

Both Google and research databases can be useful depending on your information need, and results from both need to be evaluated for accuracy and credibility. If you’re searching for scholarly research in mechanical engineering, a subject-specific engineering database would be a better place to search than Google. However, if you’re looking for websites of professional engineering organizations , Google is the better search option.

If you still have questions about research databases and how to use them, contact UH Libraries for help.

• What is the Difference Between a Research Database and Google transcript

Research Process: Research Databases

• Selecting a Topic
• Background Information
• Narrowing the Topic
• Library Terms
• Generating Keywords
• Boolean Operators
• Search Engine Strategies
• Google Searching
• Basic Internet Terms
• Research & The Web
• Search Engines
• Evaluating Books
• Evaluating Articles
• Evaluating Websites
• Bibliographic Information
• Off Campus Access
• Periodical Locator

Research Databases

Research databases are organized collections of computerized information or data such as periodical articles, books, graphics and multimedia that can be searched to retrieve information. Databases can be general or subject oriented with bibliographic citations, abstracts, and or full text. The sources indexed may be written by scholars, professionals or generalists.

Research databases that are retrieved on the World Wide Web are generally non-fee based, lack in-depth indexing, and do not index proprietary resources. Subscription or commercial databases are more refined with various types of indexing features, searching capabilities, and help guides.

Prince George's Community College's Library provides commercial databases for its users as well as non-fee databases. These databases are available from the Library's Website. To review these databases, click on  Research Databases .

Selecting Appropriate Online Databases

Your topic statement determines the type of database, kind of information, and the date of the sources that you will use. It is important to clarify whether your topic will require research from journals, magazines, newspapers, and books or just journals. To understand the differences between magazines, journals, and newspapers, see the  Magazines, Journals, and Newspapers: What's the Difference  section under Evaluating Sources. 

Search Strategies

Before you begin to search the databases, it is important that you develop a well planned comprehensive search strategy. Determine what your keywords are and how you want them to link together. Always read the help screens and review any tutorials that have been developed for a particular database.

After you determine what your keywords are, consult any subject headings or guides to locate controlled vocabulary such as a thesaurus that may appear in the subject field. You will also want to decide what other fields may be valuable for your search.

Boolean searching is one of the basic and best search strategies that is used by most online databases.

For more help with search strategies see  Search Strategies  section.

• << Previous: Bibliographic Information
• Next: Off Campus Access >>
• Last Updated: Jan 8, 2024 10:20 AM
• URL: https://pgcc.libguides.com/researchprocess

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Thorac Dis
• v.10(Suppl 29); 2018 Oct

How to set up a database?—a five-step process

Alice brembilla.

1 Unité de Méthodologie en Recherche Clinique, épidémiologie et de Santé Publique, Inserm CIC 1431, CHU de Besançon, France;

2 UMR CNRS 6249 Chrono-Environnement, Université Bourgogne Franche Comté, Besançon, France;

Bérenger Martin

Anne-laure parmentier, maxime desmarets.

3 UMR1098 Inserm, Etablissement Français du Sang, Université Bourgogne Franche Comté, Besançon, France;

Pierre-Emmanuel Falcoz

4 INSERM (French National Institute of Health and Medical Research), UMR 1260, Regenerative Nanomedicine (RNM), FMTS, Strasbourg, France;

5 Faculté de Médecine et Pharmacie, Université de Strasbourg, Strasbourg, France;

6 Hôpitaux Universitaires de Strasbourg, Service de Chirurgie Thoracique - Nouvel Hôpital Civil, Strasbourg, France

Marc Puyraveau

Frédéric mauny.

Database set-up directly impacts the quality and viability of research data, and therefore is a crucial part of the quality of clinical research. Setting up a quality database implies following a strict data-management process. Too much collected information threatens the quality of the information required to achieve the objectives of the study. Therefore, the data that will be collected and managed have to be cautiously discussed and selected. Case report forms (CRF) are the tools the most frequently used to collect the data specified by the protocol. An informative and well-structured document simplifies database design and data validation. Key elements are about choice of sequential or thematic structuring, information and type of information that should be entered and the importance of data standards and coding guide. Final database must be structured with unique ID patient, with one record per subject or per measure. Specific information must be provided for each variable according to the database specifications. The quality of the results is directly related to the quality of the collected data. The CRF should then be completed as fully and accurately as possible. Data validation relies on three key points: the CRF completion guidelines, the Edit Checks process and the Data clarification process. Various open source or business software applications provide all functionalities to set up a clinical data base and CRF. The General Data Protection Regulation (GDPR) standardizes and strengthens the protection of personal data across the EU and for other country’s data being “processed” within the EU. The General principles include lawfulness, fairness and transparency, restricted use of data, data minimization, accuracy, limited storage, confidentiality and probity, and accountability.

Introduction

Database set-up directly impacts the quality and viability of research data, and therefore is a crucial part of the quality of clinical research. Setting up a quality database implies following a strict data-management process ( 1 ). This process should be described in a data-management plan, “a to-do list that details how one plans to collect, clean, store and share the products of their research” ( 2 , 3 ). Data-management had been the subject of continued interest and development for over three decades ( Figure 1 ), largely before the emergence of the concept of Big Data and the data management issues associated with it ( 4 ). Whatever the size of the database, data-management is based on the same main rules and concepts. This paper aims to provide the basics of database set-up, with a particular focus on the case report form (CRF). We will discuss data collection, database conception, building, computerization and data validation, as well as regulatory aspects.

Annual number of publications indexed in Medline ® and associated with the “Data Management”.

The query was conducted using PubMed ® (builder = “data management” in “All fields”, 09 August 2018).

Data collection

Which data should be collected ( 5 - 7 ).

This question of great importance is about the relevance of the collected data with regard to the objectives of the study. Too much (collected) information threatens the quality of the information required to achieve the objectives of the study. Therefore, the data that will be collected and managed have to be cautiously discussed and selected (see also “Evolution of the legal consideration in Europe” below). The golden rule “one scientific question, one objective, one study” also applies when the data are selected for the study, keeping in mind that the usefulness of all the collected pieces of data is unequal. The retained data will provide different information related to specific roles and functions. The function of the data should be clarified and be in line with the objective of the research: data which will be used to assess the respect of the protocol, those for safety and quality purposes, those to give the main general characteristics of the study sample, those to analyze to address the objectives. Indirect identification by the data management should be maintained for validation, correction, for patient and medical records queries (even the recorded data must be anonymized). The actual collected data will be used to define:

• The outcomes (primary and secondary);
• The eligibility criteria;
• The matching/stratification criteria;
• The relevant groups of patients (allocated treatment, case vs. controls, exposed vs. unexposed…);
• The known and potential confounding factors;
• The factor potentially involved in effect modification or mediation;
• The general characteristics of the study sample.

How should the data be collected? The case report form

Case report forms are the tools the most frequently used to collect the data specified by the protocol. An informative and well-structured document simplifies database design and data validation. The CRF should be designed in accordance with the following rules:

• Use a multidisciplinary approach to designing and developing the CRF: the project leader, the methodologist(s), the clinical and safety personnel, and the data manager(s) provide valuable perspectives to help optimize the CRF;
• Design the CRF with safety and efficacy endpoints in mind. In order to do this, consult the study, and review the statistical analysis plan (if available) to ensure that all key endpoints are collected;
• Design the CRF to follow the data flow from the perspective of the person in charge of the completion, and take into account the flow of study procedures. Data that are logically related should be grouped together in CRF sections. Use the time schedule of enrolment, interventions and visits to structure the document;
• Keep the CRF questions, prompts, and instructions as clear and concise as possible.

Database conception: structure and organization of the data

Sequential or thematic structuring.

Two major organizations/strategies can be implemented. The sequential organization structures data in chronological blocks (i.e., regularly/periodically collected blocks of data), such as daily body temperature or dosage antibodies. The thematic organization is adapted when one data statement is necessary like medical history. The type of organization must be linked with the variable definition.

Which information should be entered?

To avoid the loss of information, crude data will be relevant. For example, if we want to collect body mass index, we must ensure that crude data such as size and weight are entered. The body mass index will be calculated automatically in a post-processing phase. If necessary, information about weight will be available and can be used for another description or calculation.

Which type of information?

As much as possible, the data collection should be based on closed-ended questions. In this case, the doctor/Data Entry Clerk chooses among a fixed set of choices. Some data may also be collected with open-ended questions and free-form text. For example, it can be allowed to specify additional information when a category “other” is present. This strategy prevents the loss of data without building an overly long list of choices, some of which will occur only rarely over the course of the study. The heterogeneity of such written information requires specific processing to homogenize the information. It is therefore recommended to use open-ended questions sparingly.

Importance of data standards

The unit of measure and the rounding value of each variable must be specified. The international system of units should be preferred. Thus, the data survey will be homogeneous making analysis possible.

Coding guide

The organization/arrangement of data is a precondition/prerequisite to computerize the data base. It’s recommended to synthesize in a document the name and the definition of the collected data, with its unit of measure and rounding value. This document allows the data-manager to faithfully build the data base.

Database building: data computerization

How should the database be structured.

The final structure of the database should be constituted as follows:

• If there is only one measure of the main outcome per subject one record per subject in the database is appropriate;
• If there are repeated measures, then the database should contain one record per measure for the subject.

Each subject needs to be identified with a unique ID. If there are several records per subject, they should be identified with a unique record ID.

Each variable must be presented in a distinct column with unique and synthetic brief but clear name.

How must variables be coded? ( 8 )

Database specifications should at least provide the following information for each variable:

• Name and label (questions asked on the CRF);
• CRF section, forms, or other logical group to which the data belongs;
• Type (e.g., numeric, text, date, time);
• Length (including number of characters before and after the decimal point, when applicable);
• Definitions for all coded values included in code lists;
• Algorithms for derived or calculated variables;
• Dependent relationship.

The CRF should be annotated to map the sections, visits, forms and collected items to their corresponding database tables and variable item names.

Data validation

How to increase data quality.

The quality of the results is directly related to the quality of the collected data. The CRF should then be completed as fully and accurately as possible. This section proposes a focus on three key points: the CRF completion guidelines, the Edit Checks process and the Data clarification process.

CRF completion guidelines ( 8 )

CRF completion guidelines will help to ensure that all required fields will be completed, and that the data provided within these forms are in compliance with the study protocol. The guidelines should not provide guidance or suggestions that could be considered leading the user. In order to standardize the data collection, the CRF guidelines should be developed in accordance with the following rules:

• Provide any instructions on mandatory/optional fields, and clearly define acceptable notations if a data item is unavailable or unknown;
• ❖ any visit that a subject failed to make;
• ❖ any clinical biological test that was missed, examinations that were not performed;
• ❖ all withdrawals and dropouts of enrolled subjects from the trial.
• Provide instructions for recording Adverse Events and Serious Adverse Events (e.g., record diagnosis instead of symptoms whenever possible).

Edit checks process

The edit checks process allows to automate data reviewing in order to reduce potential data errors and inconsistencies in accordance with the study requirements. It improves the quality of the data and reduces the data reviewing and data-cleaning activities.

Edit checks generate warnings related to missing, out of range, unexpected, incompatible data. They may also point to discrepancies with other data or study parameters.

Edit checks are mainly focused on data related to eligibility criteria to avoid protocol violations, on data related to endpoints, and on safety data. This process is directly derived from the study protocol, the CRF and the database documentation. The edit checks process should be performed directly during the data entry process (to draw attention before saving the data) or should be performed in post-processing and then will generate queries.

Data clarification process

The process allows to describe how queries will be generated, transferred to the clinical site, tracked and reviewed.

Software application

Various open source or business software applications provide all functionalities to set up a clinical data base and CRF (web-based data entry, edit check programming, queries management and data clinical trials management system). The choice between open source or commercial solutions often depends on time, budgetary considerations, and human resources and skills. These solutions generally meet regulatory requirements on data hosting, data transfer and data control access to ensure data security and confidentiality. Simple data file or even “home-made” solution should not be used without keeping in mind that these requirements have to be respected to the letter.

Legal evolution in Europe: the General Data Protection Regulation (GDPR)

The aim of the GDPR (European regulation effective May 25, 2018) is to standardize and strengthen the protection of personal data across the EU and for other country’s data being “processed” within the EU ( 9 ). Under the new regulation, each structure (industrial or institutional research) processing of the personal data of subjects residing in the Union must comply. Personal data are defined by information that allows or could allow identifying the person. It is important to distinguish identifiable data (even if it is key coded) from completely anonymous rendered data, as the GDPR applies only to the first. Personal data may contain any information relating to a person (private, professional or public life including health) ( 10 ). GDPR applies to treatment of data by a third party (a person or legal entity).

The GDPR aims: (I) to increase the rights of patients to be better informed about how their data I used and (III) to set out clearer responsibilities and obligations on healthcare professionals using such data. Transparency, security, and accountability of Data Controllers are determinant. In the GDPR, Data Controllers are defined as any person or entity which collect or process personal data. Structures involved in research must identify: (I) the data that is being processed, (II) where it is transferred to, (III) who processes the data, (IV) what it used for, (V) any risks and processes, and (VI) must ensure all people are trained.

The conditions for consent have been also consolidated: consent must be given in a clear, intelligible, and easily accessible form, using clear and plain language with the purpose of the research attached to that consent. Patients should be informed on how to withdraw consent. And finally a Data Controller has to be able to demonstrate that a person has given consent.

This GDPR does not only cover patients participating in clinical trials, but also any individual involved in medical and health research. The sponsor of the research has obligation to make sure that rules are in place, known and followed by all. Data impact assessments will be crucial, for both electronic and hard copy data. It should cover what the data will be used for, how it will be managed, and which actions will be needed. The Data Protection Officer has been also defined by the GDPR: he is responsible for overseeing data protection strategy and implementation to ensure compliance with GDPR requirements.

Patient’s rights and the existing exemptions to these rights are also well-defined in the context of research ( 9 ). Patient’s rights cover different main points such as:

• Access own personal data;
• Rectification or erasure of data;
• Being forgotten;
• Rights in case of security breach;
• Lodging a complaint and right to compensation;
• Be informed.

European law aware of the complexity of a scientific research project admits some exceptions to these principles. Derogation may be granted to the principle of information and deletion of data if this compromises the research, for example: when providing the information is a “disproportionate effort” (time or cost) or can be a problem in a blind trial.

The GDPR sets clear principles that apply to all use of personal health data and to all Data Controllers (article 5). Seven principles were extensively presented in a guide for patients and patient’s organization ( Table 1 ) ( 11 ).

Conclusions

The Data collection, the design of the case report form, the database conception, the structure and organization of the data and the data validation are essential steps of a quality database set-up.

At each all these stages, it is essential to follow rules that may appear constraining but are easy to follow and make common scientific sense. The focus should be not only on the data and their organization but also on data safety and confidentiality. Regarding this important issue, the General Data Protection Regulation has been implemented and deployed in the European Union to standardize and strengthen the protection of personal data. With this evolution of European community, it is expected that the legal framework will be prompted to evolve in Europe but also in a world-wide context.

Acknowledgements

Conflicts of Interest: The authors have no conflicts of interest to declare.

General Library Research Tutorial: Module 4: Searching a Database

• Module 1: Library Orientation
• Module 2: Developing a Topic
• Module 3: Understanding Source Types
• Module 4: Searching a Database
• Module 5: Evaluating Sources
• Module 6: Citing Sources

Ask a Librarian

Chat with a Librarian

Lisle: (630) 829-6057 Mesa: (480) 878-7514 Toll Free: (877) 575-6050 Email: [email protected]

Book a Research Consultation Library Hours

Learning Objectives

• Define the term research database.
• Differentiate between a subject and keyword search.
• Build a search using Boolean operators (AND, OR, NOT).
• Understand how to use truncation, nesting, phrase searching, and field-specific searching.

What is a Research Database?

A database is a searchable collection of information. Most  research databases are searchable collections of journal, magazine, and newspaper articles. Each database contains thousands of articles published in many different journals, allowing you find relevant articles faster than you would by searching individual journals.

Some databases provide the full text of articles. Others provide abstracts , or summaries, only.

Searching a Library database is different from searching the Internet.

Selecting a Database

Selecting the best research databases for your topic is an important step. You need to locate databases that cover your topic within the date range you need.

Find all of our databases on the Academic Databases page (from the Library website, click "Databases" in the menu bar). Use the "Subjects" dropdown menu to select your discipline. Skim through the list of databases to learn:

• Subjects covered
• Types of publications covered (e.g., journal articles, books, etc.)
• Dates covered

Keyword Searching

Keyword searches are similar to Google searches in that the database looks for your search terms wherever they may be on a page. Keyword searches search all available fields (e.g., Title, Author, Abstract, etc.) for the keyword.

In the example record below, you can see the keywords "video games" and "aggressive behavior" in bold in every field where they appear, including the Title, Subject Terms, and Abstract fields.

Subject Searching

Unlike keyword searches, subject searches only return results that include your search term in the subject headings field.

Many databases use a controlled vocabulary , which is a list of standardized subject headings used to index content. You can usually find the database's controlled vocabulary in a section called subject terms or the thesaurus . Use this tool to determine which word or phrase is the one used by the database for a specific concept. For example, since "adolescents" and "teenagers" mean roughly the same thing, a database may choose to index all articles on this topic under "teenagers." That way, a subject search for "teenagers" will also return articles about "adolescents."

In the database Academic Search Complete, we clicked "Subject Terms" in the blue menu bar. We then browsed for the term "adolescents." The search revealed that the preferred term in this database is "TEENAGERS."

Keyword vs. Subject Searching

Databases have different interfaces and use different subject terms, but most provide both keyword and subject searching. Let's take a closer look at the differences between these two search options.

Watch the video below to learn more.

Source: Wayne State University Libraries Instruction. “ Keyword vs. Subject Searching .” Online video clip. YouTube. YouTube, 9 January 2014. Web. 12 May 2017.

Phrase Searching

Place quotation marks around a phrase to search for that exact phrase. Most databases support phrase searching .

Example: A search for "United Nations" (with the quotation marks) will return only results where the two words appear together as a phrase.

For a quick demo, watch the video below.

Source: "Tips and Tricks: Phrase Searching" by North Carolina State University Libraries, licensed under a CC BY-NC-SA 3.0 US License .

Boolean Operators

When you want to combine search terms, you will need to use the Boolean operators , or connectors. This is best done using the advanced search mode. There are three main Boolean operators: AND, OR, and NOT.

Use AND to retrieve articles that mention  both terms  somewhere in the article. The use of AND generally will retrieve fewer but more focused results .

Example: Childhood obesity AND exercise

Use OR  between two terms to retrieve articles that mention  either term . The use of OR generally will retrieve a  larger set of results . The OR operator is useful when searching with terms that are synonyms or convey the same concept.

Example: Cloning OR genetics OR reproduction

Use NOT to exclude terms . The use of NOT allows you to remove search results containing a specific term. The use of NOT generally will retrieve fewer but more relevant results .

Example: Eating disorders NOT anorexia

Effective use of Boolean operators is essential to sophisticated research. Watch the video below to learn more about Boolean searching.

Source: fuliboutreach. “ Boolean Operators .” Online video clip. YouTube. YouTube, 30 September 2012. Web. 4 May 2017.

Field Specific Searching

A good technique for focusing a database search is to limit your search to a specific field. Do a field-specific search when you are looking for:

• articles in a particular journal
• items published in a particular year or years
• particular keywords in the title
• items written in English only

Example: Search for "Eating Disorders" as a keyword; search for "Gupta" in the Author field; search "Secondary Eating Disorder" in the Title field.

Truncation is a search technique that allows you to search for all variants of a root word at the same time. Enter the root word followed by the truncation symbol. Many databases use the asterisk (*)  for truncation. Others use the question mark (?). Check the Help page for the database you're using to determine which symbol to use for truncation.

Example: The search term plagiar* will return results that include terms:

• plagiarizing
• plagiarized
• plagiarizer
• plagiarizers

Broadening Your Search

Keep in mind that if you're looking for an all-in-one source that addresses your topic perfectly, you might need to change your approach. Watch this short video to learn what to do when you can't find enough resources on your topic.

Source: “One Perfect Source?” by North Carolina State University Libraries, licensed under a CC BY-NC-SA 3.0 US License .

Module 4 Quiz

• << Previous: Module 3: Understanding Source Types
• Next: Module 5: Evaluating Sources >>
• Last Updated: Feb 19, 2023 5:21 PM
• URL: https://researchguides.ben.edu/general-research

Kindlon Hall 5700 College Rd. Lisle, IL 60532 (630) 829-6050

Gillett Hall 225 E. Main St. Mesa, AZ 85201 (480) 878-7514

ASU Online Library Guide

What is a research database, research tools, multidisciplinary research dababases, start searching, navigating to the next page....

• Physical and Other Materials
• Subject Librarians
• Citations, Tutorials & More

Need More Help?

Ask a librarian.

View all hours  (subject to change) Read policy and privacy info

ASU Directory

Help Center and Technical Support   | 1-855-278-5080 

Library Disability Services   | 1-480-965-2600; [email protected] 

Interlibrary Loan  | 1-480-965-3282 or [email protected]

The Library One Search, located on the main page of the ASU Library webpage, brings up all library materials including physical and digital. One of the most common digital resources you will find are articles from research databases.  Research databases  provide access to published  magazine  and  scholarly journal  articles that you will generally NOT find freely on the internet. 

You will need your ASURITE ID and password to access ASU Library research databases.

To learn more about what a research database is, and why you should use them, view this tutorial:

There are three main ways to access research databases:

• Research Databases List : The Research Databases List contains all the databases available through ASU Library. You can find databases alphabetically, by subject or by database/source type. This then leads you to s earchable collections of articles and article citations from newspapers, magazines, scholarly journals, trade publications and more.
• Library One Search :  Using Library One Search not only allows you to search research databases, but it will pull up all materials and resources in the ASU Library as well. It even includes an option to search the Library Catalog only.
• WorldCat :  WorldCat is the world's largest network of library content and services. WorldCat libraries are dedicated to providing access to their resources on the Web, where most people start their search for information.

-       IMPORTANT!       - 

When using any resources from the ASU Library or elsewhere, keep in mind that you must cite all of your sources to comply with ASU's  Academic Integrity . Here is more information on  Citation Styles . If you are unsure of which citation style to use, please check with your professor. 

Coverage: 1909+ Maximum concurrent users: Unlimited A multidisciplinary periodical index which provides access to popular press magazines and scholarly (including peer-reviewed) journals from nearly every academic discipline. Includes content from international publishers, a growing collection of open access journals, and a large historic collection of video recordings from the Associated Press. Content may fluctuate at the publishers’ discretion.

Maximum Concurrent Users: Unlimited Provides full text of selected newspapers worldwide, trade publications, legal periodicals, and legal scholarly journals. Includes company directories, financial reports, quotations, biographies, almanac, federal/state laws, regulations, court opinions, accounting statements/guidelines, and news transcripts.

• Dissertations & Theses Global This link opens in a new window Coverage: 1861+ Maximum Concurrent Users: Unlimited A comprehensive collection of full-text dissertations and theses that includes millions of searchable citations to dissertations and theses from 1861 to the present day together with over a million full-text dissertations that are available for download in PDF format. The database offers full text for most of the dissertations added since 1997 and provides strong retrospective full-text coverage for older graduate works. It also includes PQDT UK & Ireland content. more... less... Alternate titles: ProQuest Dissertations and Theses Global

Google Scholar is an enhanced version of Google that provides scholarly research results. If you use this search box (or the Google Scholar link on the library home page) you will be connected to full text links via the ASU Library. Watch this  tutorial  about using Google Scholar at ASU Library!

Click here to go to the Physical and Other Materials page  to learn more on how to request, borrow, and return books, chapters, articles, microform, materials not available at ASU Library, and more.

• << Previous: Home
• Next: Physical and Other Materials >>
• Last updated: Feb 27, 2024 12:44 PM
• URL: https://libguides.asu.edu/online

The ASU Library acknowledges the twenty-three Native Nations that have inhabited this land for centuries. Arizona State University's four campuses are located in the Salt River Valley on ancestral territories of Indigenous peoples, including the Akimel O’odham (Pima) and Pee Posh (Maricopa) Indian Communities, whose care and keeping of these lands allows us to be here today. ASU Library acknowledges the sovereignty of these nations and seeks to foster an environment of success and possibility for Native American students and patrons. We are advocates for the incorporation of Indigenous knowledge systems and research methodologies within contemporary library practice. ASU Library welcomes members of the Akimel O’odham and Pee Posh, and all Native nations to the Library.

Research Tutorial

• Introduction
• Understanding Your Assignment
• Developing Key Term from Your Topic
• Creating Searches
• Searching the Library Catalog
• Finding Books on the Shelf
• The Call Number System
• What Are Databases?
• Accessing Databases
• Off Campus Access

Choosing a Database

• The Mechanics of Searching
• Finding Websites
• Evaluating Websites
• What Every Citation Needs
• Citation Formats
• Making the Databases Work for You
• Resources for Citation Formats

In Databases: An Introduction , we showed you how to find a list of databases that are relevant to your topic. But that still leaves you with a number of different choices. So how do you know which database to start with? Most databases fall into two categories:

• General databases
• Subject-specific databases

General databases cover many subject areas in one place. Subject-specific databases focus on one particular subject area. You can read the descriptions of the databases to get a sense of if it is general or subject-specific (sometimes the name of the database will give you a clue, too!).

This is an example of a general database:

These are examples of subject specific databases:

So which should you use? Well, ideally, you'll use both types. General databases are a really good place to start your research. Because they cover lots of subject areas, you can be fairly confident that your search will turn up something. However, as you do more research on your topic, you may need to turn to the subject-specific databases to fill in holes or to drill deeper into your subject.

• << Previous: Searching in Databases
• Next: The Mechanics of Searching >>
• Last Updated: Dec 19, 2023 2:36 PM
• URL: https://libguides.hartford.edu/ResearchTutorial

A-Z Site Index | Contact Us | Directions | Hours | Get Help

University of Hartford | 200 Bloomfield Avenue, West Hartford, CT 06117 Harrison Libraries © 2020 | 860.768.4264

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Trending Articles

• Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. GBD 2021 Fertility and Forecasting Collaborators. Lancet. 2024. PMID: 38521087
• Single-cell dissection of the human motor and prefrontal cortices in ALS and FTLD. Pineda SS, et al. Cell. 2024. PMID: 38521060
• The effects of pregnancy, its progression, and its cessation on human (maternal) biological aging. Pham H, et al. Cell Metab. 2024. PMID: 38521058 No abstract available.
• Plasma interleukin-41 serves as a potential diagnostic biomarker for Kawasaki disease. Cai X, et al. Microvasc Res. 2023. PMID: 36682486
• Pembrolizumab or placebo with chemoradiotherapy followed by pembrolizumab or placebo for newly diagnosed, high-risk, locally advanced cervical cancer (ENGOT-cx11/GOG-3047/KEYNOTE-A18): a randomised, double-blind, phase 3 clinical trial. Lorusso D, et al. Lancet. 2024. PMID: 38521086

Latest Literature

• Am J Surg Pathol (1)
• Clin Infect Dis (1)
• Gastroenterology (3)
• J Neurosci (3)
• Methods Mol Biol (15)
• Nat Commun (41)
• Nature (19)
• Nucleic Acids Res (1)
• Oncogene (1)
• Pediatrics (2)

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

News alert: UC Berkeley has announced its next university librarian

Secondary menu

• Log in to your Library account
• Hours and Maps
• Connect from Off Campus
• UC Berkeley Home

Search form

• UC Berkeley
• Library Guides

A-Z Databases

Related links.

Find: eJournals

Browse: General article databases News article databases Book and film review databases

Help: Finding articles Finding databases Finding resources for text mining Research help Disability Resources Report a problem

More information: Conditions of use Known problems

New Databases

Frequently asked questions

How do i search research databases efficiently.

When searching for sources in databases, think of specific keywords that are relevant to your topic , and consider variations on them or synonyms that might be relevant.

Once you have a clear idea of your research parameters and key terms, choose a database that is relevant to your research (e.g., Medline, JSTOR, Project MUSE).

Find out if the database has a “subject search” option. This can help to refine your search. Use Boolean operators to combine your keywords, exclude specific search terms, and search exact phrases to find the most relevant sources.

Frequently asked questions: Working with sources

Synthesizing sources means comparing and contrasting the work of other scholars to provide new insights.

It involves analyzing and interpreting the points of agreement and disagreement among sources.

You might synthesize sources in your literature review to give an overview of the field of research or throughout your paper when you want to contribute something new to existing research.

You can find sources online using databases and search engines like Google Scholar . Use Boolean operators or advanced search functions to narrow or expand your search.

For print sources, you can use your institution’s library database. This will allow you to explore the library’s catalog and to search relevant keywords.

Lateral reading is the act of evaluating the credibility of a source by comparing it with other sources. This allows you to:

• Verify evidence
• Contextualize information
• Find potential weaknesses

As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.

This involves:

• Reading abstracts , prefaces, introductions , and conclusions
• Looking at the table of contents to determine the scope of the work
• Consulting the index for key terms or the names of important scholars

An abstract concisely explains all the key points of an academic text such as a thesis , dissertation or journal article. It should summarize the whole text, not just introduce it.

An abstract is a type of summary , but summaries are also written elsewhere in academic writing . For example, you might summarize a source in a paper , in a literature review , or as a standalone assignment.

All can be done within seconds with our free text summarizer .

You might have to write a summary of a source:

• As a stand-alone assignment to prove you understand the material
• For your own use, to keep notes on your reading
• To provide an overview of other researchers’ work in a literature review
• In a paper , to summarize or introduce a relevant study

You can assess information and arguments critically by asking certain questions about the source. You can use the CRAAP test , focusing on the currency , relevance , authority , accuracy , and purpose of a source of information.

Ask questions such as:

• Who is the author? Are they an expert?
• Why did the author publish it? What is their motivation?
• How do they make their argument? Is it backed up by evidence?

Critical thinking skills include the ability to:

• Identify credible sources
• Evaluate and respond to arguments
• Assess alternative viewpoints
• Test hypotheses against relevant criteria

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

It is important to find credible sources and use those that you can be sure are sufficiently scholarly .

• Consult your institute’s library to find out what books, journals, research databases, and other types of sources they provide access to.
• Look for books published by respected academic publishing houses and university presses, as these are typically considered trustworthy sources.
• Look for journals that use a peer review process. This means that experts in the field assess the quality and credibility of an article before it is published.

In academic writing, the sources you cite should be credible and scholarly. Some of the main types of sources used are:

• Academic journals: These are the most up-to-date sources in academia. They are published more frequently than books and provide cutting-edge research.
• Books: These are great sources to use, as they are typically written by experts and provide an extensive overview and analysis of a specific topic.

Scholarly sources are written by experts in their field and are typically subjected to peer review . They are intended for a scholarly audience, include a full bibliography, and use scholarly or technical language. For these reasons, they are typically considered credible sources .

Popular sources like magazines and news articles are typically written by journalists. These types of sources usually don’t include a bibliography and are written for a popular, rather than academic, audience. They are not always reliable and may be written from a biased or uninformed perspective, but they can still be cited in some contexts.

There are many types of sources commonly used in research. These include:

• Journal articles
• Encyclopedias

You’ll likely use a variety of these sources throughout the research process , and the kinds of sources you use will depend on your research topic and goals.

You usually shouldn’t cite tertiary sources as evidence in your research paper, but you can use them in the beginning stages of the research process to:

• Establish background information
• Identify relevant keywords and terms
• Familiarize yourself with current debates in your field

Use tertiary sources in your preliminary research to find relevant primary and secondary sources that you will engage with in more depth during the writing process .

What constitutes a tertiary source depends on your research question and how you use the source.

To determine whether a source is tertiary, ask:

• Am I examining the source itself, or am I using it for background information?
• Does the source provide original information ( primary ) or analyze information from other sources ( secondary )? Or does it consolidate information from other sources (tertiary)?

Primary sources provide direct evidence about your research topic (photographs, personal letters, etc.).

Secondary sources interpret and comment on information from primary sources (academic books, journal articles, etc.).

Tertiary sources are reference works that identify and provide background information on primary and secondary sources . They do not provide original insights or analysis.

A tertiary source may list, summarize , or index primary and secondary sources or provide general information from a variety of sources. But it does not provide original interpretations or analysis.

Some examples of tertiary sources include:

• Bibliographies
• Dictionaries

It can sometimes be hard to distinguish accurate from inaccurate sources , especially online. Published articles are not always credible and can reflect a biased viewpoint without providing evidence to support their conclusions.

Information literacy is important because it helps you to be aware of such unreliable content and to evaluate sources effectively, both in an academic context and more generally.

Information literacy refers to a broad range of skills, including the ability to find, evaluate, and use sources of information effectively.

Being information literate means that you:

• Know how to find credible sources
• Use relevant sources to inform your research
• Understand what constitutes plagiarism
• Know how to cite your sources correctly

Proximity operators are specific words used alongside your chosen keywords that let you specify the proximity of one keyword in relation to another.

The most common proximity operators include NEAR ( N x ), WITHIN ( W x ), and SENTENCE .

Each proximity operator has a unique function. For example, N x allows you to find sources that contain the specified keywords within a set number of words ( x ) of each other.

Boolean operators are specific words and symbols that you can use to expand or narrow your search parameters when using a database or search engine.

The most common Boolean operators are AND , OR , NOT or AND NOT , quotation marks “” , parentheses () , and asterisks * .

Each Boolean operator has a unique function. For example, the Boolean operator AND will provide search results containing both/all of your keywords.

A Boolean search uses specific words and symbols known as Boolean operators (e.g., AND , OR ) alongside keywords to limit or expand search results. Boolean searches allow you to:

• Prioritize keywords
• Exclude keywords
• Search exact keywords
• Search variations of your keywords

The CRAAP test is an acronym to help you evaluate the credibility of a source you are considering using. It is an important component of information literacy .

The CRAAP test has five main components:

• Currency: Is the source up to date?
• Relevance: Is the source relevant to your research?
• Authority: Where is the source published? Who is the author? Are they considered reputable and trustworthy in their field?
• Accuracy: Is the source supported by evidence? Are the claims cited correctly?
• Purpose: What was the motive behind publishing this source?

To avoid plagiarism when summarizing an article or other source, follow these two rules:

• Write the summary entirely in your own words by paraphrasing the author’s ideas.
• Cite the source with an in-text citation and a full reference so your reader can easily find the original text.

A summary is always much shorter than the original text. The length of a summary can range from just a few sentences to several paragraphs; it depends on the length of the article you’re summarizing, and on the purpose of the summary.

A summary is a short overview of the main points of an article or other source, written entirely in your own words. Want to make your life super easy? Try our free text summarizer today!

Ask our team

Want to contact us directly? No problem.  We  are always here for you.

• Email [email protected]
• Start live chat
• Call +1 (510) 822-8066
• WhatsApp +31 20 261 6040

Our team helps students graduate by offering:

• A world-class citation generator
• Plagiarism Checker software powered by Turnitin
• Innovative Citation Checker software
• Professional proofreading services
• Over 300 helpful articles about academic writing, citing sources, plagiarism, and more

Scribbr specializes in editing study-related documents . We proofread:

• PhD dissertations
• Research proposals
• Personal statements
• Admission essays
• Motivation letters
• Reflection papers
• Capstone projects

Scribbr’s Plagiarism Checker is powered by elements of Turnitin’s Similarity Checker , namely the plagiarism detection software and the Internet Archive and Premium Scholarly Publications content databases .

The add-on AI detector is powered by Scribbr’s proprietary software.

The Scribbr Citation Generator is developed using the open-source Citation Style Language (CSL) project and Frank Bennett’s citeproc-js . It’s the same technology used by dozens of other popular citation tools, including Mendeley and Zotero.

You can find all the citation styles and locales used in the Scribbr Citation Generator in our publicly accessible repository on Github .

Jump to navigation

Search form

Intersession hours Jan. 3-11. The Libraries are open daily during intersession. Get more details.

A-Z Databases

Featured databases, new / trial databases.

• Privacy Policy
• Support The Blog

Your Ultimate Guide To Using Research Databases

Ahh, research databases. These can be very difficult to use, especially if you have never used them before. The easiest way is to honestly get in there and play around with it a bit, but today I am going to be showing you some excellent tips and tricks to using your libraries databases and research articles to find all the articles you need for any research paper in no time.

1. Understand That This Is Not A Google Search

A lot of people make the unfortunate mistake of treating research databases like they are Google searches. This is not a good idea, and will likely confuse your database and give you poor results. Instead, you need to be short, sweet, and to the point. Your research database of choice will appreciate it.

So, instead of asking your research database:

What is a hate group?

Search for the following term in your research database:

To a lot of students that probably seems weird, but remember, you shouldn't have the same issues within a library research database that you might have with Google. On Google, if your search hate group, there is a good chance that bunch of irrelevant items come up. Unless you type the statement, “What is a hate group?” You might get some less than stellar returns, and even some links to some hate group websites. That's no fun unless you were researching and looking to stumble upon actual hate group websites.

With research databases, on the other hand, you are not browsing the entirety of the world wide web, so you don't have to ask your database questions.

You Want To Be As Succinct As Possible

So, you see, in the above scenario, I would look up “hate group.”  This would probably lead me to several different sources talking about all areas of hate groups. Some articles may explain what they are as well as different well-known hate groups, how hate groups use certain things like social media/websites, and a whole slew of other data.

If I wanted to find other terms to use for hate groups, I could search for those. I could look up specific hate groups in the database after being more familiar with hate groups, which would help me greatly as I am writing my research. As you do more research, you are bound to find better search terms and even more content. Keep searching within your databases.

2. Get Restrictive When Using Research Databases

Even if I am super succinct in my search terms, I will likely still get way too many search results. After you have a concise search term, it's essential to use the databases advanced search features to get specific.

Make Sure You Are Only Looking At Peer Reviewed Articles

The first thing you should do is make sure that you are only looking at scholarly, peer-reviewed articles––especially if you are writing a literature review or your professor calls for this. Sometimes, using things like magazine articles and newspapers are okay, but for the most part, you want to fill your paper with scholarly articles. Databases usually don't check this off automatically, so there is a good chance that your results include pieces that aren't peer-reviewed when you first make a search request. Tick this box and watch your potential sources dwindle (in a good way!)

Use Boolean Operators

When I am using research databases, I adore boolean operators. These are three shortcuts that can help drastically reduce or widen your search results. Once you understand them, they can be powerful research tools.

This is a restrictive boolean operator. It means that you are looking for two things in your research. For instance, if I want to look at hate groups AND I wanted articles just on one particular hate group, I can add that hate group as an AND boolean phrase. The result will be that I will only get articles that mention the word hate group AND the particular hate group I am looking for.

This is an expanding boolean operator. I don't use this one as much in my research because it can expand the search results too much. Let's go back to my example of hate groups. Maybe I want to look up different types of hate groups. So I might name a hate group, as my original phrase and decide that I don't get enough results from that. Then I might choose to make the boolean phrase “Hate Group #1” OR “Hate Group #2” This will show me articles that include both of the hate groups in the article, but it will also show me articles just about Hate Group #1 OR just about Hate Group #2.

This is another restrictive operator, but it is not nearly as restrictive as AND. So say, I had a hate group that I didn't want to learn about. I could make the boolean phrase “Hate groups” NOT “Hate Group #3.” This means that I will not be shown any articles that include Hate Group #3 in the article. Depending on how closely related your words are you could end up excluding more than you think, so be careful when you are setting up this boolean operator.

Check out this library guide from MIT that does an excellent job at teaching you all about boolean operators, probably better than I ever could.

Restrict The Years You Look At In Research Databases

Academia has changed a lot over the years, and sometimes you don't want to include specific years in your analysis. Your professor may also urge you to only look at more recent years in your analysis. There is usually an amount of restriction that you can do within a research database using a slider of some sort so that you are only getting the more recent information. I usually try to keep most of my research within the past 15 years if I am doing a paper. If there is an older important work, you can usually find it by observing the recent articles you are looking at.

Other Restrictions

There are so many different ways that you can restrict your search:

• Only Articles You Have Full-Text Access To: I love having full-text articles, but I don't usually tick this box. Most schools have great interlibrary loan systems in place that make borrowing books and articles your school doesn't have moderately easy. It's better to know that an article exists and that you can borrow it from another library.
• Publisher/Journal: Some publishers and journals are better than others. You can usually sort the articles by the publisher and/or journal so that you can make sure that you are getting top-notch information.
• Language: Unless you fluently speak another language or languages, ticking the box to get articles in your language is probably a good idea. This can be extremely helpful for making sure you are only getting the most relevant results for you and your language skills.

3. Quickly Scan Your Sources

When I am doing research, there are a couple of distinct phases in that research. Some of those phases include looking at the articles in depth, but while I am doing research looking for pieces to collect, I am not a fan of in-depth article reading. It's pretty easy to scan an article to see if it would be of any help to you once you are looking at it. A quick scan of the following will help:

• What journal was the article published in?
• What is the title of the article?
• How long is the article?
• What school(s) are the author(s) representing?
• What does the abstract say?
• When was the article published?
• What are the introductory/closing paragraphs talking about?
• How many sources does the article have?
• What potential biases does the paper have? (This is usually disclosed pretty early on, how did they fund their research?)

Once you look through some of these things, you can usually easily determine a paper's potential worth to you as a researcher. Don't spend too much time on this, if your gut says the paper is worthless, it probably is.

4. Have A Master Reference List

This summer, I got some great behind the scenes looks at one of the professors I was a graduate assistant for and her paper writing process. One cool thing she taught me was all about having a reference master list. She had stockpiled pages and pages of sources, and in the end, only a couple of those pages made it into her final project. This is something I intend to do as I am writing my thesis, and I have already started my thesis master list. Starting this list allows you to stockpile data and sources so that when you are writing your paper, you have a lot of great sources.

Once I get done skimming the article for its potential worthiness, I download the article to my folder dedicated to the paper I am currently writing. Then I also grab the appropriate citation (usually given by the database website) and add it to my master reference list.

Once you do more research on the topic at hand, you should be able to do even more separation. You may have many sections of your master reference list devoted to the issues you are covering in your paper. You can re-arrange your master reference list however you would like––and you may even want to go in after a while and add summaries underneath all of the references on your master reference list.

5. Use Sources To Find Sources

Listen up. This is the best advice I have ever gotten on finding sources. If you can find ten trustworthy sources, I am going to teach you how to turn those sources into 40-50 sources in no time. Use sources to find sources! When you have an excellent paper that is on brand with the work that you are creating––use that paper's resources section to find more sources. When I am doing research, and I find an excellent paper, I go through their sources one by one looking for sources that catch my eye. Once I find those sources, I look them up on my libraries database. A lot of the time we have the paper I am looking for, and when we don't, I can usually request the article through Interlibrary Loan.

You could be searching through the resources of other people's papers for literally hours. Once you are done with one paper, you can go on to look at the sources of the papers you just found. It's a never-ending cycle.

This can create some great sources for your paper, more than anything you could potentially ever do by looking up a million search terms. Yes, your database is great, but why stop there? Let your papers work for you and find all those cool papers you never even knew about.

6. Know When To Quit

When you are doing research, there comes a time when you have done all the research that you can. It is essential to know when to quit doing research. Research is excellent, but it can be a time suck when it comes to getting things done on your paper.

• Have An End Goal In Mind: Don't just start doing research, you will never finish researching if you don't know why you are researching. It's okay to do a couple of searches without direction, but after a while, you need guidance so you can have a better idea of when you are done.
• Have a goal amount of articles in mind: If your paper requires 20 sources, you probably want to look at more than 20 sources, but you definitely shouldn't be looking at 500. Make sure you have a goal in mind of the number of sources you want to gather.
• Outline Your Paper: Outlining your paper allows you to better understand the sources you are looking for and what you need for your writing to be successful. Your outline can be a simple one-pager, and this will help you when it comes to researching for your paper.

Use Research Databases With Me

I love doing research, and I wanted to walk you through my research process as well as give you a ton of different research nuggets. I filmed this 20-minute video just for you where I walk through an EBSCOHost database and show y'all some awesome tips and tricks. Chances are your school has an EBSCOHost database or two (or even dozens.) Once you get down the basics on one database, it's effortless to transfer that knowledge to other databases (even ones that aren't EBSCOHost) so check out the video below for lots of tips and tricks.

I hope you found this video helpful and used it to put the words I talked about into action.

What is your personal favorite research tip/trick?

Amanda Cross

Amanda is the original voice behind The Happy Arkansan. She is a happiness enthusiast with a passion for helping others, marketing, and red/purple lipstick.

Leave a Comment Cancel Comment

Notify me of follow-up comments by email.

Notify me of new posts by email.

The Comments

Steph Yorke

This is so interesting! 🙂 I haven’t had to write a research paper yet, but I’m sure it’ll be coming soon. I love your tips, I usually like to use similar techniques when researching a topic for work. Bookmarking this page for future reference!

You May Also Like

Freshmen tips: getting to know people, college essentials: dealing with a horrible professor, how to prioritize self-care during finals week.

ScienceSphere.blog

Mastering The Art Of Creating A Research Database: A Step-By-Step Guide

Research databases play a crucial role in the world of academia, business, and various other fields. They provide a centralized and organized platform for storing, managing, and analyzing vast amounts of data. In this blog post, we will explore the importance of research databases and discuss the purpose of this article.

Table of Contents

Importance of Research Databases

Research databases are essential tools for researchers, students, and professionals alike. They offer a wealth of information that can be accessed and utilized for various purposes, such as:

Efficient Data Storage : Research databases provide a structured and organized way to store large volumes of data. This ensures that information is easily accessible and can be retrieved quickly when needed.

Data Integration : Databases allow for the integration of data from multiple sources, enabling researchers to analyze and draw insights from diverse datasets. This integration can lead to more comprehensive and accurate research outcomes.

Data Security : Research databases offer robust security measures to protect sensitive information. Access controls, encryption, and regular backups ensure that data remains secure and protected from unauthorized access or loss.

Collaboration and Sharing : Databases facilitate collaboration among researchers by providing a centralized platform for sharing data and findings. This promotes knowledge exchange and accelerates the progress of research projects.

Purpose of the Blog Post

The purpose of this blog post is to guide readers through the process of creating a research database. We will cover the essential steps involved in designing, implementing, and maintaining a database for research purposes. By following these steps, readers will gain a solid understanding of how to create an effective research database that meets their specific needs.

Throughout this article, we will explore topics such as:

Understanding the Basics of Research Databases : We will define research databases, discuss their types, and highlight the benefits of using them. Additionally, we will explore the common features found in research databases.

Step 1: Defining the Research Objectives : This step involves identifying the purpose of the research, determining the scope and focus of the database, and setting clear goals and objectives.

Step 2: Designing the Database Structure : Here, we will delve into choosing the appropriate database management system, creating tables, and establishing relationships between them.

Step 3: Collecting and Organizing Data : This step focuses on identifying relevant sources for data collection, extracting and importing data into the database, and ensuring data accuracy and consistency.

Step 4: Implementing Data Validation and Security Measures : We will discuss the importance of setting up data validation rules, implementing user access controls, and regularly backing up the database to ensure data integrity and security.

Step 5: Querying and Analyzing Data : This step involves writing SQL queries to retrieve specific information, utilizing data analysis tools and techniques, and generating reports and visualizations for data analysis.

Step 6: Maintaining and Updating the Database : We will explore the importance of regularly reviewing and cleaning the database, updating and adding new data as needed, and monitoring performance to optimize the database’s efficiency.

By the end of this blog post, readers will have a comprehensive understanding of the steps involved in creating a research database. They will be equipped with the knowledge and skills necessary to embark on their own database creation journey and master the art of managing research data effectively.

Understanding the Basics of Research Databases

Research databases play a crucial role in the world of academia and scientific research. They provide a centralized platform for storing, organizing, and accessing vast amounts of information. In this section, we will delve into the basics of research databases, including their definition, types, and the benefits they offer. We will also explore the common features that make research databases an indispensable tool for researchers.

Definition and Types of Research Databases

A research database is a structured collection of data that is specifically designed to support research activities. It serves as a repository for various types of information, such as scholarly articles, research papers, datasets, and more. These databases are typically created and maintained by organizations, universities, or specialized institutions.

There are different types of research databases available, each catering to specific research needs. Some common types include:

Bibliographic Databases : These databases focus on providing information about published research articles, including details such as authors, titles, abstracts, and keywords. Examples of popular bibliographic databases include PubMed, Scopus, and Web of Science.

Full-Text Databases : These databases contain the complete text of research articles, allowing researchers to access the entire content of a publication. Examples of full-text databases include JSTOR, ScienceDirect, and IEEE Xplore.

Subject-Specific Databases : These databases are dedicated to specific subject areas or disciplines, providing comprehensive coverage of research within those fields. Examples include PsycINFO for psychology research and ACM Digital Library for computer science.

Benefits of Using Research Databases

Research databases offer numerous benefits that significantly enhance the research process. Here are some key advantages:

Access to a Wide Range of Information : Research databases provide access to a vast collection of scholarly resources, enabling researchers to explore a wide range of topics and stay up-to-date with the latest research in their field.

Efficient Search and Retrieval : These databases are equipped with advanced search functionalities, allowing researchers to quickly find relevant articles, papers, or datasets based on specific criteria such as keywords, authors, or publication dates.

Quality and Credibility : Research databases often include peer-reviewed and reputable sources, ensuring the reliability and credibility of the information available. This helps researchers avoid unreliable or biased sources.

Time and Cost Savings : By utilizing research databases, researchers can save valuable time and resources that would otherwise be spent on manually searching for and accessing individual research articles or papers.

Common Features of Research Databases

Research databases typically offer a range of features that facilitate efficient data management and retrieval. Some common features include:

Advanced Search Capabilities : Research databases provide powerful search functionalities, allowing researchers to perform complex queries and refine their search results based on specific criteria.

Filters and Sorting Options : These databases often include filters and sorting options that enable researchers to narrow down their search results based on factors such as publication date, author, or journal.

Citation Management : Many research databases offer citation management tools, allowing researchers to easily generate citations in various citation styles, such as APA or MLA.

Alerts and Notifications : Researchers can set up alerts and notifications to stay informed about new publications or updates in their field of interest.

In conclusion, understanding the basics of research databases is essential for researchers looking to streamline their research process and access reliable and relevant information. By utilizing these databases, researchers can save time, access a wide range of resources, and ensure the credibility of their research findings. The next section will delve into the steps involved in creating a research database, providing a comprehensive guide for researchers to follow.

Step 1: Defining the Research Objectives

In the process of creating a research database, defining the research objectives is a crucial step. This step sets the foundation for the entire database and ensures that it aligns with the goals and purpose of the research. Here are the key aspects to consider when defining the research objectives:

Identifying the purpose of the research

Before diving into the database design, it is essential to have a clear understanding of the purpose of the research. What are you trying to achieve? Are you conducting market research, academic research, or scientific research? Defining the purpose will help you determine the type of data you need to collect and the structure of your database.

Determining the scope and focus of the database

Once you have identified the purpose of your research, it is important to determine the scope and focus of your database. This involves deciding what specific aspects of the research you want to capture in your database. For example, if you are conducting market research, you may want to focus on customer demographics, purchasing behavior, and market trends. Defining the scope will help you narrow down the data you need to collect and organize.

Setting clear goals and objectives

To ensure the success of your research database, it is crucial to set clear goals and objectives . These goals will guide your database design and help you stay focused throughout the process. For example, your goal might be to analyze customer behavior patterns to improve marketing strategies. Your objectives could include collecting data on customer demographics, purchase history, and preferences. Setting clear goals and objectives will help you stay organized and ensure that your database serves its intended purpose.

Defining the research objectives is a critical step that lays the foundation for the entire research database. It helps you understand the purpose of your research, determine the scope and focus of your database, and set clear goals and objectives. By investing time and effort into this step, you can ensure that your research database is designed to effectively capture and analyze the data you need.

Step 2: Designing the Database Structure

Designing the structure of a research database is a crucial step in the process of creating an effective and efficient database. It involves making decisions about the database management system, creating tables, and establishing relationships between them. Let’s delve into the details of this step.

Choosing the Appropriate Database Management System

The first decision you need to make when designing a research database is selecting the right database management system (DBMS). There are various DBMS options available, such as MySQL, Oracle, and Microsoft SQL Server. Choosing the appropriate DBMS is essential as it determines the functionality, scalability, and security of your database.

Consider factors like the size of your dataset, the complexity of your research, and your budget when selecting a DBMS. Each DBMS has its own strengths and weaknesses, so it’s important to evaluate your specific requirements before making a decision.

Creating Tables and Defining Fields

Once you have chosen a DBMS, the next step is to create tables and define fields. Tables are used to organize and store data in a structured manner. Each table represents a specific entity or concept in your research.

When creating tables, you need to identify the different attributes or characteristics that describe the entity. These attributes become the fields or columns of the table. For example, if you are creating a research database for a university, you might have tables for students, courses, and grades. The fields in the student table could include student ID, name, and date of birth.

It’s important to define the data types for each field, such as text, number, date, or boolean. This ensures that the data is stored correctly and can be easily queried and analyzed later on.

Establishing Relationships Between Tables

In a research database, data is often related to each other. For example, in our university database, a student is enrolled in multiple courses, and each course has multiple students. To represent these relationships, you need to establish relationships between tables .

There are different types of relationships, such as one-to-one, one-to-many, and many-to-many. One-to-one relationships occur when each record in one table is associated with only one record in another table. One-to-many relationships occur when each record in one table can be associated with multiple records in another table. Many-to-many relationships occur when multiple records in one table can be associated with multiple records in another table.

To establish relationships, you need to define primary and foreign keys . A primary key is a unique identifier for each record in a table, while a foreign key is a field that refers to the primary key of another table. This allows you to link related data across tables and ensure data integrity.

Designing the database structure is a critical step that lays the foundation for a well-organized and efficient research database. By choosing the right DBMS, creating tables, and establishing relationships between them, you can ensure that your database is capable of handling your research needs effectively.

Remember, careful planning and consideration during this step will save you time and effort in the long run. So take the time to understand your research requirements and design a database structure that aligns with your goals.

Step 3: Collecting and Organizing Data

Collecting and organizing data is a crucial step in creating a research database. It involves identifying relevant sources, extracting and importing data, and ensuring its accuracy and consistency. Let’s delve into the details of this step.

Identifying relevant sources for data collection

To build a comprehensive research database, it is essential to identify the most relevant sources for data collection. These sources can include academic journals, industry reports, government databases, surveys, and more. Thorough research is required to find credible and up-to-date sources that align with the research objectives.

Extracting and importing data into the database

Once the relevant sources have been identified, the next step is to extract and import the data into the database. This process can vary depending on the format of the data and the database management system being used. Data extraction involves retrieving information from the selected sources, while data import involves transferring the extracted data into the database.

It is important to ensure that the data is properly formatted and structured during the import process. This includes organizing the data into appropriate tables and defining the fields accurately. Data normalization techniques can be applied to eliminate redundancy and improve data integrity.

Ensuring data accuracy and consistency

Data accuracy and consistency are vital for the reliability of a research database. It is crucial to implement measures to ensure that the data being collected and organized is accurate and consistent. This can be achieved through various techniques, such as:

Data validation : Implementing validation rules to check the integrity and accuracy of the data being entered into the database. This can include checks for data types, ranges, and constraints.

Data cleansing : Regularly reviewing and cleaning the data to remove any errors, duplicates, or inconsistencies. This can involve techniques like deduplication, standardization, and data profiling.

Data integration : Integrating data from multiple sources to ensure consistency and eliminate discrepancies. This can be done through data matching and merging techniques.

By implementing these measures, researchers can ensure that the data in their research database is reliable and can be used for accurate analysis and decision-making.

Collecting and organizing data is a critical step in creating a research database. It involves identifying relevant sources, extracting and importing data, and ensuring its accuracy and consistency. By following these steps diligently, researchers can build a robust and reliable research database that serves as a valuable resource for their studies.

Step 4: Implementing Data Validation and Security Measures

In the world of research databases, data validation and security measures play a crucial role in ensuring the integrity and confidentiality of the information stored. Implementing these measures is essential to protect sensitive data and maintain the accuracy and reliability of the database. Let’s explore the key steps involved in this process.

Setting up data validation rules

Data validation is the process of ensuring that the data entered into the database meets specific criteria and is accurate. By setting up data validation rules , you can prevent the entry of incorrect or inconsistent data, reducing the chances of errors and improving data quality.

To implement data validation, you need to define rules for each field in the database. For example, you can set rules to ensure that a date field follows a specific format, or that a numeric field only accepts positive values. By enforcing these rules, you can maintain data consistency and integrity.

Implementing user access controls

Protecting the confidentiality and security of your research database is of utmost importance. One way to achieve this is by implementing user access controls . This involves assigning different levels of access to different users based on their roles and responsibilities.

By granting appropriate access privileges, you can ensure that only authorized individuals can view, modify, or delete data within the database. This helps prevent unauthorized access and reduces the risk of data breaches or misuse.

Additionally, implementing user access controls allows you to track and monitor user activities within the database. This audit trail can be valuable in identifying any suspicious or unauthorized actions and helps maintain the overall security of the system.

Regularly backing up the database

No matter how robust your data validation and security measures are, there is always a possibility of data loss or corruption. That’s why it is crucial to regularly back up your research database.

Backing up the database involves creating a copy of the entire database or specific tables and storing them in a separate location. This ensures that even if the original database is compromised or damaged, you can restore the data from the backup.

It is recommended to establish a regular backup schedule, depending on the frequency of data updates and the criticality of the information stored. This way, you can minimize the risk of data loss and ensure business continuity.

Implementing data validation and security measures is an essential aspect of managing a research database. By setting up data validation rules, you can maintain data accuracy and consistency, reducing the chances of errors. Implementing user access controls helps protect the confidentiality and integrity of the database, preventing unauthorized access. Regularly backing up the database ensures that you have a copy of the data in case of any unforeseen events.

Remember, database management is an ongoing process, and continuous improvement is key. Stay updated with the latest security practices and technologies to safeguard your research database effectively. By mastering the art of data validation and security, you can ensure the reliability and trustworthiness of your research database. So, start implementing these measures today and take your research database management to the next level.

Step 5: Querying and Analyzing Data

In the process of creating a research database, Step 5 involves querying and analyzing the data stored within the database. This step is crucial as it allows researchers to extract specific information, gain insights, and make informed decisions based on the data collected. Let’s explore the key aspects of this step in more detail.

Writing SQL queries to retrieve specific information

Structured Query Language (SQL) is a powerful tool that enables researchers to retrieve specific information from the database. SQL queries are used to interact with the database and extract data based on certain criteria. Researchers can write queries to filter, sort, and aggregate data, allowing them to answer specific research questions.

For example, if a researcher wants to analyze the sales data of a particular product, they can write an SQL query to retrieve the relevant information. The query may include conditions such as the product name, date range, and geographical location. By executing the query, the researcher can obtain the desired data for further analysis.

Utilizing data analysis tools and techniques

In addition to SQL queries, researchers can leverage various data analysis tools and techniques to gain deeper insights from the collected data. These tools provide advanced functionalities for statistical analysis, data visualization, and predictive modeling.

Statistical analysis tools such as R or Python’s pandas library allow researchers to perform complex calculations, hypothesis testing, and regression analysis. These tools enable them to uncover patterns, trends, and correlations within the data.

Data visualization tools like Tableau or Power BI help researchers present their findings in a visually appealing and easily understandable manner. By creating charts, graphs, and interactive dashboards, researchers can effectively communicate their insights to stakeholders.

Furthermore, predictive modeling techniques such as machine learning algorithms can be applied to the data to make predictions and forecasts. These techniques enable researchers to identify patterns and make data-driven decisions based on future trends.

Generating reports and visualizations

Once the data has been queried and analyzed, researchers can generate reports and visualizations to summarize their findings. Reports provide a comprehensive overview of the research outcomes, including key insights, statistical analysis results, and recommendations.

Visualizations, such as charts, graphs, and infographics, help researchers present complex data in a simplified and visually appealing format. Visual representations make it easier for stakeholders to understand the research findings and draw meaningful conclusions.

By combining the power of SQL queries, data analysis tools, and visualizations, researchers can unlock the full potential of their research database. This step allows them to extract valuable insights, identify trends, and make data-driven decisions.

In conclusion, Step 5 of creating a research database involves querying and analyzing the data stored within the database. By writing SQL queries, utilizing data analysis tools and techniques, and generating reports and visualizations, researchers can gain valuable insights from the collected data. This step plays a crucial role in the research process, enabling researchers to make informed decisions and contribute to their field of study.

Step 6: Maintaining and Updating the Database

Maintaining and updating a research database is crucial for ensuring its accuracy, reliability, and optimal performance. In this step, we will explore the key tasks involved in maintaining and updating a database.

Regularly reviewing and cleaning the database

Regularly reviewing and cleaning the database is essential to eliminate any inconsistencies, errors, or outdated information. Here are some important tasks to consider:

Data review : Regularly review the data in your database to identify any discrepancies or inaccuracies. This can be done by comparing the data with reliable sources or conducting periodic audits.

Data cleaning : Clean the database by removing duplicate records, correcting errors, and standardizing data formats. This will help improve data quality and ensure consistency.

Data archiving : Archive old or unused data to free up storage space and improve database performance. This can be done by moving the data to a separate archive database or by creating backups for long-term storage.

Updating and adding new data as needed

To keep your research database up to date and relevant, it is important to regularly update and add new data. Here are some steps to consider:

Data collection : Continuously collect new data from reliable sources to ensure that your database remains current. This can involve manual data entry, data extraction from external sources, or automated data feeds.

Data integration : Integrate new data into the existing database structure by adding new records or updating existing ones. Ensure that the new data is properly mapped to the appropriate fields and tables.

Data validation : Validate the new data to ensure its accuracy and consistency. This can involve running data validation checks, verifying data against predefined rules, or using data profiling techniques.

Monitoring performance and optimizing the database

Monitoring the performance of your research database is essential to identify any bottlenecks or issues that may affect its efficiency. Here are some steps to consider:

Performance monitoring : Regularly monitor the database performance by analyzing key metrics such as response time, query execution time, and resource utilization. This can be done using built-in monitoring tools or third-party performance monitoring solutions.

Database optimization : Optimize the database by fine-tuning queries, indexing frequently accessed columns, and optimizing database configurations. This will help improve query performance and overall database efficiency.

Capacity planning : Plan for future growth by monitoring database usage trends and estimating future data storage requirements. This will help ensure that your database can handle increasing data volumes without compromising performance.

In conclusion, maintaining and updating a research database is an ongoing process that requires regular attention and care. By regularly reviewing and cleaning the database, updating and adding new data, and monitoring performance, you can ensure that your research database remains accurate, reliable, and efficient. Remember, continuous improvement and learning are key to mastering the art of database management. So, start creating your research database and embark on a journey of knowledge discovery and insights.

Unveiling The Shelf Life: How Long Does Citric Acid Last?

Unveiling The True Value: How Much Is Jcoin Worth In Today’s Market?

Rebooting Your Booze: How To Reset Alcohol Content

Quick And Easy: Mastering The Art Of Thawing Tuna

Unveiling The Dynamic Interplay: How Physical And Human Systems Shape A Place

Unlocking The Power: How Long Does It Take For Royal Honey To Activate?

Mastering Residency: A Guide On How To Study Effectively

Mastering The Art Of Die Cast Mold Making: A Step-By-Step Guide

Unveiling The Energy Consumption Of Water Coolers: How Much Electricity Do They Really Use?

Mastering Virtual Reality: Unlocking The Secrets To Altering Your Height

Leave a Comment Cancel reply

Save my name, email, and website in this browser for the next time I comment.

• Share full article

Advertisement

Supported by

More Studies by Columbia Cancer Researchers Are Retracted

The studies, pulled because of copied data, illustrate the sluggishness of scientific publishers to address serious errors, experts said.

By Benjamin Mueller

Scientists in a prominent cancer lab at Columbia University have now had four studies retracted and a stern note added to a fifth accusing it of “severe abuse of the scientific publishing system,” the latest fallout from research misconduct allegations recently leveled against several leading cancer scientists.

A scientific sleuth in Britain last year uncovered discrepancies in data published by the Columbia lab, including the reuse of photos and other images across different papers. The New York Times reported last month that a medical journal in 2022 had quietly taken down a stomach cancer study by the researchers after an internal inquiry by the journal found ethics violations.

Despite that study’s removal, the researchers — Dr. Sam Yoon, chief of a cancer surgery division at Columbia University’s medical center, and Changhwan Yoon, a more junior biologist there — continued publishing studies with suspicious data. Since 2008, the two scientists have collaborated with other researchers on 26 articles that the sleuth, Sholto David, publicly flagged for misrepresenting experiments’ results.

One of those articles was retracted last month after The Times asked publishers about the allegations. In recent weeks, medical journals have retracted three additional studies, which described new strategies for treating cancers of the stomach, head and neck. Other labs had cited the articles in roughly 90 papers.

A major scientific publisher also appended a blunt note to the article that it had originally taken down without explanation in 2022. “This reuse (and in part, misrepresentation) of data without appropriate attribution represents a severe abuse of the scientific publishing system,” it said .

Still, those measures addressed only a small fraction of the lab’s suspect papers. Experts said the episode illustrated not only the extent of unreliable research by top labs, but also the tendency of scientific publishers to respond slowly, if at all, to significant problems once they are detected. As a result, other labs keep relying on questionable work as they pour federal research money into studies, allowing errors to accumulate in the scientific record.

“For every one paper that is retracted, there are probably 10 that should be,” said Dr. Ivan Oransky, co-founder of Retraction Watch, which keeps a database of 47,000-plus retracted studies. “Journals are not particularly interested in correcting the record.”

Columbia’s medical center declined to comment on allegations facing Dr. Yoon’s lab. It said the two scientists remained at Columbia and the hospital “is fully committed to upholding the highest standards of ethics and to rigorously maintaining the integrity of our research.”

The lab’s web page was recently taken offline. Columbia declined to say why. Neither Dr. Yoon nor Changhwan Yoon could be reached for comment. (They are not related.)

Memorial Sloan Kettering Cancer Center, where the scientists worked when much of the research was done, is investigating their work.

The Columbia scientists’ retractions come amid growing attention to the suspicious data that undergirds some medical research. Since late February, medical journals have retracted seven papers by scientists at Harvard’s Dana-Farber Cancer Institute . That followed investigations into data problems publicized by Dr. David , an independent molecular biologist who looks for irregularities in published images of cells, tumors and mice, sometimes with help from A.I. software.

The spate of misconduct allegations has drawn attention to the pressures on academic scientists — even those, like Dr. Yoon, who also work as doctors — to produce heaps of research.

Strong images of experiments’ results are often needed for those studies. Publishing them helps scientists win prestigious academic appointments and attract federal research grants that can pay dividends for themselves and their universities.

Dr. Yoon, a robotic surgery specialist noted for his treatment of stomach cancers, has helped bring in nearly $5 million in federal research money over his career.

The latest retractions from his lab included articles from 2020 and 2021 that Dr. David said contained glaring irregularities . Their results appeared to include identical images of tumor-stricken mice, despite those mice supposedly having been subjected to different experiments involving separate treatments and types of cancer cells.

The medical journal Cell Death & Disease retracted two of the latest studies, and Oncogene retracted the third. The journals found that the studies had also reused other images, like identical pictures of constellations of cancer cells.

The studies Dr. David flagged as containing image problems were largely overseen by the more senior Dr. Yoon. Changhwan Yoon, an associate research scientist who has worked alongside Dr. Yoon for a decade, was often a first author, which generally designates the scientist who ran the bulk of the experiments.

Kun Huang, a scientist in China who oversaw one of the recently retracted studies, a 2020 paper that did not include the more senior Dr. Yoon, attributed that study’s problematic sections to Changhwan Yoon. Dr. Huang, who made those comments this month on PubPeer, a website where scientists post about studies, did not respond to an email seeking comment.

But the more senior Dr. Yoon has long been made aware of problems in research he published alongside Changhwan Yoon: The two scientists were notified of the removal in January 2022 of their stomach cancer study that was found to have violated ethics guidelines.

Research misconduct is often pinned on the more junior researchers who conduct experiments. Other scientists, though, assign greater responsibility to the senior researchers who run labs and oversee studies, even as they juggle jobs as doctors or administrators.

“The research world’s coming to realize that with great power comes great responsibility and, in fact, you are responsible not just for what one of your direct reports in the lab has done, but for the environment you create,” Dr. Oransky said.

In their latest public retraction notices, medical journals said that they had lost faith in the results and conclusions. Imaging experts said some irregularities identified by Dr. David bore signs of deliberate manipulation, like flipped or rotated images, while others could have been sloppy copy-and-paste errors.

The little-noticed removal by a journal of the stomach cancer study in January 2022 highlighted some scientific publishers’ policy of not disclosing the reasons for withdrawing papers as long as they have not yet formally appeared in print. That study had appeared only online.

Roland Herzog, the editor of the journal Molecular Therapy, said that editors had drafted an explanation that they intended to publish at the time of the article’s removal. But Elsevier, the journal’s parent publisher, advised them that such a note was unnecessary, he said.

Only after the Times article last month did Elsevier agree to explain the article’s removal publicly with the stern note. In an editorial this week , the Molecular Therapy editors said that in the future, they would explain the removal of any articles that had been published only online.

But Elsevier said in a statement that it did not consider online articles “to be the final published articles of record.” As a result, company policy continues to advise that such articles be removed without an explanation when they are found to contain problems. The company said it allowed editors to provide additional information where needed.

Elsevier, which publishes nearly 3,000 journals and generates billions of dollars in annual revenue , has long been criticized for its opaque removals of online articles.

Articles by the Columbia scientists with data discrepancies that remain unaddressed were largely distributed by three major publishers: Elsevier, Springer Nature and the American Association for Cancer Research. Dr. David alerted many journals to the data discrepancies in October.

Each publisher said it was investigating the concerns. Springer Nature said investigations take time because they can involve consulting experts, waiting for author responses and analyzing raw data.

Dr. David has also raised concerns about studies published independently by scientists who collaborated with the Columbia researchers on some of their recently retracted papers. For example, Sandra Ryeom, an associate professor of surgical sciences at Columbia, published an article in 2003 while at Harvard that Dr. David said contained a duplicated image . As of 2021, she was married to the more senior Dr. Yoon, according to a mortgage document from that year.

A medical journal appended a formal notice to the article last week saying “appropriate editorial action will be taken” once data concerns had been resolved. Dr. Ryeom said in a statement that she was working with the paper’s senior author on “correcting the error.”

Columbia has sought to reinforce the importance of sound research practices. Hours after the Times article appeared last month, Dr. Michael Shelanski, the medical school’s senior vice dean for research, sent an email to faculty members titled “Research Fraud Accusations — How to Protect Yourself.” It warned that such allegations, whatever their merits, could take a toll on the university.

“In the months that it can take to investigate an allegation,” Dr. Shelanski wrote, “funding can be suspended, and donors can feel that their trust has been betrayed.”

Benjamin Mueller reports on health and medicine. He was previously a U.K. correspondent in London and a police reporter in New York. More about Benjamin Mueller

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

Creating a Corporate Social Responsibility Program with Real Impact

• Emilio Marti,
• David Risi,
• Eva Schlindwein,
• Andromachi Athanasopoulou

Lessons from multinational companies that adapted their CSR practices based on local feedback and knowledge.

Exploring the critical role of experimentation in Corporate Social Responsibility (CSR), research on four multinational companies reveals a stark difference in CSR effectiveness. Successful companies integrate an experimental approach, constantly adapting their CSR practices based on local feedback and knowledge. This strategy fosters genuine community engagement and responsive initiatives, as seen in a mining company’s impactful HIV/AIDS program. Conversely, companies that rely on standardized, inflexible CSR methods often fail to achieve their goals, demonstrated by a failed partnership due to local corruption in another mining company. The study recommends encouraging broad employee participation in CSR and fostering a culture that values CSR’s long-term business benefits. It also suggests that sustainable investors and ESG rating agencies should focus on assessing companies’ experimental approaches to CSR, going beyond current practices to examine the involvement of diverse employees in both developing and adapting CSR initiatives. Overall, embracing a dynamic, data-driven approach to CSR is essential for meaningful social and environmental impact.

By now, almost all large companies are engaged in corporate social responsibility (CSR): they have CSR policies, employ CSR staff, engage in activities that aim to have a positive impact on the environment and society, and write CSR reports. However, the evolution of CSR has brought forth new challenges. A stark contrast to two decades ago, when the primary concern was the sheer neglect of CSR, the current issue lies in the ineffective execution of these practices. Why do some companies implement CSR in ways that create a positive impact on the environment and society, while others fail to do so? Our research reveals that experimentation is critical for impactful CSR, which has implications for both companies that implement CSR and companies that externally monitor these CSR activities, such as sustainable investors and ESG rating agencies.

• EM Emilio Marti is an assistant professor at the Rotterdam School of Management (RSM) at Erasmus University Rotterdam.
• DR David Risi is a professor at the Bern University of Applied Sciences and a habilitated lecturer at the University of St. Gallen. His research focuses on how companies organize CSR and sustainability.
• ES Eva Schlindwein is a professor at the Bern University of Applied Sciences and a postdoctoral fellow at the University of Oxford. Her research focuses on how organizations navigate tensions between business and society.
• AA Andromachi Athanasopoulou is an associate professor at Queen Mary University of London and an associate fellow at the University of Oxford. Her research focuses on how individuals manage their leadership careers and make ethically charged decisions.

Partner Center

Vanderbilt to establish a college dedicated to computing, AI and data science

Media inquiries.

• 615-322-6397 Email

Latest Stories

• Roberts Academy and Dyslexia Center hires Jared Clodfelter as director
• McLean awarded Herty Medal for chemistry achievements, distinguished service
• Vanderbilt students visit Capitol Hill to champion the real-world impact of humanities 

Mar 25, 2024, 11:20 AM

Vanderbilt has begun work to establish a transformative college dedicated to computer science, AI, data science and related fields, university leaders announced today. In addition to meeting the growing demand for degrees in technological fields and advancing research in rapidly evolving, computing-related disciplines, the new, interdisciplinary college will collaborate with all of Vanderbilt’s schools and colleges to advance breakthrough discoveries and strengthen computing education through a “computing for all” approach.

The College of Connected Computing will be led by a new dean, who will report to Provost and Vice Chancellor for Academic Affairs C. Cybele Raver and to School of Engineering Dean Krishnendu “Krish” Roy. The search for the college’s dean is scheduled to begin in late August, and recruiting of faculty will begin in the coming months. It will be the first new college at Vanderbilt since the university and the Blair School of Music merged in 1981.

“Of all the factors shaping society, few are more influential than the rapid emergence of advanced computing, AI and data science,” Chancellor Daniel Diermeier said. “To continue to carry out our mission, prepare all our students for their careers and advance research across the university, Vanderbilt must contribute even more to the study, understanding and innovative application of these fast-changing disciplines. Our aim is to make Vanderbilt a global leader in these fields, ensuring our continued academic excellence and capacity for world-changing innovation.”

“Our new college will enable us to build upon our strong programs and catapult Vanderbilt to the forefront of breakthrough discovery and innovation—in key areas of computer science and also in a wide range of other disciplines that capitalize on advanced computational methods. In launching this new college, we will provide students with highest-caliber educational opportunities at the intersection of these pathbreaking fields,” Raver said. “The creation of this college represents a tremendous win and will be transformative for our entire university community.”

Raver noted the ways that Vanderbilt is forging a bold and distinct strategic path to address burgeoning research and educational opportunities, including increasing demand for expertise in computing-related fields. Moreover, she said, the global interest in AI “aligns perfectly” with Vanderbilt’s leading work in that field. She said a dedicated college will enable Vanderbilt to keep making groundbreaking discoveries at the intersections of computing and other disciplines and will more effectively leverage advanced computing to address some of society’s most pressing challenges.

“The establishment of this interdisciplinary, ‘cross-cutting’ college is a watershed moment—not only for the School of Engineering, but also for the entire university,” Roy said. “The future of education, research and thinking in all disciplines is now inherently tied to, and will be greatly influenced by, the knowledge and power of computing. The idea of ‘computing for all’ is fundamental to the future of learning.”  

Many of the specific details about the college—including its departments, degree programs and research infrastructure—will be informed by the recommendations of a task force on connected computing composed of faculty from across the university. In addition, Vice Provost for Research and Innovation Padma Raghavan will launch a Computing Catalyst working group that will engage faculty and staff leaders in computing from across campus and solicit their input on strategically expanding the university’s computing resources. “The decision to establish this new college is rooted in conversations with faculty,” Raver said. “We are continuing that faculty engagement with this working group, and we’re fortunate to have the advice of some of the best minds in these fields as we embark on this exciting journey.”   

The members of the Connected Computing Task Force include:

Krishnendu Roy , Chair   Bruce and Bridgitt Evans Dean of Engineering  University Distinguished Professor of Biomedical Engineering; Pathology, Microbiology and Immunology; and Chemical and Biomolecular Engineering        

Douglas Adams   Vice Dean of the School of Engineering   Daniel F. Flowers Chair Distinguished Professor of Civil and Environmental Engineering  Professor of Mechanical Engineering  Faculty Affiliate, VINSE        

Hiba Baroud   Associate Chair and Associate Professor of Civil and Environmental Engineering James and Alice B. Clark Foundation Faculty Fellow Associate Professor of Computer Science  Faculty Affiliate, VECTOR , Data Science Institute         

Gautam Biswas   Cornelius Vanderbilt Professor of Computer Science and Computer Engineering Professor of Engineering Management  Senior Research Scientist, ISIS   Faculty Affiliate, Data Science Institute        

Erin Calipari   Associate Professor of Pharmacology  Associate Professor of  Molecular Physiology & Biophysics Associate Professor of  Psychiatry & Behavioral Sciences Director, Vanderbilt Center for Addiction Research  Faculty Affiliate, Vanderbilt Brain Institute        

Laurie Cutting   Patricia and Rodes Hart Professor and Professor of Special Education  Professor of Psychology Professor of Pediatrics Professor of Electrical and Computer Engineering Professor of Radiology & Radiological Sciences Associate Provost in the Office of the Vice Provost of Research and Innovation Associate Director of the Vanderbilt Kennedy Center  Faculty Affiliate, Vanderbilt Brain Institute        

Benoit Dawant   Cornelius Vanderbilt Professor of Electrical Engineering Incoming Chair of the Department of Electrical and Computer Engineering  Director and Steering Committee Chair, Vanderbilt Institute for Surgery & Engineering  Professor of Biomedical Engineering Professor of Computer Science      

Abhishek Dubey   Associate Professor of Computer Science  Associate Professor of Electrical and Computer Engineering  Director, SCOPE lab at ISIS   Faculty Affiliate, Institute for Software Integrated Systems and Data Science Institute         

Bennett Landman   Stevenson Professor of Electrical and Computer Engineering and Chair of the Department of Electrical and Computer Engineering  Professor of Biomedical Engineering Professor of Computer Science Professor of Neurology Associate Professor of Biomedical Informatics Associate Professor of Psychiatry and Behavioral Sciences Associate Professor of Radiology and Radiological Sciences Faculty Affiliate, Vanderbilt Institute for Surgery and Engineering (VISE) , Vanderbilt Brain Institute , Vanderbilt Kennedy Center , Vanderbilt University Institute of Image Science (VUIIS) , Data Science Institute         

Michael Matheny   Professor of Biomedical Informatics  Professor of Biostatistics Professor of Medicine Director, Center for Improving the Public’s Health Through Informatics        

Sandeep Neema   Professor of Computer Science  Professor of Electrical and Computer Engineering  Chair of the Executive Council, Institute for Software Integrated Systems         

Ipek Oguz   Assistant Professor of Computer Science  Assistant Professor of Biomedical Engineering Assistant Professor of Electrical & Computer Engineering  Faculty Affiliate, Vanderbilt Institute for Surgery and Engineering (VISE)         

J.B. Ruhl   David Daniels Allen Distinguished Chair of Law  Director, Program in Law and Innovation   Co-Director, Energy, Environment and Land Use Program   Faculty Affiliate, Data Science Institute         

Jesse Spencer-Smith     Professor of the Practice of Computer Science  Adjunct Professor of Psychology Interim Director and Chief Data Scientist, Data Science Institute         

Jonathan Sprinkle   Professor of Computer Science  Professor of Electrical & Computer Engineering  Professor of Civil & Environmental Engineering  Faculty Affiliate, Institute for Software Integrated Systems         

Yuankai “Kenny” Tao   Associate Professor of Biomedical Engineering  Associate Professor of Ophthalmology & Visual Sciences  SPIE Faculty Fellow in Engineering Faculty Affiliate, Vanderbilt Institute for Surgery & Engineering        

Holly Tucker   Mellon Foundation Chair in the Humanities Professor of French  Director, Robert Penn Warren Center for the Humanities         

Kalman Varga   Vice Chair of the Department of Physics & Astronomy Professor of Physics  Director, Minor in Scientific Computing  Faculty Affiliate, VINSE        

Steven Wernke   Chair of the Department of Anthropology Associate Professor of Anthropology  Director, Vanderbilt Initiative for Interdisciplinary Geospatial Research   Faculty Affiliate, Data Science Institute    

Jules White Professor of Computer Science  Associate Professor of Biomedical Informatics  Senior Advisor to the Chancellor for Generative AI in Education and Enterprise Solutions  Faculty Affiliate, Institute for Software Integrated Systems , Data Science Institute         

Dan Work   Director of Graduate Studies in Civil Engineering Professor of Civil & Environmental Engineering  Professor of Computer Science  Faculty Affiliate, VECTOR , Institute for Software Integrated Systems , Data Science Institute           

Tracey George   ex officio   Vice Provost for Faculty Affairs and Professional Education  Charles B. Cox III and Lucy D. Cox Family Chair in Law and Liberty  Professor of Law       

Tiffiny Tung   Ex officio   Vice Provost for Undergraduate Education  Gertrude Conaway Vanderbilt Chair in the Social and Natural Sciences Professor of Anthropology   

  Members of the Vanderbilt community can learn more about this initiative and share feedback with the faculty working group by visiting vanderbilt.edu/about/computingtaskforce .  

Keep Reading

Vanderbilt hosts SmartComp 2023, prestigious IEEE international conference on smart computing

‘U.S. News’ graduate school rankings: Here is how Vanderbilt graduate and professional programs placed

Vanderbilt announces search for new ACCRE executive director

Explore story topics.

• myVU Latest Headlines
• C. Cybele Raver
• College of Connected Computing
• Connected Computing Task Force
• Daniel Diermeier
• feature myvu
• featured myvu
• Office of the Chancellor
• Office of the Provost
• School of Engineering
• vuhome-highlight

• U.S. Department of Health & Human Services HHS
• National Institutes of Health NIH
• Division of Program Coordination, Planning, and Strategic Initiatives DPCPSI

NIH Consortium for Advancing Research on Botanical and Other Natural Products (CARBON) Program: 2025-2029 Funding Opportunities

Botanical dietary supplements translational research teams.

A Notice of Funding Opportunity (NOFO) for a component of the 2025-2029  NIH CARBON Program to support trans-disciplinary, translational research on chemically complex botanical products or natural products traditionally used as dietary components, with a single receipt date of July 8, 2024.

• Technical Assistance Webinar for RFA-OD-24-014 - "Botanical Dietary Supplements Translational Research Teams on May 7, 2024.

Leveraging Data at Scale to Understand Natural Product Impacts on Whole Person Health

A Notice of Funding Opportunity (NOFO) for a component of the 2025-2029  NIH CARBON Program to support development of computational tools to analyze data sets related to natural products in relation to biological activity and role in the context of whole person health research, with a single receipt date of June 28, 2024.

Limited Competition: Research Resource for Natural Product Nuclear Magnetic Resonance Data

A limited competition Notice of Funding Opportunity (NOFO) for a component of the 2025-2029  NIH CARBON Program to promote the sustainability, scaling and wider community inclusiveness of the established NMR research resource, with a single receipt date of July 8, 2024.

Read our research on: Abortion | Podcasts | Election 2024

Regions & Countries

Key facts about asian americans living in poverty.

Asian Americans are often portrayed as educationally and financially successful when compared with other racial or ethnic groups. However, Asian origin groups in the United States vary widely in their economic status and education level . Indeed, more than 2.3 million Asian Americans – about one-in-ten – lived in poverty in 2022, according to a Pew Research Center analysis of U.S. Census Bureau data.

Learn more about Asian Americans’ experiences with economic hardship in  our data essay  and  short film .

Here are nine facts about Asian Americans living in poverty.

Pew Research Center conducted this analysis to better understand the characteristics, experiences and views of Asian Americans living in poverty today. It is part of a three-part study that includes an analysis of 18 focus groups conducted with 144 Asians living with economic hardship completed in February 2023 and a short film about Asian families who have experienced economic hardship .

This analysis is based on two main data sources. The first data source is the U.S. Census Bureau’s 2022 American Community Survey (ACS) provided through Integrated Public Use Microdata Series (IPUMS) from the University of Minnesota. In this analysis, poverty status is determined using the 2022 federal poverty line for the 48 contiguous states and the District of Columbia, Alaska, or Hawaii, depending on respondents’ state of residence, published by the U.S. Department of Health and Human Services. For example, a family of four living in 48 contiguous states and the District of Columbia were categorized as living “in poverty” if they make a yearly income of $27,750 or less.

The second data source is Pew Research Center’s 2022-23 survey of Asian American adults, conducted from July 2022 to January 2023 in six languages among 7,006 respondents. The survey analysis included 561 Asian adults whose approximate family income is at or below the 2022 federal poverty line for the 48 contiguous states and the District of Columbia, regardless of their state of residence. For more details, refer to the survey methodology . For questions used in this analysis, refer to the topline questionnaire .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. The Center’s Asian American portfolio was funded by The Pew Charitable Trusts, with generous support from The Asian American Foundation; Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation; the Robert Wood Johnson Foundation; the Henry Luce Foundation; the Doris Duke Foundation; The Wallace H. Coulter Foundation; The Dirk and Charlene Kabcenell Foundation; The Long Family Foundation; Lu-Hebert Fund; Gee Family Foundation; Joseph Cotchett; the Julian Abdey and Sabrina Moyle Charitable Fund; and Nanci Nishimura.

We would also like to thank the Leaders Forum for its thoughtful leadership and valuable assistance in helping make this survey possible.

The strategic communications campaign used to promote the research was made possible with generous support from the Doris Duke Foundation.

The terms Asians and Asian Americans  are used interchangeably throughout this post to refer to individuals who self-identify as Asian, either alone or in combination with other races or Hispanic identity.

The terms living in poverty and living near or below the federal poverty line are used interchangeably throughout this post to refer to those whose family income is close to or below the 2022 federal poverty line.

• For results on Asian adults from the survey , this refers to adults whose approximate family income falls at or below 100% of the federal poverty line.
• For data on the total U.S. Asian population from the U.S. Census Bureau , this refers to all Asian Americans whose family income is at or below 100% of the federal poverty line.

The term U.S. born refers to people who are U.S. citizens at birth, including people born in the 50 U.S. states, the District of Columbia, Puerto Rico, or other U.S. territories, as well as those born elsewhere to at least one parent who is a U.S. citizen.

The term immigrants , when referring to Census Bureau data, includes those who were not U.S. citizens at birth – in other words, those born outside the 50 U.S. states or the District of Columbia, Puerto Rico, or other U.S. territories to parents who were not U.S. citizens. When referring to survey respondents, this group only includes those born outside the 50 U.S. States or the District of Columbia, Puerto Rico or other U.S. territories.

About 10% of Asian Americans overall live in poverty, but poverty rates vary widely across origin groups. Burmese (19%) and Hmong Americans (17%) were among the Asian origin groups with the highest poverty rates in 2022. Meanwhile, Filipino (7%) and Indian Americans (6%) were among the groups with the lowest poverty rates.

A third of Asian Americans ages 25 and older who live in poverty have a bachelor’s degree. By comparison, among non-Asians 25 and older who live in poverty, only 14% have a bachelor’s degree.

Asian Americans 25 and older with at least a bachelor’s degree are still less likely to live in poverty (5%) than those with less formal education (13%).

Nearly six-in-ten Asian Americans who live in poverty are immigrants. And relatively few of these immigrants speak English proficiently.

Among Asian immigrants ages 5 and older living below the poverty line, 44% are proficient in English (meaning they either speak only English or speak the language very well). By comparison, 61% of those immigrants above the poverty line speak English proficiently.

About 1 million Asians who are below the poverty line live in 10 U.S. metropolitan areas. In fact, more than 500,000 live in just three metropolitan areas: New York City, Los Angeles and San Francisco. These metro areas each have about 100,000 or more Asians living in poverty, and together they hold 26% of all Asian Americans living in poverty.

Fresno, California (19%), Buffalo, New York (18%) and Pittsburgh, Pennsylvania (15%) are among the metro areas with the highest poverty rates among Asian Americans. Still, Asian Americans who live in poverty largely reside in places with larger Asian populations than these metro areas.

Refer to a downloadable spreadsheet for detailed data on the number and share of Asians living in poverty by metro area.

Around eight-in-ten Asian adults who live in poverty (79%) have experienced financial challenges in some way in the past 12 months, according to a Pew Research Center survey of Asian adults conducted in 2022 and 2023. By contrast, 48% of Asian adults living above the poverty line say they have experienced the same. Among the specific financial challenges they faced:

• 57% of Asian adults living in poverty were unable to save for emergencies, compared with 40% of Asian adults living above the poverty line.
• 42% had trouble paying their bills, more than twice the share of Asian adults living above the poverty line who said the same (17%).
• 38% have gotten food from a food bank or charitable organization, about six times the share among Asians living above the poverty line (6%).

Financial difficulties tend to come in bundles: Among those living in poverty who say they experienced at least one of the financial challenges asked about, 65% experienced two or more.

A majority of Asian adults who live in poverty (61%) have turned to family or friends for help with bills, housing, food or employment.

A large share (49%) also say they have sought help from local, state or federal governments. Smaller shares have sought help from religious institutions such as churches or temples (21%) or Asian community groups (13%).

However, 19% of Asian adults living in poverty say they have not sought help from any of the sources asked about in the survey.

Why Asian immigrants came to the U.S. is linked to whether they have received help from the government. For example, a third of all Asian immigrants, regardless of poverty status, who came to the U.S. due to conflict or persecution in their home country have received help with bills, housing, food or employment from governments (33%). By comparison, smaller shares of Asian immigrants who came for educational opportunities (14%) or economic opportunities (16%) or who migrated to be with family (25%) say the same.

Roughly half of Asian Americans who live in poverty (47%) say the American dream is out of reach, but others say they have achieved it (15%) or are on their way to achieving it (36%). By comparison, Asians living above the poverty line are more optimistic about their chances of achieving the American dream: 26% say it is out of reach for them, while 27% say they have achieved it and 46% say they are on their way to achieving it.

Asian adults who live below the poverty line and those who live above it have similar views on what’s important to achieving the American dream. For Asians living in poverty, the vast majority say having freedom of choice in how to live one’s life (91%), a good family life (91%), children having the best opportunities (91%) and retiring comfortably (90%) are important to their view of the American dream. Among Asian adults living above the poverty line, similar shares say these elements are important.

Homeownership is also seen as key: 81% of Asian adults living in poverty and 87% of those living above the poverty line say owning a home is important to their view of the American dream. However, Asian adults in poverty are much less likely than those above the poverty line to be homeowners (40% vs. 71%), according to Census Bureau data.

Note: For more details, refer to the survey methodology . For questions used in this analysis, refer to the topline questionnaire .

Sign up for our weekly newsletter

Fresh data delivered Saturday mornings

Bangladeshis in the U.S. Fact Sheet

Key facts about asian americans, a diverse and growing population, key facts about asian origin groups in the u.s., asian americans are the fastest-growing racial or ethnic group in the u.s., demographic and economic data on the thai immigrant and u.s.-born populations in the united states., most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

• Side Hustles
• Power Players
• Young Success
• Save and Invest
• Become Debt-Free
• Land the Job
• Closing the Gap
• Science of Success
• Pop Culture and Media
• Psychology and Relationships
• Health and Wellness
• Real Estate
• Most Popular

Related Stories

• Earn The best- and worst-paying college   majors, 5 years after graduation
• Work The racial pay gap starts as early as   16 for Black workers—here's why
• Closing The Gap The No. 1 thing companies can do   to keep female employees
• Life These are the 10 happiest cities in   America—none of them are in Florida
• Work You'll have almost zero competition to land   a 'highly paid' job in these cities

These are the 10 top-paying U.S. cities where women outearn men

Nationwide, women outearn men in just 42 U.S. cities out of an analysis of some 1,800 cities, according to a new GoBankingRates report using Census Bureau data.

The report considers the median annual earnings for men and women in cities with a population of at least 20,000 people.

Of locations, these are the 10 top-paying cities where women outearn men:

• Bowie, Md.: Women earn a median $81,011 a year
• Clinton, Md.: Women earn a median $71,123 a year
• Fort Washington, Md.: Women earn a median $69,983 a year
• Oakland, Calif.: Women earn a median $68,260 a year
• Goleta, Calif.: Women earn a median $65,030 a year
• Laurel, Md.: Women earn a median $65,008 a year
• Monrovia, Calif.: Women earn a median $62,016 a year
• Hackensack, N.J.: Women earn a median $60,237 a year
• Newark, Del.: Women earn a median $58,769 a year
• Chamblee, Ga.: Women earn a median $58,590 a year

In each of these cities, women outearn men by a share of .14% to 18.95% of what men earn.

Across the U.S., women are paid just 84 cents for every $1 paid to a man, on average.

Many of the top cities with gender parity and higher earning power for women are near Washington D.C., where government jobs have more transparent pay practices and, perhaps relatedly, greater gender pay parity, though a gap still exists .

At No. 4, Oakland, Calif., is the largest city on the list, with a population of nearly 360,000 people. There, women earn a median of $68,200 per year, just outpacing men's earnings of $68,100 per year.

The lack of a gender pay gap in these cities isn't, on its own, good news for women's earning power.

"Our findings show salaries are relatively low in the select few cities where women are outearning men," Andrew Murray, lead data researcher at GoBankingRates, tells CNBC Make It. "Several of the cities that made our list have median earnings for women around $30,000 to $40,000."

"This is particularly noteworthy considering that there tends to be less of a gender pay gap among lower-wage workers, especially minimum-wage workers, compared to higher-end, hourly workers," Murray adds.

Women, and particularly women of color, are overrepresented in minimum wage jobs . Research shows raising the federal minimum wage would have an outsized impact on reducing poverty rates for women and the children of women-led households.

Overall, the No. 1 city where women's earning rates are highest compared to men's is Jacksonville, N.C, but actual salary figures are much lower. There, women earn roughly 20% more than men, or $33,000 a year compared with men who earn roughly $27,000 a year — lower than the national median salary of $59,540 per year .

In the case of Jacksonville, the city "has a high government employee base both for the military and Department of Defense which could be contributing to more equitable pay," Murray says.

Overall, women earn the most in five U.S. cities, GoBankingRates notes: Los Altos, Calif. ($150,000 median salary); Saratoga, Calif. ($140,000 median salary); McLean, Va. ($137,000 median salary); San Carlos, Calif. ($137,000 median salary) and Wellesley, Mass. ($130,000). However, men outearn women in each of these cities by a rate of 60% to 70%.

Want to land your dream job in 2024?  Take  CNBC's new online course How to Ace Your Job Interview  to learn what hiring managers are really looking for, body language techniques, what to say and not to say, and the best way to talk about pay.