Skip to Main Content

Research Data Management

This guide introduce the essentials of good research data management and how the library can support researchers in managing their research data.

Sharing Your Data and Copyright Fair Use

What are FAIR Principles?

  • Set of guiding principles to help research and the data-sharing community ensure research data is shared in ways that enhance reproducibility and transparency. They go beyond just sharing data and ensure it has value once it is shared. The four principles are that data should be Findable, Accessible, Interoperable, and Reusable.

Why Share Your Data?

  • Allows researchers to build upon the work of others if it is already existing
  • Increases visibility and opportunities for future collaborations
  • Increases data circulation and use, encouraging transparency and reproducibility of results to the public
  • If you need help with data-related services, please get in touch with Leslie Golamb ( or your liaison

Is it Fair Use or Not-Copyright Services

  • Open Access and Public Domain: If the materials are in the public domain or use a Creative Commons license, you can use them as course materials. Could you always provide a link to Creative Commons material to comply with attribution requirements?
  • Using Library Materials in Courses: Always put course content in Canvas, not on public websites. More information is here.


NIH Grant/Data Management Service

What is Research Data Management?

  • Research Data Management, also known as RDM, is the management of data used or generated during the research process to ensure that the data is usable by future researchers for future researchers for further research, analysis, and the validation of completed research.

NIH Policy

  • In 2023, the NIH Data Management and Sharing Policy was created and required that all NIH-funded research describe in detail how scientific data will be shared and managed in a usable format. Data must also be preserved within a specialized repository whenever ethically and legally possible. The data management and sharing plan is a 2-page document that proactively plans for how you will manage your data throughout the research process and how you will share your data upon completion of the project.

Best Practices for Research Data Management

  • Increase research reproducibility
  • Increase public trust in research
  • Allows for the replication and validation of research
  • Enables other researchers to reuse data and avoid research waste
  • Helps researchers find, use, and interpret their own data during the research process

Library Services

  • The library provides various data services to help you manage your research data. Please get in touch with Leslie Golamb or your liaison librarian for help or questions. Our data services include:
    • Consulting on how to write a data management and sharing plan
    • Review your data management and sharing plan
    • Recommend the best repository to share your data in
    • Finding data to support a research topic
    • Recommend tools and resources for research data management
    • Answering copyright and licensing information
    • Consolations and customized instruction on research data management and data sharing best practices


Data Visualization

What is Data Visualization?

  • Data visualization is data representation using common graphics, such as charts, plots, infographics, and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

Best Practices for Data Visualization

  • Your choice of chart type, colors, or style will significantly affect how others perceive your data. Fortunately, there are simple guidelines that, if you follow, can make your data visualization both visually appealing, compelling, and captivating.
    • Simple is always better
    • Choose the right type of chart
    • Visualize one aspect per chart
    • Make your axis ranges and labels interesting 
    • Be careful with your color scheme

Data Visualization Resources

Data & Statistic Self-Learning Tutorials

Data & Health Statistics

  • Data are the raw numbers and counts of individual events or services collected locally, nationally, etc. Levels
    • As a research, some best practices:
      • Build strong file naming and cataloging conventions
      • Carefully consider metadata for data sets
      • Data storage
      • Document
  • Statistics: Data analyzed and summarized; most website data are compiled, and statistics are percentages, graphs, tables, maps, etc.
    • Best practices:
      • Should answer your scientific questions
      • Make sure you have quality data to represent your question
      • Keep it simple
      • Make your analysis reproducible

Sage Research Methods

  • Sage Research Methods: this database supports research at all levels by providing materials to guide researchers through every step of the research process. This database has an unlimited methods library with over 1000 books, reference works, journal articles, and instructional videos.
  • Sage Research Methods Datasets: this database provides a collection of teaching datasets and instructional guides that allow students to learn data analysis by practicing themselves.
  • Sage Research Methods Videos: this database provides a collection of videos, including tutorials, case study videos, expert interviews, and more, covering the entire research method. These videos can help bring methods to life.
  • Sage Research Methods Cases: this database provides stories of how real research projects were conducted. This collection provides case studies showing the challenges and success of doing research.