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Data Management: Introduction

This guide serves as a starting point for UNR faculty, students, and staff interested in research data management.

Research Data Management Help at the Libraries

Data is ubiquitous in research and we are here to help you. Our Research Data Services Team is a group of multi-disciplinary librarians available to offer consultations & trainings for students, faculty and researchers throughout the course of their research projects, from planning to sharing data with the public. To learn more about the specific services we offer, visit our research data services site

The following guide will walk you through the major components of research data management, including creating a data management plan and collecting, storing, and sharing your data, and share useful tips and resources. 

If you have questions about research data storage and/or high performance computing, please visit the University's Cyberinfrastructure site.

Why Manage Data?

Good research data management can help you:

  • Comply with funder or publisher mandates 
  • Keep your data and research materials organized (saving you time and effort)
  • Guard against data loss
  • Keep private or sensitive information (e.g., protected health information) safe and secure
  • Further research in your field (others will be better able to use, replicate, or extend your findings)
  • Make the products of your research more discoverable and, therefore, cite-able 

Don't just take our word for it! Check out the video Why Do Data Management? from the University of Wisconsin-Milwaukee Libraries' Data Services. It outlines 5 reasons for embracing good research data management practices. Or, for a more humorous take with pandas, view the New York University Health Sciences Library's video Data Sharing and Management Snafu in 3 Short Acts.

Adapted from the New England Collaborative Data Management Curriculum (NECDMC) "Module 1: Overview of Research Data Management."

What is Research Data?

Different definitions of research data abound - there is no consensus. According to the University of Edinburgh, "[r]esearch data, unlike other types of information, is collected, observed, or created, for purposes of analysis to produce original research results." The Reference Model for an Open Archival Information System (OAIS) defines data is "[a] reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing."

So what "counts" as research data? Data types and formats can vary widely by field. Here are some examples:

  • Survey responses
  • Numerical data (in spreadsheets)
  • Code
  • Biological specimens 
  • GIS data
  • Images
  • Video recordings
  • Measurements derived from lab equipment  
  • Qualitative data (interview transcripts, free-response survey answers)

Elena Azadbakht

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Elena Azadbakht
she/her
Contact:
eazadbakht@unr.edu
(775) 682-5654
MIKC 214C
Website

Scholarly Communications & Social Sciences Librarian

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Teresa Schultz
she/her/hers
Contact:
Room 214H
Mathewson-IGT Knowledge Center
University of Nevada, Reno
775.682.5638