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Scholarly Communication @ NCATSU

This guide provides an overview of scholarly communication and services provided by F.D. Bluford Library to support the creation, evaluation, dissemination, and preservation of the University's scholarly output.

What is Research Data Management?

Research Data Management is a fundamental part of the research process. RDM is the term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. In this guide, you'll find an overview of the different types and formats of data created and collected during a scholarly research project, information about and guidance for creating data management plans and complying with the requirements of funding agencies, information about metadata, and help with sharing and archiving data securely for long-term use.

What is Research Data?

Materials constituting research data vary by discipline. The following are common examples:

  • Audiotapes, videotapes
  • Collection of digital objects acquired and generated during the process of research
  • Contents of an application such as input, output, log files for analysis software, simulation software, schemas
  • Data files
  • Database contents including video, audio, text, images
  • Models, algorithms, scripts
  • Laboratory notebooks, field notebooks, diaries
  • Methodologies and workflows
  • Photographs, films
  • Questionnaires, transcripts, codebooks
  • Slides, artifacts, specimens, samples
  • Standard operating procedures and protocols
  • Test responses
  • Text or Word documents, spreadsheets

Why Manage Data?

Creating a plan to manage and store your data throughout its lifecycle is a critical component of the research process. Not only does having a data management plan save you time and resources, but is a requirement for grant applications for many major funding agencies such as the National Science Foundation (NSF), the National Institutes of Health (NIH), and the National Endowment for the Humanities (NEH). In addition, having a plan to manage your data promotes increased data sharing, transparency, and reproducibility.

Research Data Management Lifecycle

The Research Data Management Lifecycle