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Scholarly Communication Toolkit: Research Data Management

What is Research Data?



Data, from its root is “something given”.1 This makes the following definition both etymologically accurate and practical for the broader purposes of considering the intersection between research data management and libraries:

“Research data means data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media.”2

Flickr jannekestaaks Research Data Management

Research data are those ‘things given’ upon which scholarly arguments are built; they are the foundation of scholarship and research. As the definition indicates, research data may exist in a variety of forms, formats, or states, although the majority of this page will confine itself to the consideration of digital research data. Given this broad definition, it is unsurprising that different research disciplines will develop their own definitions of what is useful research data for that community. This perspective is reflected in the Office of Management & Budget’s definition of research data (§ 200.315 Intangible property. p#286 part e (3))

Research data also includes information about the context in which it was produced. Without this information, research data may be obfuscated, inaccessible, and lack interoperability.

1 Accessed 2014-09-13
2 Queensland University of Technology Management of Research Data Policy, D/2.8.3 Accessed 2014-09-13

Why Libraries and Research Data?

Historically, libraries have served as institutions where information is collected, curated, preserved, described, discovered, and accessed. Putting these traditional library activities into data terms illustrates why academic libraries and librarians should be involved in the management of scholarly information and research data. As libraries we recognize research data as a scholarly asset that should be stored and made available for reuse, just as any publication is. This is particularly important as data has become more widely accessible in its digital form and its use for experimental validation and reuse in extending the boundaries of knowledge has become more practical.

As the majority of research data falls into the “long-tail” that encompasses the many disciplines that do not have dedicated repositories1, the role of academic libraries in making sure that these data are findable, accessible, interoperable & reusable becomes more prominent. There are a few reasons why this is a really excellent thing:

  • Libraries & universities are long-lived institutions that do not traditionally rely on short term funding cycles, unlike many disciplinary repositories
  • Libraries have demonstrated a sustainable model for collection of, preservation of, and access to information
  • Libraries are filled with people who are trained in and participate in already developed and well-characterized practices and principles of information management, from description to organization to access to rights management, and on, and on
  • Libraries are often already established partners in research, having provided guidance & resources at other stages of the research lifecycle
  • Libraries provide instruction in and distribute information about other areas of information management. By adding data to this instructional portfolio, libraries can train the next generation of researchers in data standards & standard practices

These are just a few of the many reasons why academic libraries should be engaged in the challenges of research data stewardship, curation, and management.

1 Science 11 February 2011: Vol. 331 no. 6018 pp. 692-693 2014-09-13


Data Management Plan (DMP) Templates
  • DMPTool: Interactive tool for drafting data management plans for a variety of funding agencies and institutions.
  • DMPTool Templates for data management plans based on specific funder requirements.
  • Johns Hopkins University Data Management Services has an excellent training module on  Using the DMPTool to Write Your Plan.

Data Repositories


Special thanks to Amy Nurnberger, Research Data Manager at Columbia University, for creating and compiling this information on Research Data Management for the ACRL Toolkit in the Fall of 2015.