Research Data Management: Data Management Plans

Open access to research data is increasingly important for accelerating research. Grant authorities therefore request detailed plans for how data is managed in the projects they finance. We have recently developed such a plan for the EU H2020 BIG-MAP project-a cross-disciplinary project targeting disruptive battery-material discoveries. Essential for reaching the goal is extensive sharing of research data across scales, disciplines and stakeholders, not limited to BIG-MAP and the European BATTERY 2030+ initiative but within the entire battery community. The key challenges faced in developing the data management plan for such a large and complex project were to generate an overview of the enormous amount of data that will be produced, to build an understanding of the data flow within the project and to agree on a roadmap for making all data FAIR (findable, accessible, interoperable, reusable). This paper describes the process we followed and how we structured the plan.

Researchers often wish to make knowledge publicly available, especially through publication, but may not wish to share their raw data. Human Subjects offices (IRBs) sometimes wish to keep all information private or even to have raw data destroyed. Funding agencies may hope for the data they finance collection of to be made publicly available to increase its impact. These motivations often conflict. This paper discusses how current Human Subjects regulations impact sharing of corpus data among researchers, how funding agencies influence this, and how researchers react to these forces. The paper also discusses potential future changes to the current outcomes, through changes to Human Subjects Protection regulations and changes to funding agency requirements on data sharing.

This paper describes an investigation into how researchers in different fields are interpreting and responding to the U.S. National Science Foundation’s data management plan (DMP) requirement. As documents written by the researchers themselves, DMPs can provide insight into researchers’ understanding of the potential value of their data to others; the environment in which their data are developed and prepared; and their willingness and ability to ensure the data are available to others now and in the long-term. With support from the Institute of Museum and Library Services, the authors conducted a content analysis of DMPs generated at their respective institutions using a shared rubric. By developing and testing a rubric designed to understand and evaluate the content of DMPs, the authors intend to develop a more complete understanding, at a larger scale, of how researchers plan for managing, sharing, and archiving their data.

A Data Management Plan, or DMP (sometimes also called a data sharing plan), is a formal document that outlines what you will do with your data during and after a research project. It describes the type of data you use for your research, how are collected, organized, and stored, and what formats you use. When senstive data are used, the DMP must also describe what steps you are taking to make your data secure and compliant with regulations. It details how data will be accessible and documented for sharing and reuse during and after the project is finished. DMP are required by an increasing number of funding entities and research institutions...

A data management plan, or DMP (sometimes also called a data sharing plan), is a formal document that outlines what you will do with your data during and after a research project. Many funding agencies, especially government funding sources, require a DMP as part of their application processes. Even if you are not seeking funding for your research, documenting a plan for your data is a best practice and will help your data comply with Harvard's policies for responsible data management.

In general, your data management plan should address the following:
• types of data, samples, physical collections, software, curriculum materials, and other
materials that will be produced over the course of the project;
• standards to be used for data and metadata format and content (where existing
standards are absent or deemed inadequate, this should be documented along with any
proposed solutions or remedies);
• policies for access and sharing, including provisions for appropriate protection of privacy,
confidentiality, security, intellectual property, or other rights or requirements;
• policies and provisions for reuse, re-distribution, and the production of derivatives; and
• plans for archiving data, samples, and other research products, and for preservation of
access to them.

Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing...

A data management plan (DMP) is a formal document that outlines how you plan to handle your data both during your research project and after your project is complete. The need for robust DMPs has increased, with more federal and private funding agencies requiring DMPs in their grant applications.  So how do you create a DMP?  STEM Data and Research Librarian Nick Ruhs will walk us through what DMPs are, resources that are available to help craft DMPs, how to create them, and examples of DMPs for specific funding agencies.

In this video we explore the data management plans and the different ways in which librarians can offer support to their research community.