Neuroscience: Research Data Management

• Overview
• Make a plan
  • Data Management Planning
  • Funder Requirements
• Organize Your Data
  • Consistent file organization
  • File format for long-term access
• Describe Your Data
  • Metadata
• Store Your Data
  • Data Security and Storage
  • Options & Best Practices
• Share Your Data
  • Benefits of Data Sharing
  • Data Sharing for Archival and Preservation Purposes
  • Considerations in Data Sharing
• Services and Resources

Contact dataservices@vt.edu for data management questions, for assistance in creating your data management and sharing plans, and for data management aspects to consider within your research project.

Jonathan Petters Ph.D., Data Management Consultant, Data Services Unit

• Data Stories Blog co-ordinated by the DCC and the RDA Engagement interest group
• Data horror stories compiled by Kristin Briney
• Data Stories compiled by DataONE
• RDM Good Examples  and Bad Examples compiled by Dorothea Salo

This guide can assist you in effectively managing, sharing, and preserving your research data. It provides information and guidance for all aspects of the data lifecycle, from creating data management plans during the proposal phase to sharing and publishing your data at the conclusion of your project. This guide is not specific to any particular funder, discipline, or type of data.

Research data management is “the active management and appraisal of data over the lifecycle of scholarly and scientific interest." Digital Curation Center, UK.

When do you start thinking about how to manage your data? The best time to make (and write) a data management plan is during the planning or proposal stage of a research project. The plan is an opportunity for you to articulate to you and your collaborators on how data will be effectively managed.  An effective data management can lead to a more efficient, more sound and less stressful research process.

In the case of a research proposal, this plan will show how you will meet a funding agency's data management and sharing policy for research results, as well as impress your peer reviewers with your comprehensiveness and thoughtfulness.

In a data management plan you will explain what your research data look like, how they are generated, analyzed, processed/visualized, and stored, and what you will do with the data over a medium or long term. Some details we recommend you keep track of and record as your research progresses include: file naming conventions, metadata standards for data documentation, storage space, security and back-up options. This guide will help you create documentation using appropriate metadata standards, and assist you with discovering and selecting appropriate data storage options.

Virginia Tech University Libraries also provide additional guidance and resources for data management with a different focus.

• NSF Data Management Plan Guide
• NIH Data Sharing Plan Guide

When you prepare to write and publish your research paper, we recommend considering strategies for sharing and preserving the underlying data. Will you deposit your data in a subject-specific repository, VT's data repository (VTechData), or developing your own infrastructure for data distribution? This guide will help you explore options and apply best practices to make your data available to a wider audience.

Research Data Management - a 27 pg. primer by Carly Strasser, NISO, 2015.