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Data Management @ SCU: Best Practices

How to write a data management plan for an NSF or other grant proposal.

Elements to Include

The particular requirements of a data management plan will vary among funding agencies so it is best to always consult the agency. However there are a few attributes which are common to all data management plans including:

1. Types of data to be produced

2. Description and the methodology of how the data will be collected

3. Standards that would be applied for format, i.e. metadata

4. Provisions for archiving and preservation

5. Backup and storage procedures

6. Access policies and provisions for secondary uses

7. Plans for eventual transition of the data collection after project is complete

8. Any protection or security measures taken to protect participant confidentiality or intellectual property

Best Practices, Examples and Tools

This tool walks users through the process of creating ready-to-use data management plans for various funding agencies. Downloadable templates are also available for various agencies and National Science Foundation (NSF) directorates.

National Institutions of Health (NIH) Data Sharing guidance
Selected NIH policies and related guidance on sharing of research resources developed with NIH funding, including example data sharing plans.

MIT Libraries' Data Planning Checklist
This list of data planning issues is a good tool for systematically evaluating your data management plan draft to ensure that it addresses important issues.

ICPSR's Guidelines for Effective Data Management Plans
Numerous resources for researchers in the social sciences, including a printable booklet of best practices, the Guide to Social Science Data Preparation and Archiving: Best Practice Through the Data Life Cycle, 4th ed. [pdf].

NSF Proposal & Award Policies & Procedures Guide (PAPPG)  NSF 20-1 June 1, 2020.

Ten Simple Rules for Creating a Good Data Management Plan

Article from PLoS - Computational Biology.  It presents ten simple rules that can help guide the process of creating an effective plan for managing research data—the basis for the project’s findings, research papers, and data products

UK Data Archive’s Managing and Sharing Data: a best practice guide for researchers, 3rd ed. [pdf] 
This booklet addresses preferred file formats for preservation of various types of data (images, text, geospatial data, etc.), best practices for quality control, version control, storage, migration, security, anonymization, copyright, and access. Some of the information about British law is only relevant for researchers in the United Kingdom, but most of it is pertinent for all researchers.

University of Minnesota Libraries' Managing Your Data
This guide includes a glossary of data-related terms, summary of funding agency guidelines, and information on data documentation, storage, sharing, and citation.

DataONE Learn
Data management best practices and five sample NSF data management plans from DataONE, a major environmental sciences project funded by the NSF.

Some Simple Guidelines for Effective Data Management
Elizabeth T. Borer, Eric W. Seabloom, Matthew B. Jones, Mark Schildhauer. Bulletin of the Ecological Society of America 90(2) 205-214
This article provides practical advice for beginners about the technical details of managing tabular data, such as hardware and software formats, and file naming.
Credit:  Western Carolina University - Hunter Library's Data Management Plans

Engineering/Math Librarian