Research Data Management NSF Data Sharing Policy

NOTE: Even if if your proposed project will not produce data, you must include a document justifying this in place of the data management plan. For projects that do produce data, the 2-page plan should cover five areas:

1. Description of data. Describe the types of data, samples, physical collections, software, curriculum materials and other materials to be produced during the project.

2. Data standards. The standards to be used for data and metadata format and content. 

   This section allows you to explain which file formats you’ll be using and detail what metadata will be shared. Metadata are structured information about the data that facilitate its interpretation and reuse. Metadata include information such as who created the data, date of creation, sample ID number, etc. It is important to share document(s) that outline file naming convention, file organization, defines variables, and protocols.

   Data standards should be considered for each type of data being collected/analyzed. Explain any cases where there are no formal standards for a particular data type and how the data will be structured and include codebooks and/or data dictionaries. 

   • Examples of data standards
     • Standard terminology (eg. IUPAC nomenclature for chemicals, gene ontology terms for systems biology etc.)
     • Non-proprietary file formats such as .pdf, .tif, .txt, .csv
     • Vetted standard survey instruments for surveys and interviews 
   • Bioportal Ontologies and fairsharing.org are useful resources for discovering data and metadata standards for your field of study
3. Data access and sharing. Address appropriate protection of privacy, confidentiality, security, intellectual property, etc.
4. Policies and provisions for data reuse, redistribution and the production of derivatives.
5. Plans for preserving and sharing data, samples, and other research products. 
   • Detail where, when and how long data will be shared
   • Review the How to select a data repository section of this guide

Tip: A good way to start writing a DMSP is to build a summary table. 

These sample plans were contributed by UAB researchers with successfully funded NSF grants. If you would like to add your Plan to the collection, please contact the OSC.

Sample 1. Functional genomics project in Drosophila. Data types include DNA sequencing and tabular data. Multiple data repositories including Open Science Framework (OSF), Sequence Read Archive (SRA), Gene Expression Omnibus (GEO) and Dryad.

Sample 2. Student behavioral study. Data types include behavioral data, survey responses, and data from the Rockviewer software and electronic records. Data repositories include OSF and an external institutional repository.

For additional examples, see the DMPTool's catalog of sample plans.

Effective July 24, 2023, the National Science Foundation (NSF) updated the Project Reporting System in Research.gov to enable datasets and research materials to be entered as distinct product types that are managed and reviewed separately. This change improves project report data quality by listing each product type resulting from NSF funded research as a separate entry rather than a combined listing of multiple product types. 

An updated How to Add Datasets to the NSF-PAR and NSF In-progress Project Reports guide and updated How to Remove Datasets from the NSF-PAR and In-progress Project Reports guide are available on the Research.gov About Public Access page. Visit the NSF Public Access Initiative page for more information including the NSF Public Access Plan 2.0 - Ensuring Open, Immediate and Equitable Access to National Science Foundation Funded Research.

National Science Foundation Public Access Repository (NSF-PAR) for scholarly publications and datasets

NSF public action plan 2.0 (released February 21, 2023)