Data Management Plan Nsf Template

Standard Operating Procedure: NSF Data Management Plan (DMP) Architecture & Compliance

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1. Executive Summary & Purpose

1.1 Purpose

This Standard Operating Procedure (SOP) defines the institutional engineering standard for authoring, validating, and submitting Data Management Plans (DMPs) in compliance with National Science Foundation (NSF) Proposal & Award Policies & Procedures Guide (PAPPG) requirements.

1.2 Objective

To eliminate audit risk, ensure metadata longevity, enforce FAIR (Findable, Accessible, Interoperable, Reusable) data principles, and maximize institutional compliance through a standardized 2-page operational framework.

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2. Scope & Prerequisites

2.1 Scope

Applies to all research proposals, subawards, and cooperative agreements submitted to the NSF originating from or managed via Template Registry infrastructure.

2.2 Prerequisites & Tooling

• Active Access: DMPTool (dmptool.org) institutional account.
• Repository Targets: Institutional Data Repository (e.g., Dataverse, Dryad, ICPSR) or NSF-recognized disciplinary repository (e.g., GenBank, Zenodo).
• Standards Framework: Dublin Core, DDI, or Darwin Core depending on domain-specific metadata requirements.
• Software Requirements: Markdown / LaTeX for document compilation, Git for version control of code artifacts.

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3. Roles & Responsibilities (RACI Matrix)

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4. Step-by-Step Procedure

Phase 1: Pre-Submission Architecture & Scoping

• 1.1 Review current NSF PAPPG instructions and Directorate-specific (BIO, CISE, ENG, GEO, MPS, SBE) guidelines for unique DMP mandates.
• 1.2 Identify all data, code, physical samples, and derived digital artifacts to be generated during the project lifecycle.
• 1.3 Establish the persistent identifier (PID) strategy (e.g., DOI, ORCID, RRID) for datasets and software releases prior to project initiation.

Phase 2: Core DMP Drafting via Template Registry Framework

• 2.1 Initialize the master document using the Template Registry NSF-compliant structural template within DMPTool.
• 2.2 Draft Section 1: Products of Research detailing types of data, samples, physical collections, software, curriculum materials, and other materials to be produced.
• 2.3 Draft Section 2: Standards specifying metadata standards, data formats (e.g., CSV, NetCDF, HDF5, JSON), and nomenclature rules to ensure interoperability.
• 2.4 Draft Section 3: Policies for Access and Sharing defining access timelines (immediate upon publication vs. embargo periods), provisions for privacy/confidentiality, and intellectual property/license assignments (e.g., CC-BY-4.0, MIT License).
• 2.5 Draft Section 4: Reusability, Redistribution, and Policies outlining long-term preservation strategies, duration of data retention (minimum 3-5 years post-award closeout per federal guidelines), and third-party repository commitments.

Phase 3: Compliance Validation & Technical Review

• 3.1 Verify document length constraints (strictly $\le$ 2 pages as an NSF supplementary document).
• 3.2 Run internal metadata schema check against target repository ingestion APIs.
• 3.3 Submit draft to the Institutional Data Librarian for syntax and policy validation.

Phase 4: Integration & Institutional Sign-Off

• 4.1 Export final DMP as a PDF conforming to NSF margin and typography requirements (1-inch margins, Times New Roman 11pt or equivalent).
• 4.2 Attach the compiled PDF to the FastLane / Research.gov / Grants.gov submission package under the "Data Management Plan" module.
• 4.3 Archive the source Markdown/LaTeX file and compiled PDF within the Template Registry version-control system.

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5. Quality Assurance & Pro-Tips

5.1 Pro-Tips for Systemic Compliance

• Avoid Vague Commitments: Replace ambiguous phrases like "data will be shared upon request" with deterministic actions: "Data will be deposited in [Repository Name] and assigned DOI [Pending] within 30 days of primary publication."
• Budget Alignment: Ensure any costs associated with long-term data archiving or specialized repository fees are explicitly accounted for in the proposal's budget justification.

5.2 Common Pitfalls

• Exceeding Page Limits: Using dense text blocks that overflow the 2-page limit, resulting in automated rejection by NSF administrative systems.
• Proprietary Formats: Committing to proprietary data formats without specifying conversion pipelines to open, archival-grade formats (e.g., TIFF over PSD).

5.3 Metric Thresholds

• Metadata Completeness Score: $\ge 98%$ compliance with Dublin Core standard.
• Repository Uptime SLA: Target repositories must guarantee $\ge 99.9%$ availability and permanent retention guarantees of $\ge 10$ years.

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6. Frequently Asked Questions (FAQ)

Q1: What should be done if the research generates human-subjects data requiring restricted access?

A1: Explicitly state the legal and ethical constraints within Section 3 of the DMP. Outline the protocols for de-identification, secure institutional enclaves, and controlled-access repositories (e.g., ICPSR, dbGaP) while maintaining compliance with HIPAA/IRB regulations.

Q2: Are software and code repositories considered valid outputs under the NSF DMP template?

A2: Yes. Source code, scripts, and computational pipelines must be treated as primary research products. They must be archived in a permanent repository (e.g., Zenodo via GitHub integration) with an open-source license specified in the DMP.