Data Management Plan Template European Commission

Standard Operating Procedure: European Commission Data Management Plan (DMP) Lifecycle Architecture

1. Document Control Block

• Document ID: SOP-TR-EC-DMP-042
• Effective Date: October 24, 2023
• Version: 2.4.0
• Review Cadence: Semi-Annual (Every 6 Months)
• Author: Julian Vance, Chief Architect, Template Registry

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2. Executive Summary & Purpose

This Standard Operating Procedure (SOP) defines the institutional requirements, technical workflows, and governance controls for authoring, validating, and maintaining a Data Management Plan (DMP) compliant with the European Commission (EC) Horizon Europe framework. The purpose of this document is to ensure absolute alignment with FAIR (Findable, Accessible, Interoperable, Reusable) data principles, guarantee secure management of research data, and operationalize contractual reporting milestones across all project lifecycles hosted or registered within Template Registry.

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3. Scope & Prerequisites

Scope

Applies to all principal investigators, data stewards, work package leads, and technical architects contributing to EC-funded grants managed or cataloged via Template Registry infrastructure.

Prerequisites & Required Tools

• Active institutional or project-level account on DMPonline or Data Stewardship Wizard (DSW).
• Access to a certified trusted repository (e.g., Zenodo, Figshare, institutional Open Access repositories).
• Familiarity with the Horizon Europe Annotated Grant Agreement (AGA), specifically Article 17 (IPR) and Article 39 (Open Science).
• Standard Operating Environment: Markdown editor, JSON schema validators, and Git-versioned repository access.

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4. Roles & Responsibilities

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5. Step-by-Step Procedure

Phase 1: Initial Assessment and Infrastructure Setup

• 1.1 Extract DMP requirements directly from the specific EC Grant Agreement Data Management section and Milestone timeline (typically due at Month 6).
• 1.2 Initialize the standardized EC DMP template via the designated platform (e.g., Horizon Europe template via DMPonline).
• 1.3 Assign access control lists (ACLs) within the template repository to designated Work Package Leads and the institutional Data Steward.
• 1.4 Establish a version-controlled companion repository (/dmp-docs) under the project's internal Git registry to track edits.

Phase 2: Data Generation, Collection, and Documentation (FAIR Principles)

• 2.1 Inventory all anticipated datasets, outlining expected data volumes, formats (preferring open standards like CSV, NetCDF, JSON, TIFF), and collection methodologies.
• 2.2 Define the metadata standards to be utilized (e.g., Dublin Core, DDI, DataCite) ensuring machine-readability and cross-walk compatibility.
• 2.3 Formulate persistent identifier (PID) allocation strategies (e.g., assigning DOIs via Zenodo upon dataset publication).
• 2.4 Document data quality assurance processes, including calibration logs, versioning schemas, and automated validation tests.

Phase 3: Ethical, Legal, and Security Frameworks

• 3.1 Conduct a Personal Data Audit in conjunction with the DPO to determine if General Data Protection Regulation (GDPR) constraints apply.
• 3.2 Detail explicit anonymization, pseudonymization, or encryption protocols (AES-256 at rest, TLS 1.3 in transit) for sensitive or Personal Identifiable Information (PII).
• 3.3 Outline intellectual property rights (IPR), licensing conditions (e.g., CC-BY 4.0 for data, MIT/Apache-2.0 for software), and embargo periods where commercial exploitation is pending.
• 3.4 Define secure storage architecture, daily incremental backup routines, and off-site replication frequencies.

Phase 4: Data Sharing, Storage, and Long-Term Preservation

• 4.1 Select appropriate certified open-access repositories guaranteeing long-term preservation (minimum 10 years post-project).
• 4.2 Formulate the Open Research Data (ORD) strategy: "As open as possible, as closed as necessary" (justifying any restrictions due to security, privacy, or commercial interests).
• 4.3 Calculate estimated storage costs and identify resource allocation within the project's direct costs or institutional infrastructure.
• 4.4 Define workflow for long-term accessibility, including software emulation requirements or format migrations.

Phase 5: Validation, Submission, and Living-Document Maintenance

• 5.1 Perform a pre-submission completeness audit against the EC DMP evaluation rubric (Checklist: FAIR coverage, GDPR alignment, Repository certification).
• 5.2 Submit the finalized DMP via the EC Funding & Tenders Portal as a formal contractual deliverable by the M6 deadline.
• 5.3 Convert the DMP into a "living document," scheduling mandatory updates at mid-term (M18) and project end (M36/M48).
• 5.4 Archive the signed confirmation receipt within the Template Registry compliance archive.

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6. Quality Assurance & Pro-Tips

Best Practices

• Adopt Open Formats Early: Never rely on proprietary file formats for primary deliverables; mandate open-standard equivalents during project kick-off.
• Link PIDs Proactively: Ensure that publications linked in the DMP reference the associated datasets via explicit PID cross-linking.

Common Pitfalls to Avoid

• Generic Statements: Avoid vague text like "Data will be stored securely." Specify exact physical server locations, encryption standards, and toolsets.
• Neglecting GDPR: Failing to consult the DPO early often results in EC reviewers flagging non-compliant consent forms for human-subject data.

Metric Thresholds

• FAIR Scorecard Completeness: $\ge 95%$ adherence to designated machine-readable metadata standards.
• Review Latency: Internal institutional review must not exceed 5 business days prior to milestone deadlines.

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7. Frequently Asked Questions (FAQ)

Q1: What happens if our data generation strategy shifts significantly midway through the project?
A1: The EC DMP is a living document. Substantial shifts in methodology, repository choices, or data types must be documented via internal version control and formally updated in the EU Funding & Tenders Portal during the scheduled periodic reporting intervals or mid-term review.

Q2: How do we handle proprietary or commercially sensitive data without violating Open Science mandates?
A2: Apply the "as closed as necessary" principle. Explicitly state the commercial exploitation grounds, patent applications, or security constraints in Section 3 of the DMP, and outline an embargo period during which access is restricted prior to public release.