Data Management Plans (DMPs) are a crucial element of good data management as they provide the description of its life cycle, following the FAIR (findable, accessible, interoperable and re-usable) data principle. DMPs include information on: ● How the data will be handled (how it will be described, managed and stored) both during and after the end of the project; ● What data will be collected, processed and/or generated by the project; ● Which methodology and standards will be used; ● Whether data will be shared/made open access and; ● How data will be protected and preserved (including after the completion of the project). This document presents the updated version of the SUSTRACK Data Management Plan (DMP), prepared as D7.2 (T7.4, WP7 “Project Management”). Building on the initial DMP submitted in Month 6, this revised version incorporates the experience gained during project implementation, updates on data collection and processing activities, and refinements to ensure alignment with FAIR principles and Horizon Europe requirements. As a living document, the DMP evolved alongside the project, reflecting new datasets, updated methodologies, and lessons learned from ongoing activities. This updated version consolidates the final state of SUSTRACK’s data management practices and provides a framework that ensures all data generated, collected, processed, and re-used was handled transparently, securely, and in a way that maximises its scientific, societal, and policy relevance. In line with the project’s objectives and expected outcomes, SUSTRACK involved multiple activities that required systematic data collection, generation, processing, and validation across scientific, policy, and stakeholder engagement dimensions. To guarantee reliability and reproducibility, datasets were securely stored immediately after collection or generation, as well as after processing. The purpose of this final DMP is to provide the consortium with a consolidated and harmonised framework for data management throughout the SUSTRACK project. It defined common rules and practices for the collection, documentation, storage, preservation, and sharing of project data. Metadata standards were consistently applied (e.g. author, date, affiliation, version, title, revisions, access rights, and storage details), ensuring that datasets were findable, interoperable, and suitable for long-term preservation. By following these practices, the consortium strengthened internal communication, ensured full compliance with ethical and legal requirements (including GDPR), and maximised the value and re-use potential of SUSTRACK data. As a result, the project’s datasets have been made accessible and usable for policymakers, researchers, industry stakeholders, and society at large, contributing to both the scientific knowledge base and evidence-based policymaking in support of the transition to a sustainable circular bioeconomy. This document includes the description of: ● Data types and how this data was collected, processed, maintained and shared during and after the end of the project; ● FAIR data management; ● Data Security; ● Preferred repositories to archive published data ● Metadata and vocabulary ● Social, Ethical, Legal, and Privacy concerns.
Mester et al. (Mon,) studied this question.