D7.2 – Data Management Plan
Deliverable 7.2 – Data Management Plan, was submitted by CzechGlobe with contributions from all partners in November 2023. The description of the deliverable is available below and the full deliverable is at the end for download.
As a research project funded under the Horizon Europe programme of the European Commission, PLUS Change will follow all rules on Open Science, Open Research Data and Research. When research data are well organised, well stored, and accessible, their validity can be monitored at all times and the result is high-quality, efficient research and cost savings. The PLUS Change consortium aims to contribute to open science policy and practices by guaranteeing that research data is made findable, accessible, interoperable, and reusable (FAIR). This will be achieved through a project-specific Data Management Plan (DMP), which will ensure that research data used and generated within PLUS Change will be managed in a resilient and transparent way.
The purpose of this DMP is to provide an analysis of the main elements of the data management policy that will be applied with regard to all the datasets to be generated in PLUS Change including the process, methodology and policy on data generation/collection, handling, archiving/ preservation and data application.
This data management plan (DMP) is a Deliverable as part of Task 7.2 within Work Package 7. The DMP has been developed in close collaboration with project partners who provided information on their planned usage and generation of research data, along with their institutional policies on data management. The DMP will be updated throughout the project, to reflect emerging data management needs. A final DMP is an additional Deliverable in Task 7.2, due at the end of the project.
The project consortium has defined the expected used and generated data types and their description based on a questionnaire filled out by partners in coordination with WP leaders. This process of defining data types serves also as a process of identifying data management challenges, overlaps in data needs, and possible synergies in data needs across the project. In particular, it serves to foster cooperation between the research and practice partners in the consortium to match together data needs and availability of datasets and material held by the practice partners from their previous and ongoing work.