Data Management Plan - Horizon Europe

Data Management Plan Horizon Europe Thursday, 18 September 2025 Max Steinhausen1, Joanna Mau1, Tobias Conradt2, Martin Drews3, Paolo Mazzoli4, PiaJohanna Schweizer5, Lydia Cumiskey6, Amalie Laursen7, Sandro Nanni13, Christopher Genillard9, Stefan Hochrainer-Stigler10, Julian Struck11, Levente Huszti12, Valeria Pancioli8, Heiko Apel14, Katharina Demmich15, Chahan Kropf16, Tracy Irvine17, Sukaina Bharwani18 1. TECHNISCHE UNIVERSITAET BRAUNSCHWEIG 10. INTERNATIONALES INSTITUT FUER ANGEWANDTE SYSTEMANALYSE 2. POTSDAM-INSTITUT FUR KLIMAFOLGENFORSCHUNG EV 11. ERFTVERBAND 3. DANMARKS TEKNISKE UNIVERSITET 12. ZALA KULONLEGES MENTOK ES ONKENTES TUZOLTO EGYSULET 4. GECOSISTEMA SRL 13. AGENZIA REGIONALE PER LA PREVENZIONE, L'AMBIENTE E L'ENERGIA DELL'EMILIAROMAGNA 5. RESEARCH INSTITUTE FOR SUSTAINABILITY 14. HELMHOLTZ ZENTRUM POTSDAM DEUTSCHESGEOFORSCHUNGSZENTRUM GFZ 6. UNIVERSITY COLLEGE CORK - NATIONAL UNIVERSITY OF IRELAND, CORK 15. 52 NORTH SPATIAL INFORMATION RESEARCH GMBH 7. REGION HOVEDSTADEN 16. EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZÜRICH 8. AGENZIA REGIONALE PER LA SICUREZZATERRITORIALE E LA PROTEZIONE CIVILE 17. OASIS HUB LIMITED 9. GENILLARD & CO GMBH 18. SEI OXFORD OFFICE LIMITED Data Management Plan 2 Report overview Project number 101073978 Project acronym DIRECTED Project name Disaster Resilience for Extreme Climate Events providing Interoperable Data, Models, Communication and Governance Call HORIZON-CL3-2021-DRS-01 Topic HORIZON-CL3-2021-DRS-01-02 Type of action HORIZON Innovation Action Responsible service European Research Executive Agency Project starting date 01/10/2022 Project duration 4 Years Period covered 1 October 2022 - 30 September 2026 Reporting period number RP1 Periodic report date and version 28 February 2023 Data Management Plan 3 Document history The Horizon Europe Model Grant Agreement requires that a data management plan (‘DMP’) is established and regularly updated. The use of this template is recommended for Horizon Europe beneficiaries. In completing the sections of the template the requirements for research data management of Horizon Europe as described in Article 17 and analysed in the Annotated Grant Agreement, article 17, must be addressed. Version Date Comment 1.0 03/02/2023 Initial Version (Draft) 2.0 08/08/2023 Updated content based on partner feedback 3.0 18/09/2025 Reworked version for upload to Zenodo Data Management Plan 4 Executive summary This Deliverable constitutes the Data Management Plan (DMP). This report presents what type of data will be collected, generated or handled throughout the duration of the DIRECTED project and after its completion, not just among the consortium members but also those outside of the project. The DMP should be considered a living document that is to be updated over the course of the project whenever significant changes arise. Throughout the project more details regarding the structure and types of documents will be clarified and this document will address these changes accordingly. The DMP will be adapted whenever major changes arise or more details become apparent, but it will be reviewed at least annually. A final version of the DMP will be available at the end of the project. The aim of the initial version of the DIRECTED DMP is to provide a general overview of data types collected and/or created by different project partners and on the usage of such data in line with the project objectives. The Horizon Europe DMP template was used and as the project proceeds, more questions will be addressed in detail. The DMP states the type of data generated through various work packages (WPs) and the restrictions that may apply during dissemination and exploitation of the data. The DMP outlines the scope of FAIR data management in DIRECTED and the allocation of resources for various activities concerning DMP. The data security measures that apply to the DIRECTED data repositories and the ethical aspects of the data generated through questionnaires and survey are covered in the DMP. The document summarizes the accessibility of the results of various tasks involved from all the WPs. A questionnaire that was circulated among the partners of DIRECTED to obtain information for the DMP is provided at the end of the document as an annex. Generally, it can be said that the data in the project can be categorized as follows: • Model data including input and output data sets • Risk-Tandem Framework (set up and evaluation) • Architecture of the DIRECTED Data Fabric (Data-Infrastructure) • RWL surveys, interviews and workshops • Policy recommendations • Training materials A large part of the data will be stored in .docx, .pdf, .pptx, .jpg or .xlsx and .csv format according to the data generated. The size of the data stored depends on the data origin and software/user requirements. The largest volume (GB to TB) and greatest number of files have been foreseen for data related to model input (WP 2), whereas other data corresponding to reports and training material are in the range of few MB’s and files. In DIRECTED, data generated and collected throughout the project will be stored in open repositories such as Zenodo or OpenAIRE. A key component of the project is the setup of a Data Fabric (WP 5) to make data, software and metadata generated in DIRECTED publicly accessible and easily findable. Data security of all the restricted data is ensured through access control with restricted access (username + password) to authorized users from each partner. Restricted data is stored locally on existing infrastructure of project partners and on secured self-hosted servers. Data Management Plan 5 Contents Report overview .................................................................................................................... 2 Document history .................................................................................................................. 3 Executive summary ............................................................................................................... 4 List of Abbreviations .............................................................................................................. 6 1 Data Summary ............................................................................................................... 7 2 FAIR data....................................................................................................................... 9 2.1 Making data findable, including provisions for metadata .......................................... 9 2.2 Making data accessible ......................................................................................... 10 2.3 Making data interoperable ..................................................................................... 12 2.4 Increase data re-use ............................................................................................. 12 3 Other research outputs .......................................................................................... 13 4 Allocation of resources .......................................................................................... 13 5 Data security ......................................................................................................... 14 6 Ethics .................................................................................................................... 14 7 Other issues .......................................................................................................... 14 Annex of figures and tables ................................................................................................. 16 Annex ................................................................................................................................. 17 Partners .............................................................................................................................. 19 Data Management Plan 6 List of Abbreviations ACRONYM DEFINITION CCA CLIMATE CHANGE ADAPTION DMP DATA MANAGEMENT PLAN DRM DISASTER RISK MANAGEMENT DRR DISASTER RISK REDUCTION FAIR FINDABLE,ACCESSIBLE, INTEROPERABLE AND REUSABLE RWL REAL WORLD LAB WP WORK PACKAGE DOA DESCRIPTION OF THE ACTION GDPR GENERAL DATA PROTECTION REGULATION Data Management Plan 7 1 Data Summary The DIRECTED data management plan was prepared based on the official “Horizon Europe data management plan template. The DMP will support DIRECTED partners to identify and address ethics issues and handling of data during and beyond the project’s lifespan. In order to collect input for the DMP, an online spreadsheet was compiled which is stored on the Nextcloud server hosted by TU-Braunschweig that is used by DIRECTED partners to store and share files throughout the project. The file will allow all partners to easily note changes or further details in connection to data management. DMP and WP 5 – Data Fabric are closely linked in the DIRECTED project. WP 5 has the objective to establish a platform that makes DRR and CCA related data and software accessible and interoperable for users from various communities, e.g. Scientific, administrative, commercial. Further, there is a close link to WP 6 related to dissemination and communication activities. A key task of WP 6 is the establishment of the e-Learning portal where all training materials generated throughout the project will be available. The DMP will describe what data sets should be made available and how. For some aspects the question of how cannot be fully addressed at this stage of the project as this will depend on the outcome of other work packages in the project, namely WP 2. Sharing of project data is a central goal of DIRECTED, which will in return foster all dissemination and exploitation activity even beyond the duration of the project. In general, the data generated in DIRECTED can be categorized as follows: • Model data including input and output • Risk-Tandem Framework (set up and evaluation) • Architecture of Data Fabric • RWL surveys, interviews and workshops • Policy recommendations • Training materials What types and formats of data will the project generate or re-use? A large part of the data generated in the project will be stored as .docx, .pdf, .pptx, .jpg, or .xlsx depending on the type of data generated. Data related to model input or output is stored in different formats such as CSV, TIFF, NetCDF or complex data format such as HDF5. Data Management Plan 8 Will you re-use any existing data and what will you re-use it for? What is the origin/provenance of the data, either generated or re-used? Data generated in DIRECTED partially relies on already existing data such as data publications (WP 3) or in case of model input data collected from the RWL, data from national agencies, or monitoring stations are used. What is the purpose of the data generation or re-use and its relation to the objectives of the project? The overall goal of the data generation depends on the different WPs and Tasks in the project. WP 2 aims to make selected numerical models interoperable, i.e. able to share and incorporate information between various different models. Tools and models used include SaferPLACES Digital Twin Solution for flood risk intelligence, RIM2D pluvial flood risk modelling and forecasting, Seamless Forecasting Tool, CLIMADA, DCAM. Access rights to the tools as well as use of generated output is agreed upon in the CA. Data collected in WP 3 is largely connected in developing the Risk-Tandem and assessing its functionality in the RWLs. The purpose of the datasets in WP 4 is to develop and strengthen the Tandem coproduction framework. What is the expected size of the data that you intend to generate or re-use? The sizes of the files vary considerably, whereas simple reports use around a few KB, other files such as static data from an RWL can be up to a size of 40 TB (more than 1000 files). To whom might your data be useful ('data utility'), outside your project? The data and general research output is aimed at the public, specifically stakeholders of the RWL or policy makers. The generated datasets are of DIRECTED are thus publicly available. Background not intended for public use, is stated in the CA including conditions for availability among DIRECTED partners and how it may or may not be exploited. Data Management Plan 9 2 FAIR data 2.1 Making data findable, including provisions for metadata Will data be identified by a persistent identifier? Most data will, at this stage of the project, will not be assigned a persistent identifier, as these data sets will mostly be for internal use and development. They therefore do not yet require a persistent id. With progressing development of tools, data sets and software more and more data will be made public and receive persistent ids, such as DOI or perma.cc. Will rich metadata be provided to allow discovery? What metadata will be created? What disciplinary or general standards will be followed? Rich metadata will be provided with most openly and internally available data. DIRECTED will make use of one or more of the following metadata standards: • CERIF - Common European Research Information Format • CF (Climate and Forecast) Metadata Conventions In case metadata standards do not exist in your discipline, please outline what type of metadata will be created and how. For data sets or software where no general standard for metadata exists or where no metadata can easily be attached DIRECTED will ensure that descriptive metadata will be made available as part of the documentation or integrated into the data itself. Metadata will include: title, description, keywords, author, contact, version, date Where applicable we will also include legal metadata such as licenses and references to work of third parties included in the data or software. Will search keywords be provided in the metadata to optimize the possibility for discovery and then potential re-use? Will metadata be offered in such a way that it can be harvested and indexed? Keywords will be provided with all publicly available and searchable data sets, software and other publications to improve discoverability. Further metadata will be offered in such a way that it can be harvested Data Management Plan 16 Annex of figures and tables Figure 1: Schematic of the DIRECTED Data-Infrastructure developed in WP 5. ................. 12 Table 1: Annex 1 DMP Questionnaire for DIRECTED partners .......................................... 18 Data Management Plan 17 Annex DATA MANAGEMENT PLAN QUESTIONNAIRE FOR DIRECTED PLEASE FILL THE BLANK CELLS STARTING FROM COLUMN C FOR THE DIRECTED PROJECT. IF YOU HAVE MORE THAN ONE DATASET, PLEASE USE ADDITIONAL COLUMNS. Table 1: Annex 1 dmp questionnaire for directed partners PARTNER NAME NAME: WORK PACKAGE LEADER AND DELIVERABLE LEAD FOR WP(S): PROJECT PARTNER(S) INVOLVED: DELIVERABLE (S): DATASET NAME NAME: DATASET DESCRIPTION PLEASE WRITE A BRIEF DESCRIPTION OF THE DATASET. RESPONSIBLE PARTNERS WHO ARE THE LEAD PARTNERS RESPONSIBLE FOR THE DATASET GENERATION/COLLECTION? PURPOSE WHAT IS THE PURPOSE OF THE DATA COLLECTION/GENERATION AND ITS RELATION TO THE OBJECTIVES OF THE PROJECT? TYPE, FORMAT AND VOLUME WHAT TYPES OF DATA WILL THE PROJECT GENERATE? CAN IT BE STORED BEYOND THE PROJECT, WILL YOU PROVIDE CONSENT? WHAT DATA FORMAT IS USED (E.G. XLS, DOC, PDF, PPT, JPEG, OPJ, TIFF, ...)? VOLUME WHAT IS THE EXPECTED FILE SIZE (IN GB OR MB)? NUMBER OF FILES (APPROX): SOURCE WHAT IS THE ORIGIN OF THE DATA? HOW IS THE DATASET GENERATED/COLLECTED? WILL YOU PROVIDE META DATA? YES OR NO DOES IT NEED ADDITIONAL SOFTWARE TO BE READ? IF YES PLEASE SPECIFY! DO YOU OR YOUR ORGANISATION HAVE A SPECIFIC WAY OF NAMING A FILE, SPECIFIC USE OF ABBREVIATIONS (E.G. YYYY-MMDD_FILENAME_AUTHOR.XYZ) STORAGE AND ACCESS WHERE DO YOU INTEND TO STORE YOUR DATA? DO YOU INTEND TO USE A REPOSITORY? IF YES, PLEASE CLARIFY HOW WILL YOU MANAGE ACCESS TO THE DATA? WILL DATA BE IDENTIFIED BY A PERSISTENT IDENTIFIER? YES OR NO Data Management Plan 18 EVALUATION OF DATA QUALITY DO YOU ACCEPT TO EVALUATE THE QUALITY OF DATA PROVIDED ? YES OR NO PLEASE DESCRIBE YOUR QUALITY ASSURANCE PROCESS IPR OWNER DO YOU FORESEE PRIOR INTIMATION BEFORE USING YOUR CONTENT? YES OR NO WHICH LICENSE WILL APPLY? PLEASE SPECIFY! WILL YOU MARK A CONTENT CONFIDENTIAL AS YOU SEE FIT? YES OR NO (SENSITIVE/PUBLIC) RE-USE EXISTING DATA WILL YOU RE-USE ANY EXISTING DATA? YES OR NO IF YES, HOW WILL YOU USE? HOW MANY PEOPLE FROM YOUR TEAM WILL ACCESS THE DATA? ARE THERE SOME SPECIFIC PERSON ALLOCATED FROM YOUR TEAM? BENEFICIARY TO WHOM WILL THE DATA BE USEFUL? ETHICS ARE THERE ETHICAL ISSUES RELATED TO YOUR DATA? YES OR NO WILL YOU TAKE NECESSARY PRECAUTIONS TO PREVENT SHARING PERSONAL DATA CONFINING TO GDPR ? KEYWORDS PLEASE PROVIDE SOME KEYWORDS THAT MAY BE ASSOCIATED WITH THE DATASET TO OPTIMIZE REUSE POSSIBILITIES (E.G. SURVEY, ROADMAP, …) VERSION NUMBER WILL YOU PROVIDE CLEAR VERSION NUMBER TO KEEP TRACK OF CHANGES TO THE DATASET? YES OR NO COSTS AND RESOURCES IS THERE ENOUGH RESOURCE FROM YOUR SIDE TO ENSURE FAIR (FINDABLE, ACCESSIBLE, INTEROPERABLE AND RE-USABLE) DATA MANAGEMENT AND TIMELY UPLOADING OF GENERATED DATA? YES OR NO HOW MANY (PERSONNEL) RESOURCES DO YOU ESTIMATE TO ALLOCATE TO DATA MANAGEMENT (I.E. 1 PERSON MONTH/YEAR) Data Management Plan 19 Partners