D1.3 Data Management Plan HURRICANE

Deliverable D1.3: Data Management Plan 2025 Resilient and holisc soluon for first responders Funded by the European Union Horizon Europe Research and Innovaon Program under Grant Agreement N°101168017. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union Funded by the European Union 2 Table of Contents List of Tables ................................................................................................................................ 3 Document History ........................................................................................................................ 4 Disclaimer ................................................................................................................................... 5 List of Participants ........................................................................................................................ 5 1. Executive Summary ............................................................................................................... 5 2. Acronyms ............................................................................................................................. 6 3. Introduction .......................................................................................................................... 7 3.1 Brief descripon of the project and its objecves ........................................................................................... 7 3.2 Purpose of the DMP and how it aligns with Horizon Europe's Open Science policy ....................................... 7 4. Data Summary ...................................................................................................................... 7 4.1 Risk: The potenal impact if the data is improperly disclosed. Potenal use cases for the data.................... 9 5. FAIR Data Management ........................................................................................................ 10 5.1 Metadata standards and idenfiers (e.g., DOIs, URIs)................................................................................... 10 5.2 Naming convenons for datasets .................................................................................................................. 10 5.3 Data documentaon and metadata schemas ................................................................................................ 11 5.4 File formats ensuring interoperability ........................................................................................................... 12 6. Storage and backup during the research process ................................................................... 12 6.1 Centralized Storage with redundancy ............................................................................................................ 12 6.2 Automated and Regular Backups ................................................................................................................... 12 6.3 Version Control and Change Management .................................................................................................... 12 6.4 Compliance with Security and Data Protecon Standards ............................................................................ 12 7. Data management responsibilities and allocation of resources .............................................. 13 7.1 Roles and responsibilies of team members in data management .............................................................. 13 7.2 Training requirements for data handling ....................................................................................................... 14 7.3 Budget allocaon for data management and storage. .................................................................................. 14 8. Data security (sharing and long-term preservation) ................................................................ 15 8.1 Data Classificaon and Access Control .......................................................................................................... 15 8.2 Encrypon and Secure Storage ...................................................................................................................... 15 8.3 Long-Term Preservaon Strategy .................................................................................................................. 15 Funded by the European Union 3 9. Legal and ethical requirements, codes of conduct ................................................................. 16 10. Intellectual Property Rights ............................................................................................... 16 List of Tables Table 1 Types of data to be collected, generated, or reused ............................................................................. 8 Table 2 Potenal data use cases ........................................................................................................................ 9 Table 3 Data management responsibilies per WP ......................................................................................... 13 Table 4 List of data stewards from each organizaon ...................................................................................... 14 Table 5 Preservaon strategies ........................................................................................................................ 15 Funded by the European Union 4 Document History PROJECT ACRONYM HURRICANE Project Title Holisc UGV-based Resilient and Real-me Intelligence for Crisis And Natural Emergency Grant Agreement Nº 101168017 Project Duraon 01/01/2025 – 31/12/2028 (48 Months) Work Package WP 1 DoA This deliverable refers to Task 1.5 Deliverable No. D1.3 Due date 06/30/2025 Submission date 08/29/2025 Disseminaon SE Deliverable Lead EURAC Author name(s): Ekaterina Chuprikova Status 1.0 Date Version Author Comment 02/04/2025 0.1 Ekaterina Chuprikova (EURAC) First version 02/19/2025 0.2 Ekaterina Chuprikova (EURAC) Internal iteraon 02/25/2025 0.3 Ekaterina Chuprikova (EURAC) Internal iteraon 03/07/2025 0.4 Ekaterina Chuprikova ( EURAC) Internal iteraon 03/13/2025 0.5 Ekaterina Chuprikova (EURAC) Internal iteraon 05/30/2025 0.6 Ekaterina Chuprikova ( EURAC) Internal iteraon 06/20/2025 0.7 Ekaterina Chuprikova (EURAC) Internal iteraon 06/20/2025 0.8 Ekaterina Chuprikova ( EURAC) Internal iteraon 06/23/2025 0.9 Lucia Paladino (EURAC) Review 08/29/2025 1.0 Abraham MEJIA-AGUILAR (EURAC) Final version Funded by the European Union 5 Disclaimer Funded by the European Union under the Horizon Europe Framework Programme Grant Agreement Nº: 101182176. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or of the European Research Execuve Agency. Neither the European Union nor the granng authority can be held responsible for them. List of Parcipants Parcipant No. Parcipant legal name Short Name Type Country 1 (Coord.) Academia Europea di Bolzano EURAC RTO IT 2 Robotnik Automaon SL ROB SME SP 3 MAVTech s.r.l. MAV SME IT 4 Instuto de Engenharia de Sistemas e Computadores, Tecnologia E Ciência INESC TEC RTO PT 5 Centre Technologique ALPhANOV ALPhA RTO FR 6 University of Twente UTwente ACA NTHDS 7 Universidad Complutense de Madrid UCM ACA SP 8 XLIM Research Instute - CNRS UMR N°7252 XLIM ACA FR 9 MidGard SAS MidGard SME FR 10 Blue Tensor s.r.l. BlueTensor SME IT 11 University of Žilina UNIZA ACA SK 12 TIMELEX BV TLX SME BE 13 Service d’incendie et de secours de Haute Corse SIS2B First R. FR 14 Agencia de Seguridad y Gesón Integral de Emergencia - INFOCA EMA-INFOCA First R. SP 15 Ayuntamiento de Almuñecar ALMU Authority SP 1. Execuve Summary HURRICANE will unlock the potenal of UGV operaon in hazardous environment, relying on enhanced vision capabilies and smart integraon over a holisc, resilient and real-me situaonal awareness infrastructure that includes innovave UAV-UGV cooperaon pathways and mul-technology communicaon infrastructure. Data-driven opmizaon models will provide recommendaons through a user-friendly API to support first responders’ taccs. Three complementary pilots will be implemented to demonstrate the benefits brought by HURRICANE soluons. Last, but not least, EU-wide training modules will be implemented to raise awareness among first responders about these innovave technologies, integrang new operaonal procedures. Funded by the European Union 6 2. Acronyms AI Arficial Intelligence COTS Commercial Off-The-Shelf D&E&C Disseminaon, Exploitaon, Communicaon FR First Responders FSO Free Space Opcs KER Key Exploitable Results KET Key Enabling Technology KIP Key Impact Pathway KPI Key Performance Indicators KSO Key Strategic Orientaons IPR Intellectual Property Rights LoS Line of Sight OWC Opcal Wireless Communicaons QoS Quality of Service P/M Persons/months SO Specific Objecve SoA State-of-the-Art UAV Unmanned Aerial Vehicle UGV Unmanned Ground Vehicle UxV Unmanned Vehicle WP Work packages WPT Wireless Power Transfer Funded by the European Union 7 3. Introducon 3.1 Brief descripon of the project and its objecves Programme: Disaster-Resilient Society 2023 Call: Robocs: Autonomous or semi-autonomous UGV systems to supplement skills for use in hazardous environments (HORIZON-CL3-2023-DRS-01-05) HURRICANE’s vision is the establishment of UGV systems – and, in a broader sense, autonomous systems - as a standard for first responders’ (FR) operations. Thanks to enhanced sensing capabilities, UGV will provide high quality ground data to be sent to the command station, relying on an innovative communication infrastructure that involves strong cooperation with UAV. This will allow a cutting-edge real-time situational awareness that will feed data optimization models which will generate reliable recommendations to first responders. 3.2 Purpose of the DMP and how it aligns with Horizon Europe's Open Science policy The DMP aligns with Horizon Europe's Open Science policy, which emphasizes open access, transparency, and the reusability of research outputs while ensuring data privacy and security where necessary. To support these principles, the project commits to open access and FAIR data by making research outputs available through repositories such as ZENODO or the European Open Science Cloud (EOSC), ensuring that metadata and non-sensitive datasets are openly shared to maximize their impact within the scientific community. Furthermore, the DMP facilitates structured data sharing among consortium members, emergency response agencies, and research institutions, promoting collaboration and interoperability across different stakeholders. 4. Data Summary Table 1 integrates the previously defined data categories with their origins. It shows that most data are derived from observaonal sources (real-me sensor outputs and stakeholder feedback) and experimental setups (controlled tests and pilot demonstraons). In addion, simulaon-based and third-party data (e.g., satellite imagery) complement the project datasets, supporng robust analysis and decision-making across various work packages. Funded by the European Union 8 Data Data Type Formats WP Sensivity Origin Sensor & Imagery Data High-resoluon video and sll images (RGB, thermal, NIR), dehazed images, LIDAR readings, and other sensor logs JPEG, PNG, RAW video files, CSV/Binary sensor logs WP2 – Enhanced UGV Sensing High (missioncrical, operaonal) Experimental / Observaonal Geospaal & Mapping Data 2D/3D maps, Digital Surface Models, mulspectral maps generated from combined UGV/UAV data GeoTIFF, PNG Shapefiles, other GIS formats WP2/WP3 – Sensing & Navigaon Medium (open or public formats) Experimental / Observaonal Communicaon & Telemetry Data Real-me communicaon logs (RF/opcal), telemetry data (posioning, navigaon, performance metrics), signal quality (SNR, latency) CSV, JSON, XML, proprietary sensor logs WP4 – Resilient Communicaon Infrastructure High (security and operaonal details) Experimental / Observaonal Remote Sensing & Satellite Data SAR imagery, opcal imagery, and weather/environmental data from satellite systems (e.g., Copernicus) GeoTIFF, NetCDF, HDF WP5 – Datadriven Opmizaon Models Medium (mostly public sources) Third-Party Experimental & Pilot Demonstraon Data Field test measurements, environmental condion records, operaonal performance metrics, and pilot demonstraon reports CSV, Excel, sensor logs, PDF reports WP7 – Demonstrators High (proprietary pilot data) Experimental Stakeholder & User-Generated Data Survey responses, interview transcripts, workshop feedback, and consultaon outcomes Text documents, audio recordings, spreadsheets WP1/DEC – Stakeholder Engagement & Management High (personal and sensive informaon) Observaonal Modeling & Simulaon Data Training datasets, simulaon outputs, hazard predicon models, and opmizaon model outputs CSV, HDF5, pickle files, MATLAB formats WP5 – Opmizaon Models & Visualizaon Tools Medium (internal use, modeling data) SimulaonBased Table 1 Types of data to be collected, generated, or reused The sensivity column indicates:  Confidenality: How private or crical the data is.  Protecon Requirements: The level of security measures needed. Funded by the European Union 9 4.1 Risk: The potential impact if the data is improperly disclosed. Potenal use cases for the data Table 2 outlines key potenal use cases for the collected data. It highlights how data from various sources— such as sensor imagery, geospaal maps, and simulaon outputs—can be integrated to enhance real-me situaonal awareness, support autonomous navigaon, inform emergency decision support systems, forecast hazards, monitor communicaon resilience, and develop training simulaons for first responders. Each use case idenfies the relevant data types and describes the benefits, including improved response mes, enhanced safety, and proacve disaster management. Use case Descripon Relevant Data Types Benefits Real-Time Situaonal Awareness Integraon of mul- sensor data (video, thermal, LIDAR, etc.) to build a live operaonal picture Sensor & Imagery, Communicaon & Telemetry, Geospaal Data Enhanced decision-making and rapid response Autonomous Navigaon & Obstacle Avoidance Use of sensor fusion and mapping data to support UGV/UAV navigaon in complex, hazardous terrains Sensor & Imagery, Geospaal Data Improved mobility and safety in emergency environments Emergency Decision Support Data-driven opmizaon models that translate raw data into aconable recommendaons Modeling & Simulaon, Experimental Data, Remote Sensing Timely guidance for resource deployment and hazard migaon Hazard Predicon & Forecasng Predicve models using simulaon and remote sensing data for forecasng events like fires or structural damage Simulaon Data, Remote Sensing Data Proacve disaster planning and risk reducon Communicaon Resilience Monitoring Real-me monitoring of communicaon channels to ensure robust connecvity during crises Communicaon & Telemetry Data Sustained connecvity and operaonal reliability Training & Simulaon for First Responders Using real-world data to develop virtual training scenarios and simulaons for first responders Experimental Data, Stakeholder & UserGenerated Data, Simulaon Data Improved preparedness and skill development Table 2 Potential data use cases Funded by the European Union 16 9. Legal and ethical requirements, codes of conduct The HURRICANE project embeds rigorous compliance and legal consideraons within its data management plan to ensure that all project acvies meet current and evolving regulatory standards. The project will conduct a comprehensive legal assessment focusing on EU data protecon regulaons such as GDPR, alongside emerging frameworks like the AI Act, to safeguard personal and operaonal data. This involves ensuring data integrity, quality, and traceability through robust data governance pracces, as well as implemenng cybersecurity measures to protect against unauthorized access and cyber threats. Addionally, the legal framework will address cross-border data transfers and the interplay between UGV-UAV systems and exisng communicaon infrastructures, ensuring that all technologies and data sharing pracces comply with naonal and internaonal standards. These measures, combined with ongoing consultaons with legal and ethical experts, guarantee that Hurricane’s innovave soluons uphold civil liberes and promote trust among stakeholders while fostering a harmonized regulatory environment across the EU. 10. Intellectual Property Rights The HURRICANE project priorizes clear and fair Intellectual Property Rights (IPR) arrangements to support innovaon, ensure transparency, and enable effecve collaboraon. These arrangements align with the Grant Agreement and are governed by the Consorum Agreement (CA), which defines the management of background and foreground knowledge, access rights, and licensing terms.  Primary data—collected or produced during project acvies—will be co-owned by the consorum but retain the intellectual authorship of the individuals who generated them. These contributors must be credited in any reuse or publicaon. They also have the right to be consulted before external data sharing, especially before the official public release, to ensure ethical use and maintain internal trust.  Secondary data—exisng or externally sourced data—remain the sole property of the original provider. Their use is subject to exisng licenses or agreements. However, if secondary data are processed (e.g., via modeling or machine learning) to create new datasets, these will be treated as new project outputs and fall under the same co-ownership and authorship rules as primary data.  Access to primary and derived data will be granted under fair and reasonable condions, following Open Science principles while respecng contributor's rights. Any external data sharing will comply with the project’s Open Access policy (e.g., using CC-BY licenses), with clear credit and citaon requirements.  Collaborave outputs will be jointly owned, with a Joint Ownership Agreement (JOA) defining terms for use, licensing, revenue sharing, and access. All IPR policies in HURRICANE adhere to FAIR principles, striking a balance between openness, proper aribuon, legal clarity, and long-term data sustainability.