LiNES Project Data Management Plan

Životní cyklus nových zdrojů energie (LiNES) Horizon Europe Data Management Plan 24 March 2025 Data Management Plan created in FAIR Wizard «fair-wizard.com» using CAS Common DSW Knowledge Model v3.0.3 (053avzc18:CAScommon:3.0.3). HISTORY OF CHANGES Version Publication date Changes There are no named versions 2 / 9 Contributors The following contributors are related to the project of this DMP: Vladimír Církva Czech Academy of Sciences, Institute of Chemical Process Fundamentals (ÚCHP AV ČR) ORCID: {'type': 'PlainType', 'value': '0000-0001-5351-4003'} [email protected] Role: Data Steward • 3 / 9 Acronym: LiNES Project Number: CZ.02.01.01/00/23_020/0008508 Start date: 2024-09-01 End date: 2028-12-31 Funding: Ministerstvo Školství, Mládeže a Tělovýchovy (Czechia) : CZ.02.01.01/00/23_020/0008508 (granted) Projects We will be working on the following project and for those are the data and work described in this DMP. Lifecycle of New Energy Sources, Životní cyklus nových zdrojů energie The project investigates new energy sources (NES) at several levels, from developing innovative technologies for energy storage and preventing risks associated with NSE operation to managing NSE as a source of secondary raw materials. With the expansion of new energy sources in the EU, a scientific problem arises in assessing safety, especially in the medium and long term. The project assesses the risks of NSE to human health and safety, optimizes using these sources, and examines the economic and environmental impacts. It focuses on research into new materials, battery diagnostics, and incident prevention, innovative environmentally friendly processing of NSE, and an overall assessment of the environmental impacts of NSE. 4 / 9 1. Data Summary Data formats and types We will be using the following data formats and types: DOC It is a standardized format. This is a suitable format for long-term archiving. We will have only a small amount of data stored in this format. PDF It is a standardized format. This is a suitable format for long-term archiving. We will have only a small amount of data stored in this format. CSV It is a standardized format. This is a suitable format for long-term archiving. We will have only a small amount of data stored in this format. XLS It is a standardized format. This is a suitable format for long-term archiving. We will have only a small amount of data stored in this format. TIFF It is a standardized format. This is a suitable format for long-term archiving. We will have only a small amount of data stored in this format. MPEG-4 It is a standardized format. This is a suitable format for long-term archiving. We expect to have 500 GB of data in this format. Crystallographic Information Framework (CIF) It is a standardized format. This is a suitable format for long-term archiving. We will have only a small amount of data stored in this format. AVI It is a standardized format. This is a suitable format for long-term archiving. We expect to have 500 GB of data in this format. 2. FAIR Data 2.1. Making data findable, including provisions for metadata a short name, sufficient for yourself to know what data it is about (not published) We will use lab notebooks to make sure that there is good provenance of the data analysis. • • • • • • • • • 5 / 9 We made a SOP (Standard Operating Procedure) for file naming. Everyone in the project will name files and folders according to the abbreviations of the institutions, and the folder structure will also be structured. We will be keeping the relationships between data clear in the file names. All the metadata in the file names also will be available in the proper metadata. 2.2. Making data accessible We will be working with the philosophy as open as possible for our data. The data cannot become completely open because of: legal reasons patent-related business reasons Concerning the legal reasons, a data sharing agreement will be required. People can apply to one of the project members. Limited embargo cannot be used because some restricted data will be embargoed indefinitely. Metadata will be openly available including instructions how to get access to the data. Metadata will available in a form that can be harvested and indexed (managed by the used repository / repositories). We have a consortium agreement that arranges Intellectual Property. For our produced data, conditions are as follows: a short name, sufficient for yourself to know what data it is about (not published) 2.3. Making data interoperable We will be using the following data formats and types: DOC It is a standardized format. PDF It is a standardized format. CSV It is a standardized format. XLS It is a standardized format. TIFF It is a standardized format. MPEG-4 It is a standardized format. Crystallographic Information Framework (CIF) It is a standardized format. • • • • • • • • • • 6 / 9 AVI It is a standardized format. We will be using the following standards (encodings, terminologies, vocabularies, ontologies): 2.4. Increase data re-use The metadata for our produced data will be kept as follows: a short name, sufficient for yourself to know what data it is about (not published) – This data set will be kept available as long as technically possible. – The metadata will be available even when the data no longer exists. As explained in Section 2.2, our data cannot become completely open. Due to privacy reasons, the data must stay in the same institute. We cannot use neither nor , nor to make the data more openly available. There are no IP reasons why our data can not be open. We will be archiving data (using so-called cold storage) for long term preservation already during the project. The data are expected to be still understandable and reusable after a long time. To validate the integrity of the results, the following will be done: We will run a subset of our jobs several times across the different compute infrastructures. 3. Other research outputs We use FAIR Wizard for planning our data management and creating this DMP. The management and planning of other research outputs is done separately and is included as appendix to this DMP. Still, we benefit from data stewardship guidance (e.g. FAIR principles, openness, or security) and it is reflected in our plans with respect to other research outputs. 4. Allocation of resources FAIR is a central part of our data management; it is considered at every decision in our data management plan. We use the FAIR data process ourselves to make our use of the data as efficient as possible. Lifecycle of New Energy Sources, Životní cyklus nových zdrojů energie - CZ.02.01.01/00/23_020/0008508 • • • • • 7 / 9 Following resources will be dedicated to data management and ensuring that data will be FAIR: (no name given) - We will be archiving data (using so-called 'cold storage') for long term preservation after the project but also already during the project. The used data archiving service is budgeted by one or more of the participating institutes. The minimum lifetime of the archive is 10 years. The archival period can be extended – one of the principle investigators involved in the project will decide. The decision whether or not to extend the renewal be based on the actual use of the archived data. Data formats of data in cold storage will be upgraded if they become obsolete. Archived data will be migrated regularly to more modern storage media (e.g. newer tapes). None of the used repositories charge for their services. We have a reserved budget for the time and effort it will take to prepare the data for publication. For making data or other research outputs FAIR, we budgeted: 100 thousand CZK. Vladimír Církva is responsible for the management and proficiency of data including data processing, data policies, data guidelines, and data availability. To execute the DMP, no additional specialist expertise is required. We do not require any hardware or software in addition to what is usually available in the institute. 5. Data security Project members will not carry data with them (e.g. on laptops, USB sticks, or other external media). All data centers where project data is stored carry sufficient certifications. All project web services are addressed via secure HTTP (https://...). Project members have been instructed about both generic and specific risks to the project. The possible impact to the project or organization if information is lost is small. The possible impact to the project or organization if information is leaked is small. The possible impact to the project or organization if information is vandalised is small. We are not using any personal information. The archive will be stored in a remote location to protect the data against disasters. The archive need to be protected against loss or theft. It is clear who has physical access to the archives. We are running the project in a collaboration between different groups and institutes. A collaboration agreement that describes who can have access to what data in the project is set. ◦ 8 / 9 6. Ethics Data we produce For the data we produce, the ethical aspects are as follows: a short name, sufficient for yourself to know what data it is about It does not contain personal data. It does not contain sensitive data. Data we collect We will not collect any data connected to a person, i.e. "personal data". The data collection is not subject to ethical legislation. 7. Other issues We use the FAIR Wizard with its CAS Common DSW Knowledge Model (ID: 053avzc18:CAScommon:3.0.3) knowledge model to make our DMP. More specifically, we use the https://avcr.fair-wizard.com/wizard FAIR Wizard instance where the project has direct URL: https://avcr.fair-wizard.com/wizard/projects/8b05055ba4c7-4fbe-95d7-59fdacf76e96. We will not be using any extra national, funder, sectorial, nor departmental policies or procedures for data management. • ◦ ◦ 9 / 9