{"type": "FeatureCollection", "features": [{"id": "10.1007/s11368-022-03203-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:15:40Z", "type": "Journal Article", "created": "2022-04-23", "title": "Improving the design and implementation of sediment fingerprinting studies: summary and outcomes of the TRACING 2021 Scientific School", "description": "Identifying best practices for sediment fingerprinting or tracing is important to allow the quantification of sediment contributions from catchment sources. Although sediment fingerprinting has been applied with reasonable success, the deployment of this method remains associated with many issues and limitations.Seminars and debates were organised during a 4-day Thematic School in October 2021 to come up with concrete suggestions to improve the design and implementation of tracing methods.First, we suggest a better use of geomorphological information to improve study design. Researchers are invited to scrutinise all the knowledge available on the catchment of interest, and to obtain multiple lines of evidence regarding sediment source contributions. Second, we think that scientific knowledge could be improved with local knowledge and we propose a scale of participation describing different levels of involvement of locals in research. Third, we recommend the use of state-of-the-art sediment tracing protocols to conduct sampling, deal with particle size, and examine data before modelling and accounting for the hydro-meteorological context under investigation. Fourth, we promote best practices in modelling, including the importance of running multiple models, selecting appropriate tracers, and reporting on model errors and uncertainty. Fifth, we suggest best practices to share tracing data and samples, which will increase the visibility of the fingerprinting technique in geoscience. Sixth, we suggest that a better formulation of hypotheses could improve our knowledge about erosion and sediment transport processes in a more unified way.With the suggested improvements, sediment fingerprinting, which is interdisciplinary in nature, could play a major role to meet the current and future challenges associated with global change.The online version contains supplementary material available at 10.1007/s11368-022-03203-1.", "keywords": ["[SDE] Environmental Sciences", "DATA", "550", "[SDU.STU.GM] Sciences of the Universe [physics]/Earth Sciences/Geomorphology", "[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study", "01 natural sciences", "333", "source-to-sink", "basin", "local knowledge", "[SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "[SDU.STU.GC] Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "11. Sustainability", "[SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "catchment", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "watershed", "FAIR", "0105 earth and related environmental sciences", "sediment tracing", "ddc:550", "Frontiers in Soils and Sediments \u2022 Research Article", "15. Life on land", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "sediment fingerprinting", "Chemistry", "critical Zone", "13. Climate action", "Earth and Environmental Sciences", "[SDE]Environmental Sciences", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1007/s11368-022-03203-1.pdf"}, {"href": "https://doi.org/10.1007/s11368-022-03203-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Soils%20and%20Sediments", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11368-022-03203-1", "name": "item", "description": "10.1007/s11368-022-03203-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11368-022-03203-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-23T00:00:00Z"}}, {"id": "10.1016/j.dib.2022.108226", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:16:24Z", "type": "Journal Article", "created": "2022-04-29", "title": "Provision of metadata of European agricultural long-term experiments through BonaRes and EJP SOIL collaboration", "description": "Agricultural Long-Term Experiments (LTEs) are crucial agricultural research infrastructures for monitoring the long term effects of management and environment on crop production and soil resources. We have compiled the meta-information of 616 LTEs from 30 different countries across Europe with a duration of typically 20 years, including clustered information of the European LTEs in different categories (management operations, land use, duration, status, etc.). It consists of the updated version of the dataset published by Grosse et\u00a0al., (2020) but is extended by further LTE metadata, categories and research themes. Each set of metadata consists of up to 49 different attributes (categorical or numeric). Collected attributes were analyzed according to several research themes, including fertilization, crop rotation and tillage treatments. The collection of individual metadata was enlarged by the recent agreement between the BonaRes (www.bonares.de) and EJP SOIL (www.ejpsoil.eu) groups into the most comprehensive dataset in Europe, providing access to LTE and other, shorter running experiments. This dataset centralized past and existing information usually dispersed across several national actors. As such, it provides an extensive database that can be used by decision-makers, scientists, LTE owners and the public. The dataset can be updated in the future to foster networking and information exchange continuously.", "keywords": ["[SDV.SA]Life Sciences [q-bio]/Agricultural sciences", "2. Zero hunger", "0301 basic medicine", "[SDV.SA] Life Sciences [q-bio]/Agricultural sciences", "EJP SOIL", "Science (General)", "BonaRes", "Computer applications to medicine. Medical informatics", "R858-859.7", "Agriculture", "04 agricultural and veterinary sciences", "FAIR data principles", "15. Life on land", "630", "Europe", "LTE", "Q1-390", "03 medical and health sciences", "BonaRes ; Long-term experiments ; EJP SOIL ; FAIR data principles ; LTE ; Agriculture ; Europe", "13. Climate action", "Long-term experiments", "0401 agriculture", " forestry", " and fisheries", "BonaRe", "Data Article"]}, "links": [{"href": "https://doi.org/10.1016/j.dib.2022.108226"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Data%20in%20Brief", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.dib.2022.108226", "name": "item", "description": "10.1016/j.dib.2022.108226", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.dib.2022.108226"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-01T00:00:00Z"}}, {"id": "10.1088/1748-9326/adfe83", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:18:58Z", "type": "Journal Article", "created": "2025-09-02", "title": "Mining global soil carbon datasets: can modern machine learning uncover the missing pieces of process-based models?", "description": "Abstract

The future of terrestrial soil carbon stocks plays a crucial role in climate change prediction. Modern machine learning techniques are now widely applied in soil science to predict the spatial distribution of soil properties from observational data. Beyond prediction, the use of machine learning as a data-mining tool offers a promising pathway for improving soil carbon modelling and refining projections of climate\uffe2\uff80\uff93carbon feedbacks. In this paper, we review recent advances in the application of machine learning to global soil carbon modelling as a data-mining tool and highlight its potential to drive an iterative feedback loop that improves the representation of soil carbon dynamics in Earth System Models.

Abstract. Snapshots derived from the World Soil Information Service (WoSIS) are served freely to the international community. These static datasets provide quality-assessed and standardised soil profile data that can be used to support digital soil mapping and environmental applications at broad scale levels. Since the release of the preceding snapshot in 2019, new ETL (Extract, Load, Transform) procedures for screening, ingesting and standardising disparate source data have been developed. In conjunction with this, the WoSIS data model was overhauled making it compatible with the ISO 28258 and Observations and Measurements (O&M) domain models. Additional procedures for querying, serving, and downloading the publicly available standardised data have been implemented using open software (e.g. GraphQL API). Following up on a short discussion of these methodological developments we discuss the structure and content of the \u201cWoSIS 2023-snapshot\u201d. A range of new soil datasets was shared with us, registered in the ISRIC World Data Centre for Soils (WDC-Soils) data repository, and subsequently processed in accordance with the licences specified by the data providers. An important effort has been the processing of forest soil data collated in the framework of the EU-HoliSoils project. We paid special attention to the standardisation of soil property definitions, description of the soil analytical procedures, and standardisation of the units of measurement. The \u201c2023 snapshot\u201d considers the following soil chemical properties (total carbon, organic carbon, inorganic carbon (total carbonate equivalent), total nitrogen, phosphorus (extractable-P, total-P, and P-retention), soil pH, cation exchange capacity, and electrical conductivity) and physical properties (soil texture (sand, silt, and clay), bulk density, coarse fragments, and water retention), grouped according to analytical procedures that are operationally comparable. Method options are defined for each analytical procedure (e.g. pH measured in water, KCl or CaCl2 solution, molarity of the solution, and soil/solution ratio). For each profile we also provide the original soil classification (i.e. FAO, WRB and USDA system with their version) and pedological horizon designations as far as these have been specified in the source databases. Three measures for \u201cfitness-for-intended-use\u201d are provided to facilitate informed data use: a) positional uncertainty of the profile\u2019s site location, b) possible uncertainty associated with the operationally defined analytical procedures, and c) date of sampling. The most recent (i.e. dynamic) dataset, called wosis_latest, is freely accessible via various webservices. To permit consistent referencing and citation we also provide a static snapshot (in casu, December 2023). This snapshot comprises quality-assessed and standardised data for 228 k geo-referenced profiles. The data come from 174 countries and represent more than 900 k soil layers (or horizons) and over 6 million records. The number of measurements for each soil property vary (greatly) between pro\ufb01les and with depth, this generally depending on the objectives of the initial soil sampling programmes. In the coming years, we aim to gradually fill gaps in the geographic distribution of the profiles, as well as in the soil observations themselves, this subject to the sharing of a wider selection of \u201cpublic\u201d soil data by prospective data contributors. The WoSIS 2023-snapshot is archived and freely available at https://doi.org/10.17027/isric-wdcsoils-20231130 (Calisto et al., 2023).

", "keywords": ["Environmental sciences", "QE1-996.5", "13. Climate action", "GE1-350", "Geology", "FAIR data principles", "15. Life on land", "global", "database", "6. Clean water", "soil"]}, "links": [{"href": "https://doi.org/10.5194/essd-16-4735-2024"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-16-4735-2024", "name": "item", "description": "10.5194/essd-16-4735-2024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-16-4735-2024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-27T00:00:00Z"}}, {"id": "10.5194/essd-2024-14", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:22:48Z", "type": "Journal Article", "created": "2024-03-27", "title": "Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023)", "description": "

Abstract. Snapshots derived from the World Soil Information Service (WoSIS) are served freely to the international community. These static datasets provide quality-assessed and standardised soil profile data that can be used to support digital soil mapping and environmental applications at broad scale levels. Since the release of the preceding snapshot in 2019, new ETL (Extract, Load, Transform) procedures for screening, ingesting and standardising disparate source data have been developed. In conjunction with this, the WoSIS data model was overhauled making it compatible with the ISO 28258 and Observations and Measurements (O&M) domain models. Additional procedures for querying, serving, and downloading the publicly available standardised data have been implemented using open software (e.g. GraphQL API). Following up on a short discussion of these methodological developments we discuss the structure and content of the \u201cWoSIS 2023-snapshot\u201d. A range of new soil datasets was shared with us, registered in the ISRIC World Data Centre for Soils (WDC-Soils) data repository, and subsequently processed in accordance with the licences specified by the data providers. An important effort has been the processing of forest soil data collated in the framework of the EU-HoliSoils project. We paid special attention to the standardisation of soil property definitions, description of the soil analytical procedures, and standardisation of the units of measurement. The \u201c2023 snapshot\u201d considers the following soil chemical properties (total carbon, organic carbon, inorganic carbon (total carbonate equivalent), total nitrogen, phosphorus (extractable-P, total-P, and P-retention), soil pH, cation exchange capacity, and electrical conductivity) and physical properties (soil texture (sand, silt, and clay), bulk density, coarse fragments, and water retention), grouped according to analytical procedures that are operationally comparable. Method options are defined for each analytical procedure (e.g. pH measured in water, KCl or CaCl2 solution, molarity of the solution, and soil/solution ratio). For each profile we also provide the original soil classification (i.e. FAO, WRB and USDA system with their version) and pedological horizon designations as far as these have been specified in the source databases. Three measures for \u201cfitness-for-intended-use\u201d are provided to facilitate informed data use: a) positional uncertainty of the profile\u2019s site location, b) possible uncertainty associated with the operationally defined analytical procedures, and c) date of sampling. The most recent (i.e. dynamic) dataset, called wosis_latest, is freely accessible via various webservices. To permit consistent referencing and citation we also provide a static snapshot (in casu, December 2023). This snapshot comprises quality-assessed and standardised data for 228 k geo-referenced profiles. The data come from 174 countries and represent more than 900 k soil layers (or horizons) and over 6 million records. The number of measurements for each soil property vary (greatly) between pro\ufb01les and with depth, this generally depending on the objectives of the initial soil sampling programmes. In the coming years, we aim to gradually fill gaps in the geographic distribution of the profiles, as well as in the soil observations themselves, this subject to the sharing of a wider selection of \u201cpublic\u201d soil data by prospective data contributors. The WoSIS 2023-snapshot is archived and freely available at https://doi.org/10.17027/isric-wdcsoils-20231130 (Calisto et al., 2023).

", "keywords": ["Environmental sciences", "QE1-996.5", "13. Climate action", "GE1-350", "Geology", "FAIR data principles", "15. Life on land", "global", "database", "6. Clean water", "soil"]}, "links": [{"href": "https://doi.org/10.5194/essd-2024-14"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-2024-14", "name": "item", "description": "10.5194/essd-2024-14", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-2024-14"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-27T00:00:00Z"}}, {"id": "10.5281/zenodo.13972269", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:23:30Z", "type": "Report", "created": "2024-10-22", "title": "Soil Data Assimilation Guidance", "description": "The Soil Data Assimiliation Guidance wiki is a collaborative effort to collect and describe hands-on good practices on data assimilation in the soil domain, with a focus on Europe. The term Soil data assimilation\u00a0has been chosen by the autors as an alternative to the terms harmonisation and standardisation, which already have a specific meaning in the soil domain: standardisation; aligning soil data to a common model, using common codelists. harmonisation; transforming results from observations and measurements to values as if all results for a property are measured using the same procedure, by applying so called Pedotransfer Functions (PTF). The process of assimilation also aims to capture additional aspects, such as finding, downloading and using the data. Most of these aspects are also well described as part of the\u00a0FAIR principles. The \u201cInfrastructure for Spatial Information in the European Community\u201d (INSPIRE) directive has been and is an important effort for standardisation in the environmental data domain, therefore this wiki has many links to INSPIRE sources. Because INSPIRE adopts industry standards, this wiki does reference common standards from ISO (International Organization for Standardization), Open Geospatial Consortium, Global Soils Partnership, IANA (Internet Assigned Numbers Authority) and W3C (World Wide Web Consortium), giving it a global relevance. This guide was initiatied by ISRIC - World Soil Information and Wageningen Environmental Research as part of the European Joint Program on Soil (EJP Soil) with funding from the European Union\u2019s horizon 2020 research and innovation programme under grant agreement No. 862695.", "keywords": ["EJP Soil", "Data processing", "Soil sciences", "OGC", "INSPIRE", "FAIR", "Data science"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13972269"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13972269", "name": "item", "description": "10.5281/zenodo.13972269", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13972269"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-04-22T00:00:00Z"}}, {"id": "10.5281/zenodo.13972270", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:23:30Z", "type": "Report", "created": "2024-10-22", "title": "Soil Data Assimilation Guidance", "description": "The Soil Data Assimiliation Guidance wiki is a collaborative effort to collect and describe hands-on good practices on data assimilation in the soil domain, with a focus on Europe. The term Soil data assimilation\u00a0has been chosen by the autors as an alternative to the terms harmonisation and standardisation, which already have a specific meaning in the soil domain: standardisation; aligning soil data to a common model, using common codelists. harmonisation; transforming results from observations and measurements to values as if all results for a property are measured using the same procedure, by applying so called Pedotransfer Functions (PTF). The process of assimilation also aims to capture additional aspects, such as finding, downloading and using the data. Most of these aspects are also well described as part of the\u00a0FAIR principles. The \u201cInfrastructure for Spatial Information in the European Community\u201d (INSPIRE) directive has been and is an important effort for standardisation in the environmental data domain, therefore this wiki has many links to INSPIRE sources. Because INSPIRE adopts industry standards, this wiki does reference common standards from ISO (International Organization for Standardization), Open Geospatial Consortium, Global Soils Partnership, IANA (Internet Assigned Numbers Authority) and W3C (World Wide Web Consortium), giving it a global relevance. This guide was initiatied by ISRIC - World Soil Information and Wageningen Environmental Research as part of the European Joint Program on Soil (EJP Soil) with funding from the European Union\u2019s horizon 2020 research and innovation programme under grant agreement No. 862695.", "keywords": ["EJP Soil", "Data processing", "Soil sciences", "OGC", "INSPIRE", "FAIR", "Data science"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13972270"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13972270", "name": "item", "description": "10.5281/zenodo.13972270", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13972270"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-04-22T00:00:00Z"}}, {"id": "10.5281/zenodo.14224365", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:23:40Z", "type": "Report", "title": "Data management plan", "description": "This Data Management Plan (DMP) will contribute to the management of research data collected or generated in the course of InBestSoil work and how these data is going to be stored, published, cited and made FAIR (findable, accessible, interoperable and reusable) beyond the project life. Our goal is to meet the requirements of excellent scientific practice and to allow for accessibility, interoperability, reproducibility of InBestSoil research results. This DMP also aims to contribute to the development of the European Soil Observatory (EUSO). To ensure that relevant knowledge and project outputs (including data) are fed to the EUSO, datasets of relevance to the EUSO have been identified", "keywords": ["interoperable data", "FAIR data", "reproducible data", "findable data", "accessible data", "Data Management"], "contacts": [{"organization": "Fern\u00e1ndez-Calvi\u00f1o, David, Zornoza, Raul,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14224365"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14224365", "name": "item", "description": "10.5281/zenodo.14224365", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14224365"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-11-26T00:00:00Z"}}, {"id": "10.5281/zenodo.15102057", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:23:57Z", "type": "Report", "title": "Unlocking data for MRV: Data sharing for effective carbon farming", "description": "Building on insights from Credible Focus Group 3.4 (FG 3.4) discussions, we emphasize the critical role of long-term monitoring (LTM) data in i) calibration, validation, and simplification of models, ii) validation of MRV approach, iii) upscaling results from local to regional level, and iv) support for digitalization. One major challenge highlighted in our earlier analysis was the limited access to open data and the lack of effective data-sharing mechanisms. Similar issues were observed from the 1st European Carbon Farming Summit (ECFS) that soil databases are not shared. This highlights the urgent need for greater inter-sector transparency and collaboration. During the 2nd European Carbon Farming Summit, we expanded the scope of discussion beyond LTM data to include both public and private datasets. The key messages from this report are: Robust data collection and sharing across the value chain are essential for accurate MRV in carbon farming. LTM data is invaluable for model calibration and MRV validation, yet greater trust and clear incentives are needed to encourage data sharing between the public and private sectors. \u201cCollect once, use many times\u201d principles can reduce the reporting burden on farmers and streamline compliance with multiple purposes. User-friendly digital tools and data-sharing platforms\u2014supported by clear licensing agreements and federated learning approaches\u2014can balance privacy, competition, and openness.", "keywords": ["FAIR data", "Long-term monitoring", "carbon farming", "Data sharing", "CRCF", "MRV"], "contacts": [{"organization": "Xu, Hui, D'Hose, Tommy, Deroo, Ella, Lanckriet, Edouard, Fantappi\u00e8, Maria, Monhonval, Arthur, Aschonitis, Vassilis, Schulz, Wiebke, Sadowski, Shauna, Ruysschaert, Greet,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15102057"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15102057", "name": "item", "description": "10.5281/zenodo.15102057", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15102057"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-11T00:00:00Z"}}, {"id": "10.5281/zenodo.15404523", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:24:04Z", "type": "Report", "title": "Barriers and incentives for sharing input-data needed in carbon farming and MRV systems in Europe", "description": "An EU-coherent Monitoring, Reporting, and Verification (MRV) system needs the development of agreed rules for data sharing among public and private sectors, together with open access tools and procedures enabling for the standardisation and harmonisation of data. 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Through this DMP, the MARVIC consortium commits to responsible data stewardship, ensuring data longevity and maximizing its potential impact in the scientific community. 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