MultiMiner Project Deliverable No 5.4 - Data Management Plan V1.9

The Multi-source and Multi-scale Earth observation and Novel Machine Learning Methods for Mineral Exploration and Mine Site Monitoring (MultiMiner) project develops novel data processing algorithms for cost-effective utilization of Earth Observation (EO) technologies for mineral exploration and mine site monitoring. The project focuses on new EO-based exploration technologies for critical raw materials (CRM) to increase the probability of finding new sources within EU thereby strengthening the EU autonomy in the area of raw materials.

The importance of good data management practices is emphasized in data-intensive projects such as MultiMiner. During the project, large and heterogenous datasets will be acquired and analyzed. The project comprises data acquired in different scales and by different technologies. The number of the consortium partners (13) highlights the importance of data harmonization, i.e. efforts to collect and distribute data using collectively agreed methods, formats and metadata descriptions.

MultiMiner generates and collects a range of data types, most of which are instrument data. Examples of such data include, but are not limited to, point spectral data, radar satellite data and laboratory-collected hyperspectral image data. These data are stored in internationally accepted file formats for their effective sharing, re-use, and preservation. The total estimated size of the data is in the order of terabytes. MultiMiner is reusing publicly available satellite data (e.g. EnMAP, Sentinel) and existing field data from participating test sites. Should any personal data be collected during the project (e.g., stakeholder surveys), all such data are stored in line with the requirements of the General Data Protection Regulation (GDPR).

By default, all data, software and algorithms needed to reproduce and facilitate the reuse of the results of MultiMiner are made publicly available using Zenodo and GitHub. These are repositories that provide persistent identifiers (e.g., DOIs), generate formal citations and whose metadata and data are registered and searchable by search engines to ensure the findability of the data. The MultiMiner consortium shares any data as soon as possible and usually immediately after the data production and quality controls. Here, we follow the principle “as open as possible, as closed as necessary” and should the immediate release of the data be delayed, or the data restricted e.g., due to IP considerations, it is always ensured that the metadata of the data are immediately and publicly available. Only such trusted data repositories are used to share data which provide harvestable and public machine-accessible interfaces to metadata, data files, dataset terms, licenses and version information, making the data findable and accessible.

When possible, all data are prepared such as to include qualified references to other data, maximizing the interoperability of the data. Data are carefully documented at all project phases (data acquisition, data analysis, data sharing) and metadata are compiled using such broad cross-domain and domain-specific metadata schemas (e.g., DataCite, Dublin Core, ISO 19115) and controlled vocabularies (e.g., ISO 3166) which maximize the reusability and interoperability of the data. The metadata of the data always include a detailed provenance, thus including such items as the names of the authors, in addition to information about how the data was collected and processed. By default, MultiMiner shares all its data using clear and permissive licenses to maximize data reusability. By default, all metadata and data are shared using the Creative Commons Public Domain Dedication CC0 and software, algorithms and apps generated in the project are shared using permissive software licenses such as the MIT license. Access to physical samples is given upon request and at the same time as the associated data, following the same principles of openness. Only if data sharing is against the beneficiary’s legitimate interests, including, but not limited to, commercial exploitation of the research outputs, or if the consortium is reusing data already shared by other organizations (e.g., the satellite data) data is not shared or access to it is restricted. All data is stored in the secure servers of the project partners during the project and a minimum of 10 years after the end of the project. Cloud services that are deemed safe are used to share the data between the said partners.

While the Coordinator takes a leading role in data management, it is the responsibility of the individual partner organizations to ensure that the data they generate in the project is managed in accordance with the DMP and meets appropriate national and international legal and ethical standards. Data management activities are adequately resourced and implemented, and all partners allocate a minimum of 5% of their time for research data management. The DMP is treated as a living document and is updated throughout the project, and we publish its different versions in publishing platforms such as Research Ideas and Outcomes RIO journal. Examples of situations where the DMP would be updated include, but are not limited to: new datasets, changes to data storage or data sharing practices, changes in the level of openness of the data (fully open, partially open or fully closed). A new version of the DMP will be created and shared any time major changes take place.