Glossary
| Term | Description | Note |
| Anonymous data | Information which does not relate to an identified or identifiable natural person or to personal data rendered anonymous in such a manner that the data subject is not or no longer identifiable. | General Data Protection Regulation (GDPR) 2016/679 |
| Data | Any digital representation of acts, facts or information and any compilation of such acts, facts or information, including in the form of sound, visual or audiovisual recording. | Data Governance Act (DGA): Regulation 2022/868 |
| Data access | Data use, in accordance with specific technical, legal or organisational requirements, without necessarily implying the transmission or downloading of data. | Data Governance Act (DGA): Regulation 2022/868 |
| Data altruism | The voluntary sharing of data on the basis of the consent of data subjects to process personal data pertaining to them, or permissions of data holders to allow the use of their non-personal data without seeking or receiving a reward that goes beyond compensation related to the costs that they incur where they make their data available for objectives of general interest as provided for in national law, where applicable, such as healthcare, combating climate change, improving mobility, facilitating the development, production and dissemination of official statistics, improving the provision of public services, public policy making or scientific research purposes in the general interest. | Data Governance Act (DGA): Regulation 2022/868 |
| Data controller | The natural or legal person, public authority, agency or other body which, alone or jointly with others, determines the purposes and means of the processing of personal data. | General Data Protection Regulation (GDPR) 2016/679 |
| Data cooperatives | Data intermediation services offered by an organisational structure constituted by data subjects, one-person undertakings or SMEs who are members of that structure, having as its main objectives to support its members in the exercise of their rights with respect to certain data, including with regard to making informed choices before they consent to data processing, to exchange views on data processing purposes and conditions that would best represent the interests of its members in relation to their data, and to negotiate terms and conditions for data processing on behalf of its members before giving permission to the processing of non-personal data or before they consent to the processing of personal data. | Data Governance Act (DGA): Regulation 2022/868 |
| Data ecosystem | A system of co-dependent networks and actors that contribute to data collection, transfer and use. | Marcelo Iury S. Oliveira; Bernadette Farias Lóscio g.o ’18: Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, May 2018, Article No.: 74, Pages 1–9 |
| Data Holder | ‘A legal person, including public sector bodies and international organisations, or a natural person who is not a data subject with respect to the specific data in question, which, in accordance with applicable Union or national law, has the right to grant access to or to share certain personal data or non-personal data; | Data Governance Act (DGA) |
| Data intermediation service | subjects and data holders on the one hand and data users on the other, through technical, legal or other means, including for the purpose of exercising the rights of data subjects in relation to personal data. | Data Governance Act (DGA): Regulation 2022/868 |
| Data Provider | A transaction participant that, in the context of a specific data transaction, technically provides data to the data recipients that have a right or duty to access and/or receive that data. | DSSC Glossary v2.0 |
| Data recipient | A natural or legal person, public authority, agency or another body, to which the personal data are disclosed, whether a third party or not. | General Data Protection Regulation (GDPR) 2016/679 |
| Data service provider | A natural or legal person who provides data processing services. | Regulation 2018/1807 “Free Flow of Non-Personal Data Regulation” |
| Data sharing | The provision of data by a data subject or a data holder to a data user for the purpose of the joint or individual use of such data, based on voluntary agreements or Union or national law, directly or through an intermediary, for example under open or commercial licences subject to a fee or free of charge. | Data Governance Act (DGA): Regulation 2022/868 |
| Data Space | A distributed system defined by a governance framework that enables secure and trustworthy data transactions between participants while supporting trust and data sovereignty. A data space is implemented by one or more infrastructures and enables one or more use cases. | DSSC Glossary v2.0 |
| Data Space Support Centre (DSSC) | The virtual organisation and EU-funded project which supports the deployment of common European data spaces and promotes the reuse of data across sectors. | DSSC Glossary v2.0 |
| Data subject | An identified or identifiable natural person; an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person. | General Data Protection Regulation (GDPR) 2016/679 |
| Data User | A natural or legal person who has lawful access to certain personal or non-personal data and has the right, including under Regulation 2016/679 in the case of personal data, to use that data for commercial or non-commercial purposes. | Data Governance Act (DGA): Regulation 2022/868 Art. 2(9) |
| Digital Ecosystem | A system of systems inspired by the natural ecosystem paradigm for modeling the complex collaborative and competitive social domain dealing with the generation of knowledge from data and information sharing/processing. Also a purposeful collaboration or partnership consuming, producing and providing interoperable data and related resources. | Nativi, S.; Mazzetti, P.; Craglia, M. Digital Ecosystems for Developing Digital Twins of the Earth: The Destination Earth Case. Remote Sens. 2021, 13, 2119., Nativi, S., Mazzetti, P. (2021). Geosciences Digital Ecosystems. In: Daya Sagar, B., Cheng, Q., McKinley, J., Agterberg, F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. and GREAT: D4.1: Phase 1 Governance Requirements and Endorsed Governance Scheme |
| Digital Europe Programme (DEP) | An EU funding programme that funds several data space related projects, among other topics. The programme is focused on bringing digital technology to businesses, citizens and public administrations. | Source: DSSC glossary v 2.0 |
| Data and Information Access Services (DIAS) | The five DIAS online platforms (Creodias, Sobloo, Mundi, Onda and WEkEO) allow users to discover, manipulate, process and download Copernicus data and information. All DIAS platforms provide access to Copernicus Sentinel data, as well as to the information products from the six operational services of Copernicus, together with cloud-based tools (open source and/or on a pay-per-use basis). | European Commission |
| European Strategy for Data | The European strategy for data aims at creating a single market for data that will ensure Europe’s global competitiveness and data sovereignty. Common European data spaces will ensure that more data becomes available for use in the economy and society, while keeping the companies and individuals who generate the data in control. | European Commission |
| FAIR data | FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability | Mark D. Wilkinson; Michel Dumontier; IJsbrand Jan Aalbersberg; et al. (15 March 2016). “The FAIR Guiding Principles for scientific data management and stewardship”. Scientific Data. 3 (1): 160018. doi:10.1038/SDATA.2016.18. ISSN 2052-4463 |
| Governance | Governance is the process for making decisions about an entity: ● Choosing the questions that must be decided, such as the mission and objectives of the entity, the problems to be solved, and the needs to be addressed. ● Agreeing on the “scope” and “boundaries” of the entity, both initially and over time. ● Ensuring compliance of the entity with applicable laws and regulations. ● Deciding who should be involved in decision-making, including both the actual decision process (including activities like voting, etc.), as well as consultation about each decision. ● Decisions include those about the creation of the entity, such as its form and the relationships between and among outside parties with the entity, as well as who should participate in both decision making and governance and in the operation of the entity. ● Managing the decision-making process, recording both results and details about how these results were decided, such as who was consulted. ● Communicating about the governance process — identifying who is involved, what decisions are being considered, what decisions have been made. ● Tracking the decisions made, monitoring compliance with these decisions, enforcing those decisions consistent with processes (which have also been decided through the governance process). ● Measuring and reviewing the performance of the entity against agreed objectives.” |
GREAT: D4.1: Phase 1 Governance Requirements and Endorsed Governance Scheme |
| Horizon Europe (HE) | Horizon Europe is the EU’s key funding programme for research and innovation until 2027 with a budget of €95.5 billion. | European Commission |
| High Value Data sets (HVD) | The European Commission has published a list of high-value datasets that public sector bodies will have to make available for re-use, free of charge. The Open Data Directive, which defines six categories of such high-value datasets: geospatial, earth observation and environment, meteorological, statistics, companies and mobility. This thematic range can be extended at a later stage to reflect technological and market developments. The datasets will be available in machine-readable format, via an Application Programming Interface and, where relevant, as bulk download. | European Commission |
| Key Performance Indicator (KPI) | Key Performance Indicators (KPIs) are the critical (key) quantifiable indicators of progress toward an intended result. KPIs provide a focus for strategic and operational improvement, create an analytical basis for decision making and help focus attention on what matters most. | KPI.org |
| Non-personal data | Data other than personal data. | Data Governance Act (DGA): Regulation 2022/868 |
| Personal data | Any information relating to an identified or identifiable natural person (‘data subject’). | General Data Protection Regulation (GDPR) 2016/679 |
| Personal data processing | Any operation or set of operations which is performed on personal data or on sets of personal data, whether or not by automated means, such as collection, recording, organisation, structuring, storage, adaptation or alteration, retrieval, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, restriction, erasure or destruction. | General Data Protection Regulation (GDPR) 2016/679 |
| Pseudonymised data | The processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person. | General Data Protection Regulation (GDPR) 2016/679 |
| Research Data Management (RDM) | Research data management refers to the handling of research data (collection, organisation, storage, and documentation) during and after a research activity. | Science Europe |
| Special categories personal data (“Sensitive data”) | Personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing of genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a natural person’s sex life or sexual orientation. | General Data Protection Regulation (GDPR) 2016/679 |
| Green Deal Data Space specific terms | ||
| Term | Description | Note |
| Data Space initiative | A collaborative project of a consortium or network of committed partners to deploy and maintain a data space | GREAT: D4.1: Phase 1 Governance Requirements and Endorsed Governance Scheme |
| Data Space participant | A party that has committed to the governance framework of a particular data space and may have one or more roles in it. | DSSC Glossary v2.0 |
| Environmental, social, and governance (ESG) | Environmental, social and governance (ESG) is a framework used to assess an organization’s business practices and performance on various sustainability and ethical issues. It also provides a way to measure business risks and opportunities in those areas. | TechTarget/WhatiIs.com |
| European Green Deal (EGD) | The European Green Deal will transform the EU into a modern, resource-efficient and competitive economy, ensuring: – no net emissions of greenhouse gases by 2050 – economic growth decoupled from resource use – no person and no place left behind |
European Commission |
| European Green Deal Data Space (EGDS) | The common European Green Deal data space will interconnect currently fragmented and dispersed data from various ecosystems, both for/from the private and public sectors, to support the objectives of the European Green Deal. Also Green Deal Data Space (GDDS). | European Commission |
| Global Flood Monitoring (GFM) | GFM is designed to provide a continuous global, systematic monitoring of flood events, with significantly enhanced timeliness of flood maps for emergency response and improved effectiveness of Rapid Mapping activation requests through a better identification of the area of interest. | EODC |
| GREAT project | Short Name to refer to Green Deal Data Space Foundation and its Community of Practice. The GREAT project, funded by the Digital Europe program, aims to establish the Green Deal Data Space Foundation and its Community of Practice which builds on both the European Green Deal and the EU’s Strategy for Data. | GREAT project website |
| Green Deal Data ecosystem | A data ecosystem for addressing the European Green Deal objectives. A collection of data and related resources, provided, produced, and/or used by a community of actors with the purpose of enabling the achievement of the objectives of the European Green Deal. | GREAT: D4.1: Phase 1 Governance Requirements and Endorsed Governance Scheme |
| Green Deal Data Space initiative | A collaborative project of a consortium or network of committed partners to deploy and maintain a data space with the purpose of enabling one or more use cases associated with the European Green Deal | GREAT: D4.1: Phase 1 Governance Requirements and Endorsed Governance Scheme |
| Green Deal Digital ecosystem | A Digital Ecosystem to address the Green Deal objectives. A collaboration or partnership consuming, producing and providing interoperable data and related resources with the purpose of enabling the achievement of the objectives of the European Green Deal. | GREAT: D4.1: Phase 1 Governance Requirements and Endorsed Governance Scheme |
| Green Deal Data Space inventory (GDDSI) | It consists of the High Priority Data Sets and the High Priority Data Services inventories. This inventory holds all high priority data sets and services. | GREAT: D5.1: EGD Prioritised Data Sets and Gaps (Initial Inventory plus Phase 1 Reference Use Cases) |
| Greenhouse gases (GHG) | Gaseous constituents of the atmosphere, both natural and anthropogenic, that absorb and emit radiation at specific wavelengths within the spectrum of radiation emitted by the Earth’s surface, by the atmosphere itself, and by clouds. | IPCC, 2021: Annex VII: Glossary [Matthews, J.B.R., V. Möller, R. van Diemen, J.S. Fuglestvedt, V. Masson-Delmotte, C. Méndez, S. Semenov, A. Reisinger (eds.)]. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L., et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 2215–2256, doi:10.1017/9781009157896.022. |
| High Priority Data Services inventory (HPDServI) | An inventory of services that provide data relevant to the Green Deal with the focus on the three strategic actions that the GREAT project focuses on: 2030 Biodiversity strategy, Zero-pollution Action Plan, Climate Change Adaptation Strategy. The inventory is curated between project partners and prioritised based on the following criteria (as of Phase 1 of the GREAT project): relevance to the Reference Use Cases, relevance to the strategic actions that GREAT focuses on (2030 Biodiversity Strategy, Zero Pollution Action Plan, Climate Change Adaptation Strategy) and their objectives, relevance to EGD initiatives, programmes etc. data offering completeness (spatial and temporal coverage), FAIRness, business models etc. During Phase 2, this inventory will be further populated with relevant data services through the engagement with additional Green Deal stakeholders and initiatives as well as a complementary search by the WP5 team. | GREAT: D5.1: EGD Prioritised Data Sets and Gaps (Initial Inventory plus Phase 1 Reference Use Cases) |
| High Priority Data Sets inventory (HPDSetI) | An inventory of data sets developed based on the analysis of the Phase 1 Reference Use Cases. As of the end of Phase 1, all input data sets listed in this inventory are considered of high priority as they are the ones provided by the Reference Use Cases as required data for achieving their objectives. During Phase 2, this inventory will be further populated with data sets provided by additional use cases and stakeholders as well as a complementary search by the WP5 team. The envisioned structure and organisation of the high priority data set inventory is a comprehensive framework designed to efficiently catalogue, categorise, and manage a large number of data sets relevant to the Green Deal. | GREAT: D5.1: EGD Prioritised Data Sets and Gaps (Initial Inventory plus Phase 1 Reference Use Cases) |
| Large-Scale Hydrology (LSH) | Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. | Nans Addor, Hong X. Do, Camila Alvarez-Garreton, Gemma Coxon, Keirnan Fowler & Pablo A. Mendoza (2020) Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges, Hydrological Sciences Journal, 65:5, 712-725, DOI: 10.1080/02626667.2019.1683182 |
| Reference Use Case (RUC) | Reference Use Case (RUC) – GREAT selected use case, potential user of the GDDS, an organization/stakeholder/project bringing on board its network and example of how the GDDS could support its development and everyday work (e.g., BioGIS, GOS4M, Hydrology modelling, EMODNET, city of Thessaloniki, etc.) | |
| Spatial Decision Support System (SDSS) | A spatial decision support system (SDSS) is an interactive, computer-based system designed to assist in decision making while solving a semi-structured spatial problem. | Wikipedia |
| Stakeholder Forum (SF) | A series of interactive online events addressing a specific Green Deal strategies with the aim to gather and attract the relevant community of stakeholders, to discuss around a specific Case Study the user requirements and challenges, across the 3 main blocks of GREAT: Technical blueprint, High value datasets, Governance and business models.
The goal of the Stakeholder Forum is to contribute to the final endorsement of the Green Deal Data Space vision, which will support the deployment of the Data Space. |
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| Synthetic Aperture Radar (SAR) | Synthetic-aperture radar (SAR) is a form of radar that is used to create two-dimensional images or three-dimensional reconstructions of objects, such as landscapes. | Kirscht, Martin, and Carsten Rinke. “3D Reconstruction of Buildings and Vegetation from Synthetic Aperture Radar (SAR) Images.” MVA. 1998) via Wikipedia |
| Task Force (TF) | A group of domain representatives and experts gathered for a Stakeholder Forum (brought on board by the TF champion and TF leader), contributing to the outlining of the GDDS and validating its vision through their contribution to the SF and if needed, through providing additional inputs and comments after the event.
The Task Force will be formed and led by the TF champion (a person representing the corresponding reference use case) and supported and coordinated by TF leader (a person representing the GREAT project) |
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| Task Force Champion (TFC) | A person representing the corresponding reference use case, forming and leading the thematic | |
| Task Force Leader (TFL) | A person representing the GREAT project (team member) supporting and coordinating the organization and management of the TF | |
| Use Case (UC) | Example of how GDDS can be used, a generic narrative. e.g. for RUC of GOS4M, the use case can be as follows – tracking and monitoring of the air quality, monitoring of the air pollution, proving the achievement of air quality indicators, etc. |