Integration of data life cycle, architectures and standards for complex data cycles and/or human factors, language (AI, data and robotics partnership) (RIA) -

Expected Outcome

Projects are expected to contribute to the following outcomes:

• ability to process vast volumes data as one of the key enablers for other technological developments, supporting the competitiveness of the EU’s industrial ecosystems;
• successful deployment of data spaces involving several sectors of economy or society;
• improve data access (in line with the FAIR[1] principles), data sovereignty, data interoperability and data protection as an essential factor in the development of sustainable value chains respecting all stakeholder interests, particularly SMEs, but also the public sector as data providers and innovation/market ecosystem enablers. The European Strategy for Data[2] calls for actions to support and promote data sharing and the use of data for social and economic benefit.

Scope

Proposals should address the entire data life cycle from data generation/collection to the final use and disposal/deletion of data (especially when required by applicable legislation, for example the General Data Protection Regulation (GDPR)[3]. Proposals should build on existing and emerging standards, models and architectures and complement/expand them as necessary in view of interoperability of systems and portability of data, especially between sectors, between private and public sectors and between different communities/constituencies of actors, including consideration of cybersecurity issues and analysing the use and re-use potential, especially in view of use of data across sectors. Envisaged architectures and systems should enable correct allocation and enforcement of data-related rights, obligations and responsibilities across the life cycle. Proposals should address relevant human language issues at all stages of data life cycle, addressing the social and cultural factors as necessary. Systems and approaches should be able to process human-generated and human-related data (e.g. speech, text, images) and put data into context (including cultural, linguistic and social context). Likewise, the seamless integration of “human in the loop” (whenever full automation is not possible/desirable) should be considered and implemented where applicable. To achieve this, proposals should consider multidisciplinary research and involve all necessary competences in the consortium.

Proposed actions should build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms. Based on an analysis of cross-fertilisation potential of data re-use, the proposal should include use cases or pilots addressing or involving at least three different common European Data spaces and/or related ecosystems. In particular, they should create links with the Data Spaces support centre funded under the Digital Europe programme, and work in close collaboration with the emerging Common European data spaces in order to ensure interoperability and coordination of data architectures. Proposals should build on existing standards or contribute to standardisation. Interoperability for data sharing should be addressed, in line with the European Interoperability Framework (EIF), and contributing to open, standardized and trusted federated concepts, enabling cross-domain data sharing and data markets.

This topic implements the co-programmed European Partnership on AI, data and robotics.

Activities are expected to start at TRL 2-3 and achieve TRL 4-5 by the end of the project – see General Annex B

[1] FAIR = Findable, Accessible, Interoperable, Re-usable

[2]https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020DC0066

[3]https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32016R0679

News flashes