Project description
Data-centric business models for data lifecycle governance
Integrating data from multiple sources using AI-powered applications can provide organisations with a competitive edge. However, manual data lifecycle governance often results in data silos. There is a need for a systematic mechanism to collect, combine, and process data to develop new data-centric business models. The EU-funded CyclOps project proposes a new framework designed to handle large volumes of data generated from diverse sources to manage and maintain the complete data lifecycle. The project uses knowledge graphs (KGs) to automate the generation and execution of data processing pipelines while incorporating human input. CyclOps aims to enable organisations to easily share, access, and analyse both machine and human-generated data from various data spaces, thereby facilitating the provision of value-added services.
Objective
The ability to integrate data from multiple sources is nowadays a major competitive advantage for organizations. Data-driven applications using AI techniques are reshaping various industries such as manufacturing, tourism, and mobility. The European Strategy for Data aims to create a single market for data while ensuring Europe's global competitiveness and data sovereignty. This has led to the development of Common European data spaces, yet the governance of the data life cycle in organizations has not kept up with the rapid technology evolution and remains largely manual. This is especially evident in scenarios where tens or hundreds of continuously evolving data sources produce semi-structured data, and create significant challenges when governed manually, causing organizations to end up with data silos. A systematic and standardized mechanism is needed to ingest, integrate, and process data, thus boosting the ability to develop new data-centric business models. However, current research and development efforts typically target one aspect of the end-to-end data lifecycle, such as scalable data management, ML performance, AI explainability, or sharing, while dismissing its governance. To overcome this limitation, CyclOps proposes a new framework for the governance and maintenance of the complete data lifecycle for large-scale volumes of data generated in heterogeneous distributed sources to enable data sharing and exchange. CyclOps intelligently automates, by means of knowledge graphs (KGs) and with a human-in-the-loop approach, the generation and execution of data processing pipelines. KGs are the established formal models to represent data and metadata while providing context and guaranteeing interoperability with other systems adhering to the FAIR Guiding Principles. CyclOps will enable organizations to seamlessly provide, cross and analyze machine- and human-generated data from and for data spaces, thus facilitating the provision of added-value services on top.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
28050 Madrid
Spain
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Participants (26)
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
50002 Zaragoza
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38068 Rovereto
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28760 Tres Cantos Madrid
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
28037 Madrid
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
014459 BUCURESTI
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3013 Limassol
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
10416 TALLINN
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
15231 CHALANDRI
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
39100 BOLZANO
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
10587 Berlin
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1000 Bruxelles / Brussel
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
08034 Barcelona
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4 Dublin
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39100 Bolzano
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08034 Barcelona
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57001 Thermi Thessaloniki
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38106 Braunschweig
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07010 Palma De Mallorca
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
75008 Paris
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28033 PALMA DE MALLORCA
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69007 Lyon
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07300 Inca
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39100 Bolzano
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1030 Wien
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
32200 YPATO BIOTIAS
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
121 32 ATHENS
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.