Description du projet
Un lac pour la connaissance scientifique
Tout comme les lacs sont de riches écosystèmes abritant de nombreuses formes de vie telles que des plantes et des poissons, les lacs scientifiques hébergent les métadonnées de divers éléments de recherche (chercheurs, organisations, bailleurs de fonds et installations). Le projet SciLake, financé par l’UE, rassemble 13 partenaires de neuf pays pour bâtir un écosystème conçu pour répondre aux besoins de la communauté des chercheurs dans son ensemble. Plus précisément, il permettra la création de graphes de connaissances scientifiques et universitaires et la mise en œuvre de technologies pour soutenir la science des données et les requêtes d’exploration de graphes. Le projet contribuera également à la démocratisation du contenu scientifique et des services à valeur ajoutée connexes en mettant en œuvre une approche de gestion axée sur la communauté. En offrant des services avancés, assistés par l’IA, qui exploitent des perspectives de valeur scientifique spécifiques à un domaine, SciLake facilitera la navigation dans le vaste espace de la connaissance scientifique.
Objectif
SciLake's mission is to build upon the OpenAIRE ecosystem and EOSC services to (a) facilitate and empower the creation, interlinking and maintenance of Scientific/Scholarly Knowledge Graphs (SKGs) and the execution of data science and graph mining queries on top of them, (b) contribute to the democratization of scholarly content and the related added value services implementing a community-driven management approach, and (c) offer advanced, AI-assisted services that exploit customised perspectives of scientific merit to assist the navigation of the vast scientific knowledge space. In brief, SciLake will develop, support, and offer customisable services to the research community following a two-tier service architecture. First, it will offer a comprehensive, open, transparent, and customisable scientific data-lake-as-a-service (service tier 1), empowering and facilitating the creation, interlinking, and maintenance of SKGs both across and within different scientific disciplines. On top of that, it will build and offer a tier of customisable, AI-assisted services that facilitate the navigation of scholarly content following a scientific merit-driven approach (tier 2), focusing on two merit aspects which are crucial for the research community at large: impact and reproducibility. The services in both tiers will leverage advanced AI techniques (text and graph mining) that are going to exploit and extend existing technologies provided by SciLake's technology partners. Finally, to showcase the value of the provided services and their capability to address current and anticipated needs of different research communities, four scientific domains (neuroscience, cancer research, transportation, and energy) have been selected to serve as pilots. For each, the developed services will be customised, to accommodate differences in research procedures, practices, impact measures and types of research objects, and will be validated and evaluated through real-world use cases.
Champ scientifique
- natural sciencesbiological sciencesneurobiology
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesdata science
- natural sciencescomputer and information sciencesknowledge engineering
- medical and health sciencesclinical medicineoncology
Programme(s)
Régime de financement
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinateur
151 25 Maroussi
Grèce