Project description
A lake for scientific knowledge
Just like lakes are rich ecosystems hosting many life forms such as plants and fish, scientific lakes host metadata for various research elements (researchers, organisations, funders and facilities). The EU-funded SciLake project brings together 13 partners from nine countries to build an ecosystem designed to serve the needs of the research community at large. Specifically, it will empower the creation of scientific/scholarly knowledge graphs and the implementation of technologies to support data science and graph mining queries. The project will also contribute to the democratisation of scholarly content and the related added-value services by implementing a community-driven management approach. By offering advanced, AI-assisted services that exploit domain-specific perspectives of scientific merit, SciLake will assist the navigation of the vast scientific knowledge space.
Objective
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.
Fields of science
- 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)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
151 25 Maroussi
Greece