SciLake introduces an open Scientific Lake concept, featuring customizable components deployed across a federation of machines to create, interlink, and maintain domain-specific, community-managed Scientific Knowledge Graphs (SKGs). This infrastructure provides a unified method for accessing and querying contained assets, enabling the development of value-added services to enhance knowledge discovery, research reproducibility, and other research-related routines. Domain experts can select and tailor components to their specific needs, making the architecture highly customizable. Apart from the Scientific Lake concept, SciLake is also developing two indicative, discipline-tailored, value-added services that are showcasing the value of this concept in practice. The first service is designed to enhance the exploration of a specific scientific domain's knowledge space by leveraging the content of relevant SKGs. The second service focuses on enhancing research reproducibility within specific domains by utilising the contents of SKGs to provide insights on the reproducibility of associated research products. This deliverable report outlines the final version of the integrated SciLake system, its distinctive subsystems consisting of individual components, API interfaces and portals, integrated and deployed at the end of March 2026.
Horst et al. (Tue,) studied this question.