SciLake Deliverable D1.3: Final integrated system

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.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-31
DOI
https://doi.org/10.5281/zenodo.19631440
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SciLake Deliverable D1.3: Final integrated system

Miriam Baglioni, Marek Horst, Thanasis Vergoulis, Nikolay Yakovets et al.
Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

SciLake Deliverable D1.3: Final integrated system

Miriam Baglioni, Marek Horst, Thanasis Vergoulis, Nikolay Yakovets, César Parra Rojas
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" (IT), Athena Research and Innovation Center In Information Communication & Knowledge Technologies (GR), University of Warsaw (PL), Eindhoven University of Technology (NL), Sirris (BE)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Research Data Management Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.