SciLake Deliverable D5.2: Pilot Evaluation Report

This deliverable presents the evaluation of the SciLake knowledge‑management ecosystem across four domain pilots: Energy, Cancer, Neuroscience, and Transportation. The pilots tested SciLake’s ability to generate and enrich domain‑specific Scientific Knowledge Graphs (SKGs) through semantic annotation, entity extraction, citation analysis, and classification services. The evaluation followed a structured methodology combining preparatory pilot setup, component‑level validation and pilot demonstrators assessing end‑to‑end research workflows. Results show that SciLake’s modular architecture effectively supports semantic exploration, structured search, and graph‑based analysis, with high user acceptance and strong performance across key services. The assessment confirms the system’s operational readiness while identifying areas for refinement. Overall, the pilots validate SciLake as a coherent and extensible ecosystem for advanced scientific knowledge discovery.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-31
DOI
https://doi.org/10.5281/zenodo.19347350
Primary Topic
Advanced Graph Neural Networks
Type
article
Field-Weighted Citation Impact
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article

SciLake Deliverable D5.2: Pilot Evaluation Report

Serafeim Chatzopoulos, Trygve B. Leergaard, Sotiris Kotitsas, Anastasia Bolovinou et al.
Zenodo (CERN European Organization for Nuclear Research)
Advanced Graph Neural Networks
article

SciLake Deliverable D5.2: Pilot Evaluation Report

Serafeim Chatzopoulos, Trygve B. Leergaard, Sotiris Kotitsas, Anastasia Bolovinou, Leily Rabbani, Archana Golla, Julián Moreno Schneider, Sokratis Sofianopoulos, Jakob Rager, Thanasis Vergoulis, Afroditi Anagnostopoulou, Pablo Accuosto, Daniel Hägerstrand, Nikolay Yakovets, D. de Graaf, Konstantinos Kardamiliotis, César Parra Rojas, George Gavriilidis, Athanasios Ballis, Salmi Andrea, Fotis Psomopoulos, Xenophon Kitsios
article en

Abstract

This deliverable presents the evaluation of the SciLake knowledge‑management ecosystem across four domain pilots: Energy, Cancer, Neuroscience, and Transportation. The pilots tested SciLake’s ability to generate and enrich domain‑specific Scientific Knowledge Graphs (SKGs) through semantic annotation, entity extraction, citation analysis, and classification services. The evaluation followed a structured methodology combining preparatory pilot setup, component‑level validation and pilot demonstrators assessing end‑to‑end research workflows. Results show that SciLake’s modular architecture effectively supports semantic exploration, structured search, and graph‑based analysis, with high user acceptance and strong performance across key services. The assessment confirms the system’s operational readiness while identifying areas for refinement. Overall, the pilots validate SciLake as a coherent and extensible ecosystem for advanced scientific knowledge discovery.

Zenodo (CERN European Organization for Nuclear Research)
Epson (United States) (US), National Technical University of Athens (GR), Panteion University (GR), University of Oslo (NO), Karolinska Institutet (SE), German Research Centre for Artificial Intelligence (DE), HES-SO Valais-Wallis (CH), Centre for Research and Technology Hellas (GR), Athena Research and Innovation Center In Information Communication & Knowledge Technologies (GR), e-Trikala (Greece) (GR), SIRIS Academic, Eindhoven University of Technology (NL), Sirris (BE)
Openalex Percentile: Top 16%
Advanced Graph Neural Networks
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