Semantic x-Lab: Semantic search for ontology-based descriptions of laboratory processes, resources, and data

Research Institutions and universities already collect extensive metadata from projects, proposal, publication, and workflow systems. However, this information is scattered across multiple, partly isolated systems and must be linked and semantically enriched to generate true scientific knowledge. The HMC-funded Semantic x-Lab project aims to integrate these information, make them searchable, and reveal new connections. The outcome is hopefully a distributed knowledge graph co-designed with users from laboratories, large-scale facilities, and across research domains.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-11
DOI
https://doi.org/10.5281/zenodo.18607915
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Semantic x-Lab: Semantic search for ontology-based descriptions of laboratory processes, resources, and data

Oliver Knodel
Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

Semantic x-Lab: Semantic search for ontology-based descriptions of laboratory processes, resources, and data

Oliver Knodel
article en

Abstract

Research Institutions and universities already collect extensive metadata from projects, proposal, publication, and workflow systems. However, this information is scattered across multiple, partly isolated systems and must be linked and semantically enriched to generate true scientific knowledge. The HMC-funded Semantic x-Lab project aims to integrate these information, make them searchable, and reveal new connections. The outcome is hopefully a distributed knowledge graph co-designed with users from laboratories, large-scale facilities, and across research domains.

Zenodo (CERN European Organization for Nuclear Research)
Helmholtz-Zentrum Dresden-Rossendorf (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 61%
Scientific Computing and Data Management
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