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KGI4NFDI and TS4NFDI: A natural fit for applying semantic web technologies in practice [Poster]

Authors: Zapilko, Benjamin; Baum, Roman; Elhossary, Muhammad; Limani, Fidan; Mietchen, Daniel; Rossenova, Lozana; Sauerwein, Till; +3 Authors

KGI4NFDI and TS4NFDI: A natural fit for applying semantic web technologies in practice [Poster]

Abstract

Knowledge graphs (KG) and terminologies are closely related, as both are used to structure and represent knowledge within a certain scope. However, a more nuanced approach suggests a division into standard ontologies and vocabularies (Tbox) and specific (meta)data instances (Abox). A Tbox comprises expressions that contain universal statements about classes, while an Abox contains assertions about instances. In essence, terminologies offer standardized vocabularies, comprising concepts, definitions, and relationships, which form the basis for constructing KGs. These KGs, in turn, organize terminologies into semantic layers interconnecting networks of data / knowledge, and thereby enabling semantic reasoning and data integration. By leveraging terminologies, KGs ensure consistency and interoperability across various applications, such as AI-assisted tools, information search, and data analytics. KGI4NFDI advocates for a domain-independent, reusable Knowledge Graph Infrastructure (KGI) to enhance interoperability across diverse research domains and support the objectives of the NFDI. KGI4NFDI provides a KG Registry enabling discovery and federation across KGs in the NFDI, and empowers research communities to create decentralised KG instances using standardised approaches, technologies, and expertise. In a complementary manner, TS4NFDI is a cross-domain service for the provision, curation, development, harmonization and mapping of terminologies. It aims to facilitate consensus-building and interoperability of research data services and achieve a shared knowledge representation and knowledge engineering framework. Both Base services contribute to the “One NFDI” vision and deliver concrete applications of the FAIR data principles on national and international level, through future integration with EOSC. In this poster, we showcase initial prototypes integrating the two services and extending their functionalities in delivering FAIR data infrastructure for the NFDI. A first goal is to integrate the Terminology Service Suite (TSS) widgets into the contribution workflow for new entries into the KG Registry. By using an ontology provided by TS4NFDI (e.g., NFDI Core Ontology) a complete registration form can be generated based on a selection of required entities and relations. In addition, TSS widgets can allow users to choose metadata on e.g. domain subjects from a controlled vocabulary such as the DFG Classification of Subject Areas Ontology. Alongside these prototypes, the presentation will outline a vision of how KGI4NFDI and TS4NFDI could be a natural fit for enhancing the added value of applying Semantic Web technologies in NFDI. In the future, cross-domain ontology mappings provided by TS4NFDI could expand the functionality of the KG Registry. Such mappings, paired with corresponding TSS widget implementation on the user interface level, could facilitate user interactions with cross-domain data retrieval and analysis, in particular the construction of federated SPARQL queries across heterogeneous resources. This enhancement would increase accessibility and discovery across all communities represented by NFDI consortia, potentially leading to new research discoveries. An example from BERD@NFDI already points to the benefits of combining TS with KGI services - the BERD terminology service, which is based on the TSS widgets, is used to enrich the BERD KG with references to external ontologies and vocabularies. See also: https://doi.org/10.5281/zenodo.16736068 FundingFunded by Deutsche Forschungsgemeinschaft as part of Base4NFDI. DFG Grant Number: 521453681.

Keywords

NFDI, Terminologies, Base4NFDI, Research Data Management, TS4NFDI, Knowledge Graphs, KGI4NFDI, Semantic Web

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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