Semantic units: organizing knowledge graphs into semantically meaningful units of representation

dc.bibliographicCitation.firstPage7
dc.bibliographicCitation.volume15
dc.contributor.authorVogt, Lars
dc.contributor.authorKuhn, Tobias
dc.contributor.authorHoehndorf, Robert
dc.date.accessioned2024-07-03T12:28:47Z
dc.date.available2024-07-03T12:28:47Z
dc.date.issued2024
dc.description.abstractBackground In today’s landscape of data management, the importance of knowledge graphs and ontologies is escalating as critical mechanisms aligned with the FAIR Guiding Principles—ensuring data and metadata are Findable, Accessible, Interoperable, and Reusable. We discuss three challenges that may hinder the effective exploitation of the full potential of FAIR knowledge graphs. Results We introduce “semantic units” as a conceptual solution, although currently exemplified only in a limited prototype. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs by adding another layer of triples on top of the conventional data layer. Semantic units and their subgraphs are represented by their own resource that instantiates a corresponding semantic unit class. We distinguish statement and compound units as basic categories of semantic units. A statement unit is the smallest, independent proposition that is semantically meaningful for a human reader. Depending on the relation of its underlying proposition, it consists of one or more triples. Organizing a knowledge graph into statement units results in a partition of the graph, with each triple belonging to exactly one statement unit. A compound unit, on the other hand, is a semantically meaningful collection of statement and compound units that form larger subgraphs. Some semantic units organize the graph into different levels of representational granularity, others orthogonally into different types of granularity trees or different frames of reference, structuring and organizing the knowledge graph into partially overlapping, partially enclosed subgraphs, each of which can be referenced by its own resource. Conclusions Semantic units, applicable in RDF/OWL and labeled property graphs, offer support for making statements about statements and facilitate graph-alignment, subgraph-matching, knowledge graph profiling, and for management of access restrictions to sensitive data. Additionally, we argue that organizing the graph into semantic units promotes the differentiation of ontological and discursive information, and that it also supports the differentiation of multiple frames of reference within the graph.eng
dc.description.fondsTIB_Fonds
dc.description.versionpublishedVersion
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/14762
dc.identifier.urihttps://doi.org/10.34657/13784
dc.language.isoeng
dc.publisherLondon : BioMed Central
dc.relation.doihttps://doi.org/10.1186/s13326-024-00310-5
dc.relation.essn2041-1480
dc.rights.licenseCC BY 4.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectFAIR data and metadataeng
dc.subjectKnowledge grapheng
dc.subjectOWLeng
dc.subjectRDFeng
dc.subjectSemantic uniteng
dc.subjectGraph organizationeng
dc.subjectGranularity treeeng
dc.subjectRepresentational granularityeng
dc.subject.ddc570
dc.subject.ddc610
dc.titleSemantic units: organizing knowledge graphs into semantically meaningful units of representation
dc.typeArticle
dc.typeText
dcterms.bibliographicCitation.journalTitleJournal of biomedical semantics
tib.accessRightsopenAccess
wgl.contributorTIB
wgl.subjectInformatik
wgl.typeZeitschriftenartikel
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