https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc/Head https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc/assertion https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc/provenance https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc/pubinfo https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc/assertion http://id.crossref.org/issn/2194-9034 http://purl.org/dc/terms/title The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/dc/terms/abstract In the recent years the concept of knowledge graph has emerged as a way to aggregate information from various sources without imposing too strict data modelling constraints. Several graph models have been proposed during the years, ranging from the “standard” RDF to more expressive ones, such as Neo4J and RDF-star. The adoption of knowledge graph has become established in several domains. It is for instance the case of the 3D geoinformation domain, where the adoption of semantic web technologies has led to several works in data integration and publishing. However, yet there is not a well-defined model or technique to represent 3D geoinformation including uncertainty and time variation in knowledge graphs. In this paper we propose a model to represent parameterized geometries of subsurface objects. The vocabulary of the model has been defined as an OWL ontology and it extends existing ontologies by adding classes and properties to represent the uncertainty and the spatio-temporal behaviour of a geometry, as well as additional attributes, such as the data provenance. The model has been validated on significant use cases showing different types of uncertainties on 3D subsurface objects. A possible implementation is also presented, using RDF-star for the data representation. https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/dc/terms/date 2021-10-07 https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/dc/terms/isPartOf http://id.crossref.org/issn/2194-9034 https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/dc/terms/title KNOWLEDGE GRAPH CONSTRUCTION FOR SUBSURFACE OBJECTS INCLUDING UNCERTAINTY AND TIME VARIATION https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/ontology/bibo/authorList https://w3id.org/np/RAc3rrt1g7sC5CpYbILiHvpL6Ni7t4jCk08twBrOIDGAc/author-list https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/ontology/bibo/pageEnd 136 https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 http://purl.org/ontology/bibo/pageStart 131 https://doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-131-2021 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