There is a huge amount of data spread across the web and stored in databases that we can use to build knowledge graphs. However, exploiting this data to build knowledge graphs is difficult due to the heterogeneity of the sources, scale of the amount of data, and noise in the data. In this paper we present an approach to building knowledge graphs by exploiting semantic technologies to reconcile the data continuously crawled from diverse sources, to scale to billions of triples extracted from the crawled content, and to support interactive queries on the data. We applied our approach, implemented in the DIG system, to the problem of combating human trafficking and deployed it to six law enforcement agencies and several non-governmental organizations to assist them with finding traffickers and helping victims.

CRMgeo is a formal ontology intended to be used as a global schema for integrating spatiotemporal properties of temporal entities and persistent items. Its primary purpose is to provide a schema consistent with the CIDOC CRM to integrate geoinformation using the conceptualizations, formal definitions, encoding standards and topological relations defined by the Open Geospatial Consortium in GeoSPARQL. To build the ontology, the same ontology engineering methodology was used as in the CIDOC CRM. CRMgeo first introduced the concept of Spacetime volume that was subsequently included in the CIDOC CRM and provides a differentiation between phenomenal and declarative Spacetime volume, Place and Time-Span. Phenomenal classes derive their identity from real world phenomena like events or things and declarative classes derive their identity from human declarations like dates or coordinates. This differentiation is an essential conceptual background to link CIDOC CRM to the classes, topological relations and encodings provided by Geo-SPARQL and thus allowing Lehrstuhl für Digital Humanities, Universität Passau, Passau, Germany spatiotemporal analysis offered by geoinformation systems based on the semantic distinctions of the CIDOC CRM. CRMgeo introduces the classes and relations necessary to model the spatiotemporal properties of real world phenomena and their topological and semantic relations to spatiotemporal information about these phenomena that was derived from historic sources, maps, observations or measurements. It is able to model the full chain of approximating and finding again a phenomenal place, like the actual site of a ship wreck, by a declarative place, like a mark on a sea chart.

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How to put archaeological geometric data into context? Representing mining history research with CIDOC CRM and extensions How to put archaeological geometric data into context? Representing mining history research with CIDOC CRM and extensions