01566nas a2200193   4500008004100000020001800041245007400059210006900133260005900202300001400261520093500275653002301210653002101233653000901254100002101263700002001284700002401304856004401328       2021                        eng d  a978145038664700aSemantic Compression with Region Calculi in Nested Hierarchical Grids0 aSemantic Compression with Region Calculi in Nested Hierarchical   aNew York, NY, USAbAssociation for Computing Machinery  a305–3083 a<p>We propose the combining of region connection calculi with nested hierarchical grids for representing spatial region data in the context of knowledge graphs, thereby avoiding reliance on vector representations. We present a resulting region calculus, and provide qualitative and formal evidence that this representation can be favorable with large data volumes in the context of knowledge graphs; in particular we study means of efficiently choosing which triples to store to minimize space requirements when data is represented this way, and we provide an algorithm for finding the smallest possible set of triples for this purpose including an asymptotic measure of the size of this set for a special case. We prove that a known constraint calculus is adequate for the reconstruction of all triples describing a region from such a pruned representation, but problematic for reasoning with hierarchical grids in general.</p>
10aHierarchical Grids10aKnowledge Graphs10aRCC51 aZalewski, Joseph1 aHitzler, Pascal1 aJanowicz, Krzysztof  uhttps://doi.org/10.1145/3474717.3483965