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Know, Know Where, Knowwheregraph: A Densely Connected, Cross-Domain Knowledge Graph and Geo-Enrichment Service Stack for Applications in Environmental Intelligence

Krzysztof Janowicz, Pascal Hitzler, Wenwen Li, Dean Rehberger, Mark Schildhauer, Rui Zhu, Cogan Shimizu, Colby Fisher, Ling Cai, Gengchen Mai, Joseph Zalewski, Lu Zhou (+14 others)
<span title="2022-03-31">2022</span> <i title="Association for the Advancement of Artificial Intelligence (AAAI)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/27wksbinzzhjfow2wuy6m2iefm" style="color: black;">The AI Magazine</a> </i> &nbsp;
We will present our KnowWhereGraph that contains a wide range of integrated datasets at the human–environment interface, introduce our application areas, and discuss geospatial enrichment services on top  ...  Knowledge graphs (KGs) are a novel paradigm for the representation, retrieval, and integration of data from highly heterogeneous sources.  ...  FUTURE PLANS In this work, we have introduced the KnowWhereGraph, a densely connected, cross-domain KG together with geoenrichment services to support a variety of application areas that benefit from environmental  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1609/aimag.v43i1.19120">doi:10.1609/aimag.v43i1.19120</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nz6n74suorcexj7rth5mnqve3q">fatcat:nz6n74suorcexj7rth5mnqve3q</a> </span>
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