Knowledge graphs are not merely a set of technologies, but a novel paradigm for representing, retrieving, integrating, and reasoning data from highly heterogeneous and multimodal sources. Knowledge graphs (KGs) have become a core component of modern search engines, intelligent personal assistants, and business intelligence within just a few years. However, despite large-scale data availability, KGs have not yet been as successful in the realm of environmental and geospatial studies. Geospatial knowledge graphs (GeoKGs), as symbolic representations of spatial entities, their attributes, and the relations among them, bring together Geographic Information Science (GIScience), Cognitive Science, and Artificial Intelligence (AI) to help facilitate many geospatial applications such as geographic question answering, geospatial interoperability, and geospatial knowledge discovery. Nevertheless, most existing data warehouses and associated techniques in KGs do not take into account the speciality of geospatial information so GeoKGs hardly achieves its full potential in geo-science and its downstream applications.
This half-day workshop aims to emphasize the importance of geospatial information and principles in designing, developing, and utilizing geospatial knowledge graphs and other geospatial AI techniques. It will include keynote speakers, individual presentations, as well as a panel discussion at the end.
We invite researchers from disparate disciplines (e.g., environmental studies, GIScience, AI, cognition, supply chain, humanities, etc.) to submit papers in the following three formats. All submitted papers will be peer-reviewed by our Program Committee (PC). Manuscripts should be submitted in PDF format and formatted using the ACM camera-ready templates available at http://www.acm.org/publications/proceedings-template. Submissions will be single-blind — i.e., the names affiliations of the authors should be listed in the submitted version.
UC Santa Barbara, USA
University of Vienna, Austria
University of Bristol, UK
Oak Ridge National Laboratory, USA
University of Idaho, USA
Common Action, USA
University of Georgia, USA