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Documents authored by Kedrowski, David K.


Document
Precomputed Topological Relations for Integrated Geospatial Analysis Across Knowledge Graphs

Authors: Katrina Schweikert, David K. Kedrowski, Shirly Stephen, and Torsten Hahmann

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)


Abstract
Geospatial Knowledge Graphs (GeoKGs) represent a significant advancement in the integration of AI-driven geographic information, facilitating interoperable and semantically rich geospatial analytics across various domains. This paper explores the use of topologically enriched GeoKGs, built on an explicit representation of S2 Geometry alongside precomputed topological relations, for constructing efficient geospatial analysis workflows within and across knowledge graphs (KGs). Using the SAWGraph knowledge graph as a case study focused on enviromental contamination by PFAS, we demonstrate how this framework supports fundamental GIS operations - such as spatial filtering, proximity analysis, overlay operations and network analysis - in a GeoKG setting while allowing for the easy linking of these operations with one another and with semantic filters. This enables the efficient execution of complex geospatial analyses as semantically-explicit queries and enhances the usability of geospatial data across graphs. Additionally, the framework eliminates the need for explicit support for GeoSPARQL’s topological operations in the utilized graph databases and better integrates spatial knowledge into the overall semantic inference process supported by RDFS and OWL ontologies.

Cite as

Katrina Schweikert, David K. Kedrowski, Shirly Stephen, and Torsten Hahmann. Precomputed Topological Relations for Integrated Geospatial Analysis Across Knowledge Graphs. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 4:1-4:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{schweikert_et_al:LIPIcs.GIScience.2025.4,
  author =	{Schweikert, Katrina and Kedrowski, David K. and Stephen, Shirly and Hahmann, Torsten},
  title =	{{Precomputed Topological Relations for Integrated Geospatial Analysis Across Knowledge Graphs}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{4:1--4:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.4},
  URN =		{urn:nbn:de:0030-drops-238332},
  doi =		{10.4230/LIPIcs.GIScience.2025.4},
  annote =	{Keywords: knowledge graph, GeoKG, spatial analysis, ontology, SPARQL, GeoSPARQL, discrete global grid system, S2 geometry, GeoAI, PFAS}
}
Artifact
Software
OWL Ontologies for the Urban Flooding Open Knowledge Network (UF-OKN)

Authors: Torsten Hahmann and David K. Kedrowski


Abstract

Cite as

Torsten Hahmann, David K. Kedrowski. OWL Ontologies for the Urban Flooding Open Knowledge Network (UF-OKN) (Software). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@misc{dagstuhl-artifact-22447,
   title = {{OWL Ontologies for the Urban Flooding Open Knowledge Network (UF-OKN)}}, 
   author = {Hahmann, Torsten and Kedrowski, David K.},
   note = {Software, version 2.1., National Science Foundation, award# 2033607, National Science Foundation, award# 1937099, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:00a0f1fbcd022a6beed4d88b6430567ef1314872;origin=https://github.com/UFOKN/Knowledge-Graph;visit=swh:1:snp:c72cfbb7d2958ec9082a9266afc9de82b375f737;anchor=swh:1:rev:4b80c683fa9b83d85e3cb09cadc608069172e308}{\texttt{swh:1:dir:00a0f1fbcd022a6beed4d88b6430567ef1314872}} (visited on 2024-11-28)},
   url = {https://github.com/UFOKN/Knowledge-Graph/tree/master/ontologies/v2.1},
   doi = {10.4230/artifacts.22447},
}
Document
Short Paper
An Ontology and Geospatial Knowledge Graph for Reasoning About Cascading Failures (Short Paper)

Authors: Torsten Hahmann and David K. Kedrowski

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)


Abstract
During a natural disaster such as flooding, the failure of a single asset in the complex and interconnected web of critical urban infrastructure can trigger a cascade of failures within and across multiple systems with potentially life-threatening consequences. To help emergency management effectively and efficiently assess such failures, we design the Utility Connection Ontology Design Pattern to represent utility services and model connections within and across those services. The pattern is encoded as an OWL ontology and instantiated with utility data in a geospatial knowledge graph. We demonstrate how it facilitates reasoning to identify cascading service failures due to flooding for producing maps and other summaries for situational awareness.

Cite as

Torsten Hahmann and David K. Kedrowski. An Ontology and Geospatial Knowledge Graph for Reasoning About Cascading Failures (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 21:1-21:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{hahmann_et_al:LIPIcs.COSIT.2024.21,
  author =	{Hahmann, Torsten and Kedrowski, David K.},
  title =	{{An Ontology and Geospatial Knowledge Graph for Reasoning About Cascading Failures}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{21:1--21:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.21},
  URN =		{urn:nbn:de:0030-drops-208364},
  doi =		{10.4230/LIPIcs.COSIT.2024.21},
  annote =	{Keywords: knowledge graph, ontology, OWL, spatial reasoning, cascading failures, urban infrastructure}
}
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