Geospatial Knowledge Graphs and Ontology

Type: Virtual Paper
Theme:
Sponsor Groups: Geographic Information Science and Systems Specialty Group, Cyberinfrastructure Specialty Group
Poster #:
Day: 4/7/2021
Start / End Time: 11:10 AM / 12:25 PM (PDT)
Room: Virtual 46
Organizers: Alexandre Sorokine, Jeon-Young Kang, Chen-Chieh Feng, Dalia Varanka
Chairs: Alexandre Sorokine

Call for Submissions

We are soliciting presentations on both theoretical and applied aspects of spatiotemporal knowledge graphs and ontologies for the special sessions at the 2021 American Association of Geographers Annual Meeting. We welcome presentations on the following topics including, but not limited to:

* Spatial and spatiotemporal knowledge modeling, analysis, formalization, and validation (knowledge graphs, vocabularies, thesauri, ontologies)
* Emerging technologies and methods like GeoAI, deep learning, natural language processing (NLP), property graphs to support knowledge graph building, matching, and reasoning
* Information retrieval with knowledge graphs and deep learning models
* Data fusion and semantic interoperability across knowledge domains, cultures, ethnicities, languages, and time, spatiotemporal models
* Technologies for geospatial knowledge representation and processing (e.g., graph databases, GeoSPARQL, RDF, OWL)

To present a paper or to participate in the session as a discussant, submit your abstract through AAG website and email your Participant Identification Number (PIN) to Alex Sorokine (SorokinA@ornl.gov). Please follow standard AAG abstract submission procedure and guidelines. If you have any questions please forward them to one of the organizers.


Description

Capturing and representing geospatial and spatiotemporal dimensions of geographic knowledge is a great challenge from both theoretical and applied perspectives. Nowadays formalized geospatial knowledge representations and reasoning in the form of knowledge graphs powers search engines, discovery of geodata, and understanding of the crowdsourced information. New technologies like deep learning and advanced natural language processing open new possibilities for practical applications and research in this area.

We welcome presentations on the following topics including, but not limited to:

* Spatial and spatiotemporal knowledge modeling, analysis, formalization, and validation (knowledge graphs, vocabularies, thesauri, ontologies)
* Emerging technologies and methods like GeoAI, deep learning, natural language processing (NLP), property graphs to support knowledge graph building, matching, and reasoning
* Information retrieval with knowledge graphs and deep learning models
* Data fusion and semantic interoperability across knowledge domains, cultures, ethnicities, languages, and time, spatiotemporal models
* Technologies for geospatial knowledge representation and processing (e.g., graph databases, GeoSPARQL, RDF, OWL)


Agenda

Type Details Minutes Start Time
Presenter Junchuan Fan*, Oak Ridge National Laboratory, Gautam Thakur, Oak Ridge National Laboratory, Context-aware Spatial Semantic Network for Multi-Scale Land Use Mapping 15 11:10 AM
Presenter Dalia Varanka*, United States Geological Survey, An Approach to GeoSpatial Knowledge Interoperability; Metadata, Semantics, and Alignment 15 11:25 AM
Presenter Chen-Chieh Feng*, Geography, National University of Singapore, Extracting spatial relations from unstructured text 15 11:40 AM
Presenter Sean Gordon*, Portland State University, Designing an open knowledge network for spatial decision support in the context of multi-stakeholder environmental planning 15 11:55 AM
Presenter Alexandre Sorokine*, Oak Ridge National Laboratory, Jason Kaufman, Oak Ridge National Laboratory, Jacob Arndt, Oak Ridge National Laboratory, Robert Stewart, Oak Ridge National Laboratory, Geodata Integration Using Rules and Machine Learning 15 12:10 PM

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