GeoAI and Deep Learning Symposium: Geospatial and Spatiotemporal Ontology and Semantics I

Type: Paper
Theme:
Sponsor Groups: Cyberinfrastructure Specialty Group, Geographic Information Science and Systems Specialty Group
Poster #:
Day: 4/4/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Capitol Room, Omni, East
Organizers: Alexandre Sorokine, Chen-Chieh Feng, Jeon-Young Kang
Chairs: Chen-Chieh Feng

Call for Submissions

We are soliciting presentations on both theoretical and applied aspects of geospatial and spatiotemporal ontologies for the special sessions at the 2019 American Association of Geographers Annual Meeting. Next year the series in its 15th year will be a part of the 2nd GeoAI and Deep Learning Symposium. We invite presentations focusing on one or more of the following (or other related) areas of ontology research:

- Spatial and spatiotemporal knowledge modeling, analysis, formalization, and validation (thesauri, vocabularies, and ontologies)
- Emerging technologies and methods (artificial intelligence, deep learning, natural language processing) to support spatiotemporal reasoning, ontology matching, and alignment
- Mutual benefits between GeoAI and Deep Learning, and geospatial/spatiotemporal ontology
- Information retrieval with knowledge graphs and deep learning models
- Data fusion and semantic interoperability across domains, cultures, ethnicities, languages, and time, spatiotemporal models
- Semantic annotation methods, provenance, and standards for spatial knowledge representation and processing (e.g. OWL, RDF, RDFS, JSON-LD, GeoJSON)

To present a paper or to participate in the session as a discussant, submit your abstract through AAG web site 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 ontologies and 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.

This special session is in its 15th year and in 2019 is a part of the 2nd GeoAI and Deep Learning Symposium. This year the presentations will be focused on the following topics:

- Spatial and spatiotemporal knowledge modeling, analysis, formalization, and validation (thesauri, vocabularies, and ontologies)
- Emerging technologies and methods (artificial intelligence, deep learning, natural language processing) to support spatiotemporal reasoning, ontology matching, and alignment
- Mutual benefits between GeoAI and Deep Learning, and geospatial/spatiotemporal ontology
- Information retrieval with knowledge graphs and deep learning models
- Data fusion and semantic interoperability across domains, cultures, ethnicities, languages, and time, spatiotemporal models
- Impacts of new semantic technologies


Agenda

Type Details Minutes Start Time
Presenter Misa Yasumiishi*, University at Buffalo, the State University of New York, Thomas E Bittner, University at Buffalo, the State University of New York, Utility Ontology of a Nuclear Accident: Ontological Approach to Understanding the Conceptual Structure of a Nuclear Accident 20 8:00 AM
Presenter Jason Kaufman*, Oak Ridge National Laboratory, A Systematic Evaluation of the Use of Administrative Units in Geospatial Data Modeling 20 8:20 AM
Presenter Genevieve Reid*, McGill University, Spatio-temporal ontologies and Indigenous concepts of space and time 20 8:40 AM
Presenter Alexandre Sorokine*, Oak Ridge National Laboratory, Gautam Thakur, Oak Ridge National Laboratory, Comparing Geographic Categories in Different Languages Using Large Volunteered Geodata 20 9:00 AM
Presenter Chen-Chieh Feng*, Geography, National University of Singapore, Capturing relations for understanding spatial dynamics from unstructured text 20 9:20 AM

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