First Workshop on Geospatial Knowledge Graphs
co-located with The Knowledge Graph Conference 2022 at Cornell Tech campus, New York, and globally online, from May 2 - 6, 2022
Call for papers
We invite submissions to the First Workshop on Geospatial Knowledge Graphs (GeoKG2022) to be held in conjunction with the The Knowledge Graph Conference 2022 (KGC2022) that will take place at Cornell Tech campus, New York, and globally online, from May 2 to 6, 2022. GeoKG2022 is a half-day workshop consisting of two parts: paper presentations, and an interactive breakout discussion session.
The workshop aims to bring together disparate elements of the environmental and geospatial community and provide a setting to discourse about large-scale knowledge graphs for geospatial and environmental data integration and intelligence, state-of-the-art, spatiotemporally-explicit machine learning methods, tools, and their potential as well as limitations on addressing geospatial challenges. More specifically, the goal is to foster discussion on frameworks for leveraging spatial and temporal knowledge as the nexus to integrate environmental data of various themes within geospatial knowledge graphs.
We particularly welcome contributions on topics related to environmental data integration using knowledge graphs and geospatial intelligence services using innovative machine learning techniques. The main topics of interest are:
1) Geospatial Ontologies and Geospatial Knowledge Graph Construction - Spatiotemporal Scoping of GKGs - Ontologies to encode environmental observations and events in GeoKGs
2) Querying Geospatial Knowledge Graphs - GeoSPARQL and Spatial Query Evaluation - GeoKGs Visualizations
3) Machine Learning for Geospatial Knowledge Graphs - Geospatial Knowledge Graph Embeddings - Spatiotemporally-explicit Machine Learning Models for Environmental Tasks
4) Other GeoKG Topics and Applications - Real-world use cases of GeoKGs - Applications of Geospatial Knowledge Graphs (e.g. knowledge graphs in environmental data integration and AI systems)
All times are in EST (UTC -5).
|9:00 - 9:15||Welcome note and opening introduction||Organizing Committee|
|9:15 - 10:15||Keynote address - Knowledge Graph Construction and Application in GeoSciences - An Illustration with the Deep-Time Knowledge Graph>||Dr. Marshall (Xiaogang) Ma - (University of Idaho)|
|10:15 - 10:30||Break|
|10:30 - 10:45||Stratigraphic Knowledge Graph (StratKG) - Construction and Spatio-Temporal analysis based on Multi-source Data||Wenjia Li|
|10:45 - 11:00||A Knowledge Graph of Experts with Spatiotemporal Information||Yuanyuan Tian|
|11:00 - 11:15||Geospatial Knowledge Graph Development - For the National Map of the U.S. Geological Survey||Dalia Varanka|
|11:15 - 11:30||WorldKG - A World Scale Geographic Knowledge Graph||Alishiba Dsouza|
|11:30 - 11:45||Modeling Sustainability - A Spatial Approach to Facilitate Interdisciplinary Knowledge Representation||Ellie Young|
|11:45 - 12:00||Discussion and closing remarks|
We invite the submission of original research results and industry-level applications related to the focus areas of the workshop, in one of two categories given below. All submissions are requested through EasyChair.
1) Short papers (maximum 5 pages LNCS style) presenting proposed research directions, novel ideas, use-case scenarios, established results or more general positions or discussions.
2) Vision papers (maximum 4 pages ) presenting important directions for future research on GeoKGs. Such papers should identify key problem areas for GeoKGs, and propose potential solutions or strategies that could be developed to address such problems. Ideally the papers should highlight open research questions for GeoKGs, and should stimulate future research.
Submissions should be sent to firstname.lastname@example.org
- Papers submissions: April 12, 2022
- Papers notifications: April 16, 2022
- Camera-ready version submissions: April 22, 2022
- Workshop will be held on May 3rd between 9 AM -12PM
- Shirly Stephen, University of California, Santa Barbara, USA
- Lu Zhou, Tigergraph, Inc., USA
- Rui Zhu, University of California, Santa Barbara, USA
- Cogan Shimizu, Kansas State University, USA