About
With the rapid revolution and increasing availability of geospatial data, not only academia but also industry aspire for solutions to further leverage the big data and AI technologies to create new products, improve efficiencies and provide novel solutions to existing problems. However, despite the widespread interest, there is a lack of communication between the researchers in academia and industry, limiting advancements at the intersection. Academia often has limited access to the rich and potentially useful big geospatial datasets and related real problems. In addition, the solutions proposed by the academic researchers alone are usually developed for small scale with many assumptions, leaving a less-attended gap between methods and their applicability at scale for industrial applications. On the other hand, industry has the data and problems at scale. However, since existing research is often not on par, industry researchers may lean towards using the traditional approaches that are developed without spatial consideration (e.g., ignoring spatial and temporal dependencies), and project teams have limited time and efforts to dive deep on the development of novel techniques that can be high-risk but high-potential. This opens up opportunities for synergistic collaboration between industrial practitioners and academic researchers. The 2nd ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications (GeoIndustry 2023) is to offer a forum to exchange thoughts and ideas between industry and academia and reduce the siloed efforts. At the same time, the collaborations, via invited and regular talks, can not only accelerate the research-to-impact cycle, but also foster workforce development for future geospatial researchers.
Organization Committee
Program Chairs
| Heba Aly (Amazon) |
| Emre Eftelioglu (Amazon) |
| Song Gao (University of Wisconsin-Madison) |
| Yan Li (Amazon) |
| Jinmeng Rao (Mineral Earth Sciences) |
| Yiqun Xie (University of Maryland) |
Call For Papers (PDF version)
The workshop seeks high-quality regular (8-10 pages) and short (4 pages) papers that have not been published in other academic outlets and are not concurrently under peer review. Interested participants should submit a paper in the ACM format. Once accepted, at least one author is required to register for the workshop and the ACM SIGSPATIAL conference, as well as attend the workshop to present the accepted work which will then appear in the ACM Digital Library.
The topics include but are not limited to (in the context of industrial or related problems, such as delivery, routing, recommendation, mapping, resource allocation, and more):
Applications of AI
Applications of big data systems
Problems and benchmark datasets
Machine learning and deep learning
Computer vision and Earth observation
Generative models and simulation
Map generation
Heterogeneous data
Small data learning
Citizen science and data collection
Spatial query processing
Spatial data management and integration
Perspectives
Emerging topics and trends
Important Dates
Submission deadline
September 15, 2023 (anywhere on earth, extended)
Author notification
October 6, 2023 (anywhere on earth)
Workshop date
November 13, 2023