Proceedings of the 9th ACM SIGSPATIAL Workshop on Analytics for Big Geospatial Data (BigSpatial 2020)
BigSpatial 2020
- URL: https://bigspatial2020.github.io/
- Event Date: 2020-11-03 ~ 2020-11-03
- Submission Date: 2020-08-31
- Location: Seattle, United States of America
9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial 2020)
Big data is currently the hottest topic for data researchers and scientists with huge interests from the industry and federal agencies alike, as evident in the recent White House initiative on “Big data research and development”. Within the realms of big data, spatial and spatio-temporal data is one of fastest growing types of data and poses a massive challenge to researchers who deal with analyzing such data. With advances in remote sensors, sensor networks, and the proliferation of location sensing devices in daily life activities and common business practices, the generation of disparate, dynamic, and geographically distributed spatio-temporal data has exploded in recent years. In addition, significant progress in ground, air- and space-borne sensor technologies has led to an unprecedented access to earth science data for scientists from different disciplines, interested in studying the complementary nature of different parameters.
The 9th workshop on Analytics for Big Geospatial Data aims to bring together researchers from academia, government and industrial research labs who are working in the area of spatial analytics with an eye towards massive data sizes. The objective of this workshop is to provide a platform for researchers engaged in addressing the big data aspect of spatial and spatio-temporal data analytics to present and discuss their ideas. We invite participants from industry, academia, and government to participate in this event and share, contribute, and discuss the emerging big data challenges in the context of spatial and spatio-temporal data analysis.
Topics of Interest:
The workshop welcomes contributions in the area of large scale analytics for spatial and spatio-temporal data. The topics include:
1. Scalable analysis algorithms for spatial and spatio-temporal data mining
2. Novel applications on high performance computing frameworks (Clusters, GPU, cloud, Grid) for large scale spatial and spatio-temporal analysis
3. Performance studies comparing clouds, grids, and clusters for spatial and spatio-temporal analytics
4. Novel indexing methods for massive geospatial data
5. Visualization of massive geospatial data
6. Customizations and extensions of existing software infrastructures such as Hadoop for spatial, and spatiotemporal data mining
7. Applications of big data analysis: Climate Change, Disaster Management, Monitoring Critical Infrastructures, Transportation
Paper Submission:
We invite papers discussing novel research and ideas without substantial overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Submitted papers can be of two types:
1. Regular Research Papers: These papers should report original research results or significant case studies. They should be at most 10 pages.
2. Position Papers: These papers should report novel research directions or identify challenging problems. They should be at most 4 pages.
Manuscripts should be submitted in PDF format and formatted using the ACM camera-ready templates. Submissions are limited to 10 pages. All submissions should clearly present the author information including the names of the authors, the affiliations and the emails. The papers should be submitted through the workshop submission system. One author per accepted workshop paper is required to register for both the main SIGSPATIAL conference and the workshop, to attend the workshop, and to present the accepted paper in the workshop.
Submission Website:
https://easychair.org/conferences/?conf=bigspatial2020
Important Dates:
Paper Submission: August 31, 2020
Notification of Acceptance: September 21, 2020
Camera Ready Paper Due: October 5, 2020
All submissions are due at 11:59 PM Pacific Standard Time.
Big data is currently the hottest topic for data researchers and scientists with huge interests from the industry and federal agencies alike, as evident in the recent White House initiative on “Big data research and development”. Within the realms of big data, spatial and spatio-temporal data is one of fastest growing types of data and poses a massive challenge to researchers who deal with analyzing such data. With advances in remote sensors, sensor networks, and the proliferation of location sensing devices in daily life activities and common business practices, the generation of disparate, dynamic, and geographically distributed spatio-temporal data has exploded in recent years. In addition, significant progress in ground, air- and space-borne sensor technologies has led to an unprecedented access to earth science data for scientists from different disciplines, interested in studying the complementary nature of different parameters.
The 9th workshop on Analytics for Big Geospatial Data aims to bring together researchers from academia, government and industrial research labs who are working in the area of spatial analytics with an eye towards massive data sizes. The objective of this workshop is to provide a platform for researchers engaged in addressing the big data aspect of spatial and spatio-temporal data analytics to present and discuss their ideas. We invite participants from industry, academia, and government to participate in this event and share, contribute, and discuss the emerging big data challenges in the context of spatial and spatio-temporal data analysis.
Topics of Interest:
The workshop welcomes contributions in the area of large scale analytics for spatial and spatio-temporal data. The topics include:
1. Scalable analysis algorithms for spatial and spatio-temporal data mining
2. Novel applications on high performance computing frameworks (Clusters, GPU, cloud, Grid) for large scale spatial and spatio-temporal analysis
3. Performance studies comparing clouds, grids, and clusters for spatial and spatio-temporal analytics
4. Novel indexing methods for massive geospatial data
5. Visualization of massive geospatial data
6. Customizations and extensions of existing software infrastructures such as Hadoop for spatial, and spatiotemporal data mining
7. Applications of big data analysis: Climate Change, Disaster Management, Monitoring Critical Infrastructures, Transportation
Paper Submission:
We invite papers discussing novel research and ideas without substantial overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Submitted papers can be of two types:
1. Regular Research Papers: These papers should report original research results or significant case studies. They should be at most 10 pages.
2. Position Papers: These papers should report novel research directions or identify challenging problems. They should be at most 4 pages.
Manuscripts should be submitted in PDF format and formatted using the ACM camera-ready templates. Submissions are limited to 10 pages. All submissions should clearly present the author information including the names of the authors, the affiliations and the emails. The papers should be submitted through the workshop submission system. One author per accepted workshop paper is required to register for both the main SIGSPATIAL conference and the workshop, to attend the workshop, and to present the accepted paper in the workshop.
Submission Website:
https://easychair.org/conferences/?conf=bigspatial2020
Important Dates:
Paper Submission: August 31, 2020
Notification of Acceptance: September 21, 2020
Camera Ready Paper Due: October 5, 2020
All submissions are due at 11:59 PM Pacific Standard Time.
Journal Promotion
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| Acta Koreana (Acta Koreana) |
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| Acta Via Serica (AVS) |
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| Computers and Concrete (CAC) |
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| Journal of Information Processing Systems (JIPS) |
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| Journal of Internet Computing and Services (KSII - JICS) |
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| Journal of Smart Tourism (Smart Tourism) |
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| Membrane and Water Treatment (MWT) |
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| Wind and Structures, An International Journal (Wind and Structures) |
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