BigSpatial 2018 - 7th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data

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 spatiotemporal 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 7th 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.
The main motivation for this workshop stems from the increasing need for a forum to exchange ideas and recent research results, and to facilitate collaboration and dialog between academia, government, and industrial stakeholders.
We solicit high quality papers in the general areas of data analytics for large scale geospatial data.
All submitted papers will be peer reviewed. If accepted, at least one of the authors must attend the workshop to present the work. Selected accepted papers will be recommended for submission to special issues of journals.
Topics of Interest
The workshop welcomes contributions in the area of large scale analytics for spatial and spatio-temporal data. The topics include:
Scalable analysis algorithms for spatial and spatio-temporal data mining
Novel applications on high performance computing frameworks (Clusters, GPU, cloud, Grid) for large scale spatial and spatio-temporal analysis
Performance studies comparing clouds, grids, and clusters for spatial and spatio-temporal analytics
Novel indexing methods for massive geospatial data
Visualization of massive geospatial data
Customizations and extensions of existing software infrastructures such as Hadoop for spatial, and spatiotemporal data mining
Applications of big data analysis: Climate Change, Disaster Management, Monitoring Critical Infrastructures, Transportation