Scope

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 spatiotemporal data is one of the 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 unprecedented access to earth science data for scientists from different disciplines, interested in studying the complementary nature of different parameters. The immediate availability of airbone sensor technologies such as UAVs has now allowed for real-time analysis in areas such as disaster management. The volume, variety and velocity at which this data is collected present unique challenges in both their analysis and management.

The 12th 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 toward 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 spatiotemporal 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 spatiotemporal 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 spatiotemporal data. The topics include:

* Scalable analysis algorithms for spatial and spatiotemporal data mining
* Novel applications on high-performance computing frameworks (Clusters, GPU, cloud, Grid) for large-scale spatial and spatiotemporal analysis
* Performance studies comparing clouds, grids, and clusters for spatial and spatiotemporal 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