Lowering Barriers to Parallelizing Geospatial Data Processing
Abstract: Cartographic modeling represents a widely adopted framework for spatial data processing underpinning many commercial and open source geographic information systems (GIS). In this talk I will discuss a new methodological framework called parallel cartographic modeling for parallelizing spatial data processing and a new programming language for GIS. The parallel cartographic modeling language (PCML) is designed for usability, programmability, and scalability. PCML is a domain-specific language implemented in Python for the domain of GIS. A key feature of PCML is that it supports automatic parallelization of cartographic modeling codes. I will highlight recent work in trying to make parallel computing more accessible through PCML and share promising directions for future research with the ultimate aim of making parallel geospatial data processing so straightforward that it becomes commonplace in GIS.
Bio: Eric Shook is an Assistant Professor in the Department of Geography, Environment, and Society at the University of Minnesota. His research is situated at the intersection of geographic information science and computational science with particular emphasis in the areas of cyberGIS, data-intensive spatio-temporal analytics and modeling, and geo-enabled social media. He is engaged in a broad range of interdisciplinary projects ranging from analyzing risk amplification using social media data to creating a computational Paleoscape model by modeling paleoclimate, paleovegetation, and hunter-gatherer behaviors for human origins research.