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Abstract
CyberGIS – defined as cyberinfrastructure-based geographic information systems (GIS) – has emerged as a new generation of GIS representing an important research direction for both cyberinfrastructure and geographic information science. This study introduces a 5-year effort funded by the US National Science Foundation to advance the science and applications of CyberGIS, particularly for enabling the analysis of big spatial data, computationally intensive spatial analysis and modeling (SAM), and collaborative geospatial problem-solving and decision-making, simultaneously conducted by a large number of users. Several fundamental research questions are raised and addressed while a set of CyberGIS challenges and opportunities are identified from scientific perspectives. The study reviews several key CyberGIS software tools that are used to elucidate a vision and roadmap for CyberGIS software research. The roadmap focuses on software integration and synthesis of cyberinfrastructure, GIS, and SAM by defining several key integration dimensions and strategies. CyberGIS, based on this holistic integration roadmap, exhibits the following key characteristics: high-performance and scalable, open and distributed, collaborative, service-oriented, user-centric, and community-driven. As a major result of the roadmap, two key CyberGIS modalities – gateway and toolkit – combined with a community-driven and participatory approach have laid a solid foundation to achieve scientific breakthroughs across many geospatial communities that would be otherwise impossible.
Acknowledgements
This material is based in part upon work supported by the U.S. National Science Foundation under grant numbers OCI-1047916, BCS-0846655, EAR-0930731, EAR-0930643, and EIA-0325916. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors are grateful for insightful comments on the earlier drafts received from Editor May Yuan and four anonymous reviewers, Sriram Krishnan, Anand Padmanabhan, Wenwu Tang, Ranga Raju Vatsavai, and Nancy Wilkins-Diehr. Assistance received from Anand Padmanabhan, Wenwu Tang, Yanli Zhao on data processing and graphics preparation is greatly appreciated.
Notes
1. Parts of PySAL are wrapped in a graphical user interface and released as freestanding binaries. For example, the spatial econometric functionality in PySAL is released as the GeoDaSpace package (http://geodacenter.asu.edu/software).