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Mark Gahegan’s research interests are broad, covering most aspects of GIS, visualization, philosophy of science, semantics and pragmatics,e-science, representation of scientific knowledge, geocomputation, digital remote sensing, artificial intelligence tools, spatial analysis, Voronoi diagrams, spatial databases and algorithms, and spatial reasoning. He has also dabbled in mineral potential mapping, epidemiology, habitat analysis,bio-informatics, e-learning and predicting land-cover change.

Mark is currently director of the Centre for eResearch at the University of Auckland, a group that aids researchers to tackle challenging computational research by providing scientific computing and software engineering expertise, patternable services such as virtualised compute platforms, research data services, visualisation and analytics, and educational offerings to upskill the research community.

Mark came to Auckland from Penn State University, where he was involved in a number of funded research projects, from ontology capture to spatial epidemiology. He also directed a new Professional Masters degree program in GIS, developed at the Dutton e-Education Institute at Penn State, and delivered through World Campus.

Our GIS is (still) too small

The Geographers who led the Quantitative Revolution did not have a GIS to help them. They learned the skills and built the tools they needed to address their problems of choice, and they did not expect anyone else to build the tools for them. In the meantime, GIS have been successfully applied over the last 30 years to many geographical problems. But technologies and associated theory can become limiting if they end up defining how we see the world and what we believe are worthy and tractable research problems. This talk explores some of the limitations currently impacting GISystems and GIScience from the perspective of technology and community, contrasting GIScience with other informatics communities and their practices. It explores several themes:

  • GIScience and the informatics revolution
  • the lack of a community-owned innovation platform for GIScience research
  • the computational limitations imposed by desktop computing and the inability to scale up analysis
  • the continued failure to support the temporal dimension, and especially dynamic processes and models with feedbacks
  • the challenge of embracing a wider and more heterogeneous view of geographical representation and analysis
  • the urgent need to foster an active software development community to redress some of these shortcomings

Geocomputation, too, suffers from the lack of a shared, community platform for software development, evaluation and use. How can we change this?

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