Building appropriate GIS enabled analytical tools for businesses and social sciences: current initiatives and future directions
by KAM Tin Seong
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Date: Time: Venue: |
14 December 2007 (Friday)
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KAM Tin Seong |
We look forward to seeing you at this research seminar. |
Abstract
More than 80% of organisation data are location related - the locations where transactions are done, where retailers are found, and of customers who buy their products. Recently, there is an increasing interest among the business community and social scientist to use GIS to enhance decision making process at both strategic and operational levels. The use of GIS in business and policy research, however, tends to confine to simple map visualization. This is mainly due to the general lack of readily accessible, easy to use, and mathematically robust spatial statistical analysis functions available in the commercial of the shelf GIS software. In view of this, a research effort devotes to the development, implementation and application of spatial statistics methods within a GIS environment has been initiated. The mission of this research effort is to increase the knowledge and use of geographical data and spatial statistics techniques, and enable public and private sector to avoid problems related to relying on non-spatial methods in research areas where space matters.
In this talk, I will share with you our journey in achieving the above mission. It starts with an overview of GIS and its various components. This is follow by a detail discussion on the effort to integrate spatial statistics method within a GIS environment. Using real world examples, I will then demonstrate how these GIS-enabled spatial statistics functions have helped business community and social scientist in improving their understanding of the market scenario at the micro-level. The talk concludes by highlighting the challenges that are faced in developing GIS enabled spatial statistics methods and the future research directions.
Biography
Kam Tin Seong is Practice Associate Professor of Information Systems at the School of Information Systems, Singapore Management University. Prac Assoc Prof Kam has more than twenty years of experience in both the geospatial industry as well as the academia. His teaching and research interests are in GIS for Business, location intelligence and spatial optimisation, Internet Mapping and GIS services, geo-business data mining, and Spatial OLAP. Prior to joining SMU he was the Manager, Application and Educational Services, ESRI Pte. Ltd., one of the world leading GIS company.