Privacy and Security Challenges in GIS
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Postgres
12. The GiST Indexing Project (1999) GiST: A Generalized Search Tree for Secondary Storage. http://gist.cs.berkeley.edu. Accessed 1 Jan 2007 13. Sigaev, T., Bartunov, O. (2006) GiST for PostgreSQL. http:// www.sai.msu.su/~megera/postgres/gist. Accessed 1 Jan 2007 14. Hellerstein, J.M., Naughton, J.F., Pfeffer, A.: Generalized search trees for database systems. In: Proceedings of the 21st International Conference on Very Large Data Bases, Zürich, Switzerland, 11–15 Sept 1995 15. Guttman, A.: R-trees: a dynamic index structure for spatial searching. In: Proceedings of ACM SIGMOD International Conference on Management of Data Boston, MA, 18–21 June 1984 16. Nebert, D.D. (2004) Developing Spatial Data Infrastructures: The SDI Cookbook, Version 2.0. http://www.gsdi.org/pubs/ cookbook/cookbookV2.0.pdf. Accessed 12 Oct 2005 17. ISO/IEC: ISO/IEC 13249-3: Information Technology—Database Languages—SQL Multimedia and Application Packages. Part 3: Spatial (2006)
Postgres PostGIS
Preference Structure Multicriteria Decision Making, Spatial
Prism, Network Time Time Geography
Prism, Space-Time Time Geography
Privacy Cloaking Algorithms for Location Privacy
Privacy and Security Challenges in GIS B HAVANI T HURAISINGHAM, L ATIFUR K HAN , G ANESH S UBBIAH , A SHRAFUL A LAM, M URAT K ANTARCIOGLU Department of Computer Science, The University of Texas at Dallas, Dallas, TX, USA Synonyms Geographic data management
Definition Geospatial data refers to information about shapes and extent of geographic entities along with their locations on the surface of the earth. This definition, however, is often extended to include any physical or logical entity as long as it exhibits one or more geographic characteristics such as topology of a proposed highway infrastructure or location of a moving vehicle. Geospatial data management pertains to the acquisition, manipulation and dissemination of geospatial data under a set of guidelines. It has numerous applications including counter-terrorism, climate-change detection and space exploration. For example, global warming has been one of the major climate changing events in recent years. The significance of global warming lies in the severe impact that even small climate changes could cause on weather patterns, ecosystems and other activities. Understanding the causes and impacts of global warming is therefore critical. Central to this mission are the thousands of stations capturing vast amounts of geospatially referenced climate and weather data, both on and off the Earth. The data is stored in hundreds of geographically distributed databases, often in different formats. Even more problematic is that the data lack a common semantics, and as a result tends to take on different meanings in different places. These two problems are major impediments to scientists in their ability to coherently and consistently analyze the data, and investigate global trends, make predictions, and so forth. One way to effectively analyze and detect climate changes is to apply knowledge discovery t
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