Semantic Integration and Knowledge Discovery for Environmental Research

Zhiyuan Chen, Aryya Gangopadhyay, George Karabatis, Michael McGuire, Claire Welty
2007 Journal of Database Management  
Environmental research and knowledge discovery both require extensive use of data stored in various sources and created in different ways for diverse purposes. We describe a new metadata approach to elicit semantic information from environmental data and implement semanticsbased techniques to assist users in integrating, navigating, and mining multiple environmental data sources. Our system contains specifications of various environmental data sources and the relationships that are formed among
more » ... them. User requests are augmented with semantically related data sources and automatically presented as a visual semantic network. In addition, we present a methodology for data navigation and pattern discovery using multi-resolution browsing and data mining. The data semantics are captured and utilized in terms of their patterns and trends at multiple levels of resolution. We present the efficacy of our methodology through experimental results. IntroDuctIon The urban environment is formed by complex interactions between natural and human systems. Studying the urban environment requires the collection and analysis of very large datasets that span many disciplines, have semantic (including spatial and temporal) differences and interdependencies, are collected and managed by multiple organizations, and are stored in varying formats. Scientific knowledge discovery is often hindered because of challenges in the integration and navigation of these disparate data. Furthermore, 44
doi:10.4018/jdm.2007010103 fatcat:qlyhhfxamzce3ize6pt2tvrifq