Digital Government: Knowledge Management Over Time-Varying Geospatial Datasets

Spatially-related data is collected by many government agencies in various formats and for various uses. This project seeks to facilitate the integration of these data, thus providing new uses. This will require the development of a knowledge management framework to provide syntax, context, and semantics, as well as exploring the introduction of time-varying data into the framework. Education and outreach will be part of the project through the development of an on-line short courses related to data integration in the area of geographical information systems. The grantees will be working with government partners (National Imagery and Mapping Agency, the National Agricultural Statistics Service, and the US Army Topographic Engineering Center), as well as an industrial organization, Base Systems, and the non-profit OpenGIS Consortium, which works closely with vendors of GIS products

Index Based Processing of Semi-Restrictive Temporal Joins

Temporal joins are important but very costly operations. While a temporal join can involve the whole time (and/or key) domain, we consider the more general case where the join is defined by some time-key rectangle from the whole space (i.e., when the user is interested in joining portions of the –usually large – temporal data). In the most restrictive join, objects (within this rectangle) are joined together based on key equality and interval intersection. This paper concentrates on semi-restrictive joins, i.e., when either the key equality (equi-join) or the interval intersection (timejoin) predicates are used. Given the large relations created by the ever increasing time dimension, we assume that each temporal relation is indexed and examine efficient ways to process semi-restrictive temporal joins. Utilizing an inde