A semantic data dictionary method for database schema integration in CIESIN

Abstract

CIESIN (Consortium for International Earth Science Information Network) is funded by NASA to investigate the technology necessary to integrate and facilitate the interdisciplinary use of Global Change information. A clear of this mission includes providing a link between the various global change data sets, in particular the physical sciences and the human (social) sciences.The typical scientist using the CIESIN system will want to know how phenomena in an outside field affects his/her work. For example, a medical researcher might ask: how does air‐quality effect emphysema? This and many similar questions will require sophisticated semantic data integration. The researcher who raised the question may be familiar with medical data sets containing emphysema occurrences. But this same investigator may know little, if anything, about the existance or location of air‐quality data. It is easy to envision a system which would allow that investigator to locate and perform a ‘‘join’’ on two data sets, one containing emphysema cases and the other containing air‐quality levels. No such system exists today.One major obstacle to providing such a system will be overcoming the heterogeneity which falls into two broad categories. ‘‘Database system’’ heterogeneity involves differences in data models and packages. ‘‘Data semantic’’ heterogeneity involves differences in terminology between disciplines which translates into data semantic issues, and varying levels of data refinement, from raw to summary.Our work investigates a global data dictionary mechanism to facilitate a merged data service. Specially, we propose using a semantic tree during schema definition to aid in locating and integrating heterogeneous databases.