Semantics-Enabled Knowledge Management for Global Earth Observation System of Systems Surya S. Durbha, Roger L. King, Vijay P. Shah and, Nicholas H. Younan Department of Electrical and Computer Engineering GeoResources Institute Mississippi State University Mississippi State, MS 39762-9652, USA Abstract – The Global Earth Observation System of Systems (GEOSS) is a distributed system of systems built on current international cooperation efforts among existing Earth observing and processing systems. The goal is to formulate an end-to-end process that enables the collection and distribution of accurate, reliable Earth Observation data, information, products, and services to both suppliers and consumers worldwide. Earth Observations (EO) are obtained from a multitude of sources and requires tremendous efforts and coordination among different agencies and user groups to come to a shared understanding on a set of concepts involved in a domain. Semantic metadata plays a crucial role in resolving the differences in meaning, interpretation, usage of the same or related data. Also the knowledge about the geopolitical background of the originating datasets could be encoded in the metadata that would address the diversity on a global scale. In distributed environments like GEOSS modularization is inevitable. In this paper we propose a framework for modular ontologies based knowledge management approach for GEOSS in which we explore approaches on formulating smaller interconnected ontologies. This analysis is exercised in a coastal zone domain. Keywords: Coastal zone, Ontology, GEOSS, Modularization. I. INTRODUCTION The Global Earth Observation System of Systems (GEOSS) is a distributed system of systems built on current international cooperation efforts among existing Earth observing and processing systems. The goal is to formulate an end-to-end process that enables the collection and distribution of accurate, reliable Earth Observation data, information, products, and services to both suppliers and consumers worldwide. One of the critical components in the development of such systems is the ability to obtain seamless access of data across geopolitical boundaries. In order to gain support and willingness to participate by countries around the world in such an endeavor, it is necessary to devise mechanisms whereby the data and the intellectual capital is protected through strong procedures that implement the policies specific to a country. Earth Observations (EO) are obtained from a multitude of sources and requires tremendous efforts and coordination among different agencies and user groups to come to a shared understanding on a set of concepts involved in a domain. It is envisaged that the data and information deluge in a GEOSS context would be unprecedented and the current data archiving and delivery methods need to be transformed into one that allows realization of seamless interoperability. Thus EO data integration is broadly dependant on the resolution of conflicts arising from: • Data sets stemming from the same data-source with unequal updating periods. • Data sets represented in the same data-model, but acquired by different operators. • Data sets which are stored in similar, but not identical data-models. • Data sets from heterogeneous sources (across geographical boundaries), which differ in data- modeling, scale, thematic content, contexts, meaning, etc. • Data sets that are influenced by socio-political and cultural backgrounds. The resolution of such conflicts depends on the reconciliation of both syntactic and semantic heterogeneities in the data. Although the metadata standards FGDC, ISO, etc) alleviate to a large extent the syntactic heterogeneity of the data, a problem that is still not completely solved is heterogeneity in the process of converting this data into information and actionable intelligence [1]. Semantic metadata plays a crucial role in resolving the differences in meaning, interpretation, usage of the same or related data. Also the knowledge about the geopolitical background of the originating datasets could be encoded in the metadata that would address the diversity on a global scale. Ontologies are often used as interlinguas for providing interoperability; they serve as a common data format for data interchange. Ontologies help to solve the problem of implicit hidden knowledge by making the conceptualization of a domain explicit. As shown in fig 1. GEOSS consists of three Global Earth Observation System of Systems Observation Component Data Processing Component Data Exchange and Dissemination Component Fig. 1. Components of GEOSS 0-7803-9510-7/06/$20.00 © 2006 IEEE 25