Paper
26 October 2007 Semantics-enabled knowledge management for global Earth observation system of systems
Author Affiliations +
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. 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 procedures that implement the policies specific to a country. Earth Observations (EO) are obtained from a multitude of sources and requires 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 in a GEOSS context will 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 dependent on the resolution of conflicts arising from a variety of areas. Modularization is inevitable in distributed environments to facilitate flexible and efficient reuse of existing ontologies. Therefore, we propose a framework for modular ontologies based knowledge management approach for GEOSS and present methods to enable efficient reasoning in such systems.
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Roger L. King, Surya S. Durbha, and Nicolas H. Younan "Semantics-enabled knowledge management for global Earth observation system of systems", Proc. SPIE 6744, Sensors, Systems, and Next-Generation Satellites XI, 674429 (26 October 2007); https://doi.org/10.1117/12.733159
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KEYWORDS
Distributed computing

Data modeling

Computing systems

Data archive systems

Knowledge management

Data integration

Satellites

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