ACQUIRE: Agent-based Complex QUerying and Information Retrieval Engine
The heterogeneous, distributive, and voluminous nature of NASA¿s Earth science data archives impose severe constraints on meeting the diverse requirements of thousands of users who analyze the data. Additionally, communication bandwidth limitations, time constraints, and a multiplicity of archives impose further restrictions on users and systems. What is required is a reliable, robust and efficient technique that can be integrated within NASA¿s existing data servers for enhancing query support to archive users. We propose to design and prototype an Agent-based Complex QUerying and Information Retrieval Engine (ACQUIRE) for heterogeneous and distributed Earth science data sources over the Internet, while maintaining the autonomy of individual data sources. ACQUIRE translates a user query to a set of sub-queries by deploying a combination of planning and traditional database query optimization techniques. ACQUIRE first spawns a set of intelligent autonomous mobile search agents corresponding to these sub-queries for retrieving data from several Distributed Active Archive Centers (DAACs) (e.g., such as the Alaska SAR Facility (ASF)). The engine then filters and merges data from these agents and returns the answers to the query. The proposed approach will build on existing data servers and meta-database catalogs of NASA¿s Earth Observing System Data and Information System (EOSDIS).
Small Business Information at Submission:
Dr. Subrat 1. Das
Dr. Greg L Zacharias
Charles River Analytics Inc.
625 Mount Auburn Street Cambridge, MA 02138
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