CYBER INFRASTRUCTURE FOR COMMUNITY REMOTE SENSING

CYBER INFRASTRUCTURE FOR COMMUNITY REMOTE SENSING - CYBER...

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CYBER INFRASTRUCTURE FOR COMMUNITY REMOTE SENSING Arcot Rajasekar 1 , Reagan W. Moore 1 , Mike Wan 2 , Wayne Schroeder 2 Data Intensive Cyber Environments Center 1 University of North Carolina at Chapel Hill Chapel Hill, NC USA 27599-3360 2 University of California at San Diego La Jolla, CA USA 92093-0505 {sekar,moore,mwan,[email protected] ABSTRACT Community Remote Sensing (CRS) is an emerging field where information is collected about the environment by the general public and then integrated into collections to provide a holistic view of the environment with local details. We argue the need for a common architecture for the cyber- infrastructure that will be necessary to cater to the needs of Community Remote Sensing systems. We identify the challenges that such a cyber infrastructure (CRS-CI) has to meet and also proposed five principles as solutions to meet these challenges. Final ly, we also describe the integrated Rule Oriented Data System, a dat a grid middleware that is built upon these principles which provides an ideal and exemplar implementation for CRS-CI. Index Terms— cyber infrastructure, community remote sensing, data grids, iRODS 1. INTRODUCTION Community Remote Sensing (CRS) is an emerging field where information is collected about the environment by the general public and then integrated into collections to provide a holistic view of the environment with local details. Citizen scientists may use sophisticated sensors and tools to collect increasingly precise information about our environment. Such holistic views can serve as ground truthing for information collected by traditional sources such as satellites and deployed sensor systems. With social networking tools and crowd sourcing technologies, the data collected by the CRS systems can grow exponentially. One of the challenges of the CRS community is the problem of how to manage such data in a coherent manner such that it can enable new science and aid decision making. In this paper, we propose a cyber infrastructure that can be deployed for CRS systems that is scalable and that can organically grow to meet the needs of an expanding CRS community. We demonstrate the implementation challenges for a scalable data management system for CRS and the solutions to meet the challenges. We also propose an architecture based on the integrated Rule-Oriented Data Systems as an exemplar for the Community Resource Sensing cyber infrastructure (CRS-CI). 2. CRS-CI CHALLENGES Community-driven data collection can produce large amounts of environmental data (such as rainfall, temperature, humidity, water shed level, crop yields, etc.) including sensor-based point measurements, textual data capturing information in free form, photographic images and video. We expect these data to be distributed geo-spatially and contain metadata about the data collector, time information, and other contextual information that provide additional attributes about the collection process. As technology for data collection and data ingestion/acquisition
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This note was uploaded on 02/27/2011 for the course EE 92 taught by Professor John during the Spring '11 term at Bethany WV.

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CYBER INFRASTRUCTURE FOR COMMUNITY REMOTE SENSING - CYBER...

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