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dc.contributor.advisorHoward J. Herzog and Stuart E. Madnick.en_US
dc.contributor.authorCheng, David Su-Kai, 1978-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2005-06-02T19:08:50Z
dc.date.available2005-06-02T19:08:50Z
dc.date.copyright2004en_US
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/17909
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.en_US
dc.descriptionIncludes bibliographical references (p. 64-69).en_US
dc.description.abstractDatabases and analysis tools currently being used to study carbon dioxide capture and storage (CCS) options are managed by diverse organizations and are heterogeneous in format. Tools to study the various components of a CCS system have been developed in several fields including chemistry, geology, and economics. Data being used to run analyses are being obtained from an equally diverse set of organizations, from data collected for environmental assessments to data on oil and gas exploration. These variations in tools and data cause complications in systems-level analyses, resulting in additional effort expended in data collection and opportunities for human error. A geographic information system has been implemented to automate and support robust studies of both component and system options. Context management and information integration techniques have been designed into the system. The system improves the availability and quality of information by automatically managing the distributed and heterogeneous data sources. The resulting information is being used to advance research and development of CCS systems through efforts such as the NETL sponsored Regional Carbon Sequestration Partnerships. This paper will present an overview of the system and initial results of its application to CCS-related data.en_US
dc.description.statementofresponsibilityby David Su-Kai Cheng.en_US
dc.format.extent83 p.en_US
dc.format.extent4476470 bytes
dc.format.extent4476276 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectTechnology and Policy Program.en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleIntegration of distributed and heterogeneous information for public-private policy analysesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentTechnology and Policy Program
dc.identifier.oclc56726945en_US


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