{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/30908"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/30908","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"An indexing-based approach for rapid and efficient product information integration and retrieval","abstract":"Throughout a product's lifecycle, multiple stakeholders interact with each other to generate large amounts of disparate information about it. All of modern product development, particularly, in Original Equipment Manufacturers (OEMs), involves integrating such information that exists in a number of databases into a cohesive decision support solution, for various activities, such as Resource Management and Prototype Management. This integration is typically handled in the current environment using ad-hoc and manual combinations of data to address specific queries. This approach is error-prone, time consuming and limiting because every new analysis requires the definition of a specific combination of data. In this paper, as first step towards the ideal dynamic system for information integration and retrieval, we present a novel framework called CachingDB that consists of a centered database built of optimized data tables and index structures from the underlying product databases. We exemplify the multiple challenges, such as disparity of data types (structured, unstructured, and geometric) within and across the databases, redundancy of information, huge data set, rapid changes to the underlying data, and a wide variety of complex queries. We demonstrate the issues by and conclude with results of application to structured data (non-shape) stored in different databases for Prototype Management, i.e., managing components, costs, and schedules in building Vehicle Prototypes.","abstract_html":"Throughout a product's lifecycle, multiple stakeholders interact with each other to generate large amounts of disparate information about it. All of modern product development, particularly, in Original Equipment Manufacturers (OEMs), involves integrating such information that exists in a number of databases into a cohesive decision support solution, for various activities, such as Resource Management and Prototype Management. This integration is typically handled in the current environment using ad-hoc and manual combinations of data to address specific queries. This approach is error-prone, time consuming and limiting because every new analysis requires the definition of a specific combination of data. In this paper, as first step towards the ideal dynamic system for information integration and retrieval, we present a novel framework called CachingDB that consists of a centered database built of optimized data tables and index structures from the underlying product databases. We exemplify the multiple challenges, such as disparity of data types (structured, unstructured, and geometric) within and across the databases, redundancy of information, huge data set, rapid changes to the underlying data, and a wide variety of complex queries. We demonstrate the issues by and conclude with results of application to structured data (non-shape) stored in different databases for Prototype Management, i.e., managing components, costs, and schedules in building Vehicle Prototypes.","abstract_has_math":false,"creators":["Fan, Xueting"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Dutta, Debasish","Patil, Lalit"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-05-22T00:14:31Z","date_published":"2012-05-22T00:14:31Z","updated_at":"2026-07-22T22:25:29Z","subjects":["Information Integration","Data Retrieval","Indexing"],"languages":["en"],"rights":["Copyright 2012 Xueting Fan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/30908","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dutta, Debasish","Patil, Lalit"]},{"key":"dc:creator","label":"Author","values":["Fan, Xueting"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2012-05-22T00:14:31Z","2012-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Information Integration","Data Retrieval","Indexing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2012 Xueting Fan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/30908"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Throughout a product's lifecycle, multiple stakeholders interact with each other to generate large amounts of disparate information about it. 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We exemplify the multiple challenges, such as disparity of data types (structured, unstructured, and geometric) within and across the databases, redundancy of information, huge data set, rapid changes to the underlying data, and a wide variety of complex queries. We demonstrate the issues by and conclude with results of application to structured data (non-shape) stored in different databases for Prototype Management, i.e., managing components, costs, and schedules in building Vehicle Prototypes.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-04-24T21:01:44Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Fan_Xueting.pdf: 1636114 bytes, checksum: 605ae4821ff30a5f34f47b208b3fea94 (MD5)","Made available in DSpace on 2012-05-22T00:14:31Z (GMT). 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This integration is typically handled in the current environment using ad-hoc and manual combinations of data to address specific queries. This approach is error-prone, time consuming and limiting because every new analysis requires the definition of a specific combination of data. In this paper, as first step towards the ideal dynamic system for information integration and retrieval, we present a novel framework called CachingDB that consists of a centered database built of optimized data tables and index structures from the underlying product databases. We exemplify the multiple challenges, such as disparity of data types (structured, unstructured, and geometric) within and across the databases, redundancy of information, huge data set, rapid changes to the underlying data, and a wide variety of complex queries. 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