{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/100389"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/100389","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"OPM model-based integration of multiple data repositories","abstract":"Data integration is at the heart of a significant portion of current information system implementations. As companies continue to move towards a diverse, growing set of Commercial Off the Shelf (COTS) applications to fulfill their information technology needs, the need to integrate data between them continues to increase. In addition, these diverse application portfolios are becoming more geographically dispersed as more software is provided using the Software as a Service (SaaS) model, and companies continue the pattern of moving their internal data centers to cloud-based computing. As the growth of data integration activities continues, several prominent data integration patterns have emerged, and commercial software packages have been created that covers each of the patterns below: 1. Bulk and/or batch data extraction and delivery (ETL, ELT, etc.); 2. Messaging / Message-oriented data movement; 3. Granular, low-latency data capture and propagation (data synchronization). As the data integration landscape within an organization, and between organizations, becomes larger and more complex, opportunities exist to streamline aspects of the data integrating process not covered by current toolsets including: 1. Extensibility by third parties. Many COTS integration toolsets today are difficult if not impossible to extend by third parties; 2. Capabilities to handle different types of structured data from relational to hierarchical to graph models; 3. Enhanced modeling capabilities through use of data visualization and modeling techniques and tools; 4. Capabilities for automated unit testing of integrations; 5. A unified toolset that covers all three patterns, allowing an enterprise to implement the pattern that best suites business needs for the specific scenario; 6. A Web-based toolset that allows configuration, management and deployment via Web-based technologies allowing geographical indifference for application deployment and integration. While discussing these challenges with a large Fortune 500 client, they expressed the need for an enhanced data integration toolset that would allow them to accomplish such tasks. Given this request, the Object Process Methodology (OPM) and the Opcat toolset were used to begin design of a data integration toolset that could fulfill these needs. As part of this design process, lessons learned covering both the use of OPM in software design projects as well as enhancement requests for the Opcat toolset were documented.","abstract_html":"Data integration is at the heart of a significant portion of current information system implementations. As companies continue to move towards a diverse, growing set of Commercial Off the Shelf (COTS) applications to fulfill their information technology needs, the need to integrate data between them continues to increase. In addition, these diverse application portfolios are becoming more geographically dispersed as more software is provided using the Software as a Service (SaaS) model, and companies continue the pattern of moving their internal data centers to cloud-based computing. As the growth of data integration activities continues, several prominent data integration patterns have emerged, and commercial software packages have been created that covers each of the patterns below: 1. Bulk and/or batch data extraction and delivery (ETL, ELT, etc.); 2. Messaging / Message-oriented data movement; 3. Granular, low-latency data capture and propagation (data synchronization). As the data integration landscape within an organization, and between organizations, becomes larger and more complex, opportunities exist to streamline aspects of the data integrating process not covered by current toolsets including: 1. Extensibility by third parties. Many COTS integration toolsets today are difficult if not impossible to extend by third parties; 2. Capabilities to handle different types of structured data from relational to hierarchical to graph models; 3. Enhanced modeling capabilities through use of data visualization and modeling techniques and tools; 4. Capabilities for automated unit testing of integrations; 5. A unified toolset that covers all three patterns, allowing an enterprise to implement the pattern that best suites business needs for the specific scenario; 6. A Web-based toolset that allows configuration, management and deployment via Web-based technologies allowing geographical indifference for application deployment and integration. While discussing these challenges with a large Fortune 500 client, they expressed the need for an enhanced data integration toolset that would allow them to accomplish such tasks. Given this request, the Object Process Methodology (OPM) and the Opcat toolset were used to begin design of a data integration toolset that could fulfill these needs. As part of this design process, lessons learned covering both the use of OPM in software design projects as well as enhancement requests for the Opcat toolset were documented.","abstract_has_math":false,"creators":["Wilmer, Greg"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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As the data integration landscape within an organization, and between organizations, becomes larger and more complex, opportunities exist to streamline aspects of the data integrating process not covered by current toolsets including: 1. Extensibility by third parties. Many COTS integration toolsets today are difficult if not impossible to extend by third parties; 2. Capabilities to handle different types of structured data from relational to hierarchical to graph models; 3. Enhanced modeling capabilities through use of data visualization and modeling techniques and tools; 4. Capabilities for automated unit testing of integrations; 5. A unified toolset that covers all three patterns, allowing an enterprise to implement the pattern that best suites business needs for the specific scenario; 6. A Web-based toolset that allows configuration, management and deployment via Web-based technologies allowing geographical indifference for application deployment and integration. While discussing these challenges with a large Fortune 500 client, they expressed the need for an enhanced data integration toolset that would allow them to accomplish such tasks. Given this request, the Object Process Methodology (OPM) and the Opcat toolset were used to begin design of a data integration toolset that could fulfill these needs. As part of this design process, lessons learned covering both the use of OPM in software design projects as well as enhancement requests for the Opcat toolset were documented."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M. in Engineering and Management"]},{"key":"dc:title","label":"Title","values":["OPM model-based integration of multiple data repositories"]}]}],"canonical_facts":{"dc:contributor.advisor":["Dov Dori."],"dc:contributor.department":["Massachusetts Institute of Technology. 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In addition, these diverse application portfolios are becoming more geographically dispersed as more software is provided using the Software as a Service (SaaS) model, and companies continue the pattern of moving their internal data centers to cloud-based computing. As the growth of data integration activities continues, several prominent data integration patterns have emerged, and commercial software packages have been created that covers each of the patterns below: 1. Bulk and/or batch data extraction and delivery (ETL, ELT, etc.); 2. Messaging / Message-oriented data movement; 3. Granular, low-latency data capture and propagation (data synchronization). As the data integration landscape within an organization, and between organizations, becomes larger and more complex, opportunities exist to streamline aspects of the data integrating process not covered by current toolsets including: 1. Extensibility by third parties. 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Given this request, the Object Process Methodology (OPM) and the Opcat toolset were used to begin design of a data integration toolset that could fulfill these needs. As part of this design process, lessons learned covering both the use of OPM in software design projects as well as enhancement requests for the Opcat toolset were documented."],"dc:description.degree":["S.M. in Engineering and Management"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/100389"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Engineering Systems Division.","System Design and Management Program."],"dc:title":["OPM model-based integration of multiple data repositories"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:22:22Z"}