David T. McWherter, Mitchell Peabody, A. Shokoufandeh, W. Regli
{"title":"Database techniques for archival of solid models","authors":"David T. McWherter, Mitchell Peabody, A. Shokoufandeh, W. Regli","doi":"10.1145/376957.376968","DOIUrl":null,"url":null,"abstract":"This paper presents techniques for managing solid models in modern relational database management systems. Our goal is to enable support for traditional database operations (sorting, distance metrics, range queries, nearest neighbors, etc) on large databases of solid models. As part of this research, we have developed a number of novel storage and retrieval strategies that extend the state-of-the-art in database research as well as change the way in which solid modeling software developers and design and manufacturing enterprises view CAD-centric data management problems.\nPast research and current commercial systems for engineering information management and Product Data Management (PDM) have predominantly taken annotation and document-based approaches—where the solid modeling data itself is simply stored as a related file to other project documents. Research in CAD and engineering databases has produced great advances, such as representation schemas for STEP-based data elements, however existing technologies stop short of enabling content-based and semantic retrieval of solid modeling data of the types now available for other higher-dimensional media (images, audio and video).\nOur approach encodes solid model BRep information as a Model Signature Graph. We demonstrate how Model Signature Graphs can be used for topological similarity assessment of solid models and enable clustering for data mining of a large design repositories. We believe this work will begin to bridge the solid modeling and database communities, enabling new paradigms for interrogation of CAD datasets.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"65","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Smart Media and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/376957.376968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 65
Abstract
This paper presents techniques for managing solid models in modern relational database management systems. Our goal is to enable support for traditional database operations (sorting, distance metrics, range queries, nearest neighbors, etc) on large databases of solid models. As part of this research, we have developed a number of novel storage and retrieval strategies that extend the state-of-the-art in database research as well as change the way in which solid modeling software developers and design and manufacturing enterprises view CAD-centric data management problems.
Past research and current commercial systems for engineering information management and Product Data Management (PDM) have predominantly taken annotation and document-based approaches—where the solid modeling data itself is simply stored as a related file to other project documents. Research in CAD and engineering databases has produced great advances, such as representation schemas for STEP-based data elements, however existing technologies stop short of enabling content-based and semantic retrieval of solid modeling data of the types now available for other higher-dimensional media (images, audio and video).
Our approach encodes solid model BRep information as a Model Signature Graph. We demonstrate how Model Signature Graphs can be used for topological similarity assessment of solid models and enable clustering for data mining of a large design repositories. We believe this work will begin to bridge the solid modeling and database communities, enabling new paradigms for interrogation of CAD datasets.