Christian Hennig, H. Eisenmann, A. Viehl, O. Bringmann
{"title":"从系统工程工件中派生概念数据模型的方法","authors":"Christian Hennig, H. Eisenmann, A. Viehl, O. Bringmann","doi":"10.5220/0005676604970508","DOIUrl":null,"url":null,"abstract":"This paper presents a novel methodology for deriving Conceptual Data Models in the scope of Model-based Systems Engineering. Based on an assessment of currently employed methodologies, substantial limitations of the state of the art are identified. Consequently, a new methodology, overcoming present shortcomings, is elaborated, containing detailed and prescriptive guidelines for deriving conceptual data models used for representing engineering data in a multi-disciplinary design process. For highlighting the applicability and benefits of the approach, the derivation of a semantically strong conceptual data model in the context of Model-based Space Systems Engineering is presented as a case study.","PeriodicalId":360028,"journal":{"name":"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A methodology for deriving Conceptual Data Models from Systems Engineering artefacts\",\"authors\":\"Christian Hennig, H. Eisenmann, A. Viehl, O. Bringmann\",\"doi\":\"10.5220/0005676604970508\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel methodology for deriving Conceptual Data Models in the scope of Model-based Systems Engineering. Based on an assessment of currently employed methodologies, substantial limitations of the state of the art are identified. Consequently, a new methodology, overcoming present shortcomings, is elaborated, containing detailed and prescriptive guidelines for deriving conceptual data models used for representing engineering data in a multi-disciplinary design process. For highlighting the applicability and benefits of the approach, the derivation of a semantically strong conceptual data model in the context of Model-based Space Systems Engineering is presented as a case study.\",\"PeriodicalId\":360028,\"journal\":{\"name\":\"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0005676604970508\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005676604970508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A methodology for deriving Conceptual Data Models from Systems Engineering artefacts
This paper presents a novel methodology for deriving Conceptual Data Models in the scope of Model-based Systems Engineering. Based on an assessment of currently employed methodologies, substantial limitations of the state of the art are identified. Consequently, a new methodology, overcoming present shortcomings, is elaborated, containing detailed and prescriptive guidelines for deriving conceptual data models used for representing engineering data in a multi-disciplinary design process. For highlighting the applicability and benefits of the approach, the derivation of a semantically strong conceptual data model in the context of Model-based Space Systems Engineering is presented as a case study.