Digital Space Systems Engineering through Semantic Data Models

Tobias Hoppe, H. Eisenmann, A. Viehl, O. Bringmann
{"title":"Digital Space Systems Engineering through Semantic Data Models","authors":"Tobias Hoppe, H. Eisenmann, A. Viehl, O. Bringmann","doi":"10.1109/ICSA.2017.35","DOIUrl":null,"url":null,"abstract":"Model-based Systems Engineering requires an intuitive semantically strong data model to enable precise data specification and provide the foundation for fruitful data analyses during data evolution. This paper presents an approach to use the Web Ontology Language (OWL) for specifying a Conceptual Data Model (CDM) being transformed into a format understandable by the Eclipse Modeling Framework (EMF) to profit from powerful data handling and knowledge management functions during runtime. Coalescing OWL with EMF brings up the strength of both approaches leading to considerably better data models with less failure potential and reveal notably more analysis potential by using a common data model specification. This approach also enables the direct application of reasoning functionality for automatic inference of several pieces of knowledge and automatic checks as illustrated by examples from aerospace industry.","PeriodicalId":6599,"journal":{"name":"2017 IEEE International Conference on Software Architecture (ICSA)","volume":"27 1","pages":"93-96"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Software Architecture (ICSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSA.2017.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Model-based Systems Engineering requires an intuitive semantically strong data model to enable precise data specification and provide the foundation for fruitful data analyses during data evolution. This paper presents an approach to use the Web Ontology Language (OWL) for specifying a Conceptual Data Model (CDM) being transformed into a format understandable by the Eclipse Modeling Framework (EMF) to profit from powerful data handling and knowledge management functions during runtime. Coalescing OWL with EMF brings up the strength of both approaches leading to considerably better data models with less failure potential and reveal notably more analysis potential by using a common data model specification. This approach also enables the direct application of reasoning functionality for automatic inference of several pieces of knowledge and automatic checks as illustrated by examples from aerospace industry.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于语义数据模型的数字空间系统工程
基于模型的系统工程需要一个直观的语义强大的数据模型来实现精确的数据规范,并为数据演化过程中富有成效的数据分析提供基础。本文提出了一种使用Web本体语言(OWL)来指定概念数据模型(CDM)的方法,该概念数据模型(CDM)被转换为Eclipse建模框架(EMF)可以理解的格式,从而在运行时从强大的数据处理和知识管理功能中获益。将OWL与EMF结合在一起,可以提高两种方法的强度,从而产生更好的数据模型,减少故障可能性,并通过使用公共数据模型规范显着显示更多的分析潜力。这种方法还可以直接应用推理功能,对多个知识片断进行自动推理和自动检查,如航空航天工业中的示例所示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Message from the ICSA 2022 General Chairs and Program Chairs Software Architecture: 16th European Conference, ECSA 2022, Prague, Czech Republic, September 19–23, 2022, Proceedings Software Architecture: 15th European Conference, ECSA 2021 Tracks and Workshops; Växjö, Sweden, September 13–17, 2021, Revised Selected Papers Software Architecture: 15th European Conference, ECSA 2021, Virtual Event, Sweden, September 13-17, 2021, Proceedings Employment of Optimal Approximations on Apache Hadoop Checkpoint Technique for Performance Improvements
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1