{"title":"From AutomationML to AutomationQL: A By-Example Query Language for CPPS Engineering Models","authors":"M. Wimmer, Alexandra Mazak","doi":"10.1109/COASE.2018.8560448","DOIUrl":null,"url":null,"abstract":"Model-based engineering is an emerging paradigm to deal with the complexity of multi-disciplinary engineering in CPPS projects. In such projects, different kinds of models are created during the lifecycle of a production system. Automa-tionML is a promising standard to provide a unifying format to represent and connect the different engineering models. Dedicated tool support has been developed for AutomationML in the last years to create and evolve models. However, when it comes to querying AutomationML models, implementation-related query languages have to be currently used. These languages have a certain complexity as they are not directly based on the concepts of AutomationML but on the underlying technological concepts and encodings of AutomationML. This often hinders the formulation of automatically executable queries by domain experts. In this paper, we propose a dedicated query language for AutomationML called Automation Query Language (Au-tomationQL) which is directly derived from AutomationML. Using this query language, queries can be defined in a by-example manner which allows engineers to formulate queries in terms of AutomationML concepts instead of switching to an implementation-oriented query language. We illustrate how AutomationQL is defined, how queries can be formulated as well as how tool support is provided to automatically evaluate the queries and represent their results. Finally, we contrast our solution with existing query languages and derive a roadmap for future research on AutomationQL.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"51 23","pages":"1394-1399"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2018.8560448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Model-based engineering is an emerging paradigm to deal with the complexity of multi-disciplinary engineering in CPPS projects. In such projects, different kinds of models are created during the lifecycle of a production system. Automa-tionML is a promising standard to provide a unifying format to represent and connect the different engineering models. Dedicated tool support has been developed for AutomationML in the last years to create and evolve models. However, when it comes to querying AutomationML models, implementation-related query languages have to be currently used. These languages have a certain complexity as they are not directly based on the concepts of AutomationML but on the underlying technological concepts and encodings of AutomationML. This often hinders the formulation of automatically executable queries by domain experts. In this paper, we propose a dedicated query language for AutomationML called Automation Query Language (Au-tomationQL) which is directly derived from AutomationML. Using this query language, queries can be defined in a by-example manner which allows engineers to formulate queries in terms of AutomationML concepts instead of switching to an implementation-oriented query language. We illustrate how AutomationQL is defined, how queries can be formulated as well as how tool support is provided to automatically evaluate the queries and represent their results. Finally, we contrast our solution with existing query languages and derive a roadmap for future research on AutomationQL.