R. Calinescu, Steve Harris, J. Gibbons, J. Davies, I. Toujilov, S. Nagl
{"title":"Model-driven architecture for cancer research","authors":"R. Calinescu, Steve Harris, J. Gibbons, J. Davies, I. Toujilov, S. Nagl","doi":"10.1109/SEFM.2007.26","DOIUrl":null,"url":null,"abstract":"It is a common phenomenon for research projects to collect and analyse valuable data using ad-hoc information systems. These costly-to-build systems are often composed of incompatible variants of the same modules, and record data in ways that prevent any meaningful result analysis across similar projects. We present a framework that uses a combination of formal methods, model-driven development and service-oriented architecture (SOA) technologies to automate the generation of data management systems for cancer clinical trial research, an area particularly affected by these problems. The SOA solution generated by the framework is based on an information model of a cancer clinical trial, and comprises components for both the collection and analysis of cancer research data, within and across clinical trial boundaries. While primarily targeted at cancer research, our approach is readily applicable to other areas for which a similar information model is available.","PeriodicalId":212544,"journal":{"name":"Fifth IEEE International Conference on Software Engineering and Formal Methods (SEFM 2007)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth IEEE International Conference on Software Engineering and Formal Methods (SEFM 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEFM.2007.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
It is a common phenomenon for research projects to collect and analyse valuable data using ad-hoc information systems. These costly-to-build systems are often composed of incompatible variants of the same modules, and record data in ways that prevent any meaningful result analysis across similar projects. We present a framework that uses a combination of formal methods, model-driven development and service-oriented architecture (SOA) technologies to automate the generation of data management systems for cancer clinical trial research, an area particularly affected by these problems. The SOA solution generated by the framework is based on an information model of a cancer clinical trial, and comprises components for both the collection and analysis of cancer research data, within and across clinical trial boundaries. While primarily targeted at cancer research, our approach is readily applicable to other areas for which a similar information model is available.