{"title":"“OntoDrive”一个多方法本体驱动框架,用于健康信息学系统分析","authors":"Vasilios A. Keramaris, K. Danas","doi":"10.1109/HealthCom.2016.7749454","DOIUrl":null,"url":null,"abstract":"Nowadays, more than ever, it is evident that we need a series of technological and methodological techniques in order to improve on the systems analysis and design (SAD) of any informational system. Recently, there is a huge demand to create domain vocabularies and semantics that along with cognition are to describe the information of any domain in the form of Resource Description Framework (RDF) and ontologies (OWL), both types of data models, resulting into relational and directed graphs and as a result both humans and machines simultaneously can understand the information offered, with machines using online links and pattern matching in order to interpret the meaning of it in a consistent and meaningful way. Ontologies are great ensuring interopirability and consistency of data, however in order to improve on current Information Systems (IS) such as Hospital Information Systems (HIS), there are many other methodologies that need to be invoked. This could be achieved with the waterfall approach and multiple deployment of systems analysis and design methodologies and of course detailed computational ontologies that will be used as a basis to represent and share domain specific knowledge and data structures ensuring the interoperability of systems and the quality of information within that domain. This multimethodological systems analysis and design framework, named “OntoDrive” is presented here.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"\\\"OntoDrive\\\" A multi-methodological ontology driven framework for systems analysis of health informatics\",\"authors\":\"Vasilios A. Keramaris, K. Danas\",\"doi\":\"10.1109/HealthCom.2016.7749454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, more than ever, it is evident that we need a series of technological and methodological techniques in order to improve on the systems analysis and design (SAD) of any informational system. Recently, there is a huge demand to create domain vocabularies and semantics that along with cognition are to describe the information of any domain in the form of Resource Description Framework (RDF) and ontologies (OWL), both types of data models, resulting into relational and directed graphs and as a result both humans and machines simultaneously can understand the information offered, with machines using online links and pattern matching in order to interpret the meaning of it in a consistent and meaningful way. Ontologies are great ensuring interopirability and consistency of data, however in order to improve on current Information Systems (IS) such as Hospital Information Systems (HIS), there are many other methodologies that need to be invoked. This could be achieved with the waterfall approach and multiple deployment of systems analysis and design methodologies and of course detailed computational ontologies that will be used as a basis to represent and share domain specific knowledge and data structures ensuring the interoperability of systems and the quality of information within that domain. This multimethodological systems analysis and design framework, named “OntoDrive” is presented here.\",\"PeriodicalId\":167022,\"journal\":{\"name\":\"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":\"2011 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2016.7749454\",\"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 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2016.7749454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
"OntoDrive" A multi-methodological ontology driven framework for systems analysis of health informatics
Nowadays, more than ever, it is evident that we need a series of technological and methodological techniques in order to improve on the systems analysis and design (SAD) of any informational system. Recently, there is a huge demand to create domain vocabularies and semantics that along with cognition are to describe the information of any domain in the form of Resource Description Framework (RDF) and ontologies (OWL), both types of data models, resulting into relational and directed graphs and as a result both humans and machines simultaneously can understand the information offered, with machines using online links and pattern matching in order to interpret the meaning of it in a consistent and meaningful way. Ontologies are great ensuring interopirability and consistency of data, however in order to improve on current Information Systems (IS) such as Hospital Information Systems (HIS), there are many other methodologies that need to be invoked. This could be achieved with the waterfall approach and multiple deployment of systems analysis and design methodologies and of course detailed computational ontologies that will be used as a basis to represent and share domain specific knowledge and data structures ensuring the interoperability of systems and the quality of information within that domain. This multimethodological systems analysis and design framework, named “OntoDrive” is presented here.