{"title":"计算机课程中数据库课程的增强型领域本体模型","authors":"N. Rahayu, R. Ferdiana, S. Kusumawardani","doi":"10.11591/ijai.v13.i2.pp1339-1347","DOIUrl":null,"url":null,"abstract":"The ACM/IEEE Computing Curricula 2020 includes the study of relational databases in four of its six disciplines. However, a domain ontology model of multidisciplinary database course does not exist. Therefore, the current study aims to build a domain ontology model for the multidisciplinary database course. The research process comprises three phases: a review of database course contents based on the ACM/IEEE Computing Curricula 2020, a literature review of relevant domain ontology models, and a design research phase using the NeOn methodology framework. The ontology building involves the ontology reuse and reengineering of existing models, along with the construction of some classes from a non-ontological resource. The approach to ontology reuse and reengineering demonstrates ontology reusability. The final domain ontology model is then evaluated using two ontology syntactic metrics: Relationship Richness and Information Richness. These metrics reflect the diversity of relationships and the breadth of knowledge in the model, respectively. In conclusion, the current research contributes to the Computing Curricula by providing an ontology model for a multidisciplinary database course. The model, developed through ontology reuse and reengineering and the integration of non-ontological resources, exhibits more diverse relationships and represents a broader range of knowledge.","PeriodicalId":507934,"journal":{"name":"IAES International Journal of Artificial Intelligence (IJ-AI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An enhanced domain ontology model of database course in computing curricula\",\"authors\":\"N. Rahayu, R. Ferdiana, S. Kusumawardani\",\"doi\":\"10.11591/ijai.v13.i2.pp1339-1347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ACM/IEEE Computing Curricula 2020 includes the study of relational databases in four of its six disciplines. However, a domain ontology model of multidisciplinary database course does not exist. Therefore, the current study aims to build a domain ontology model for the multidisciplinary database course. The research process comprises three phases: a review of database course contents based on the ACM/IEEE Computing Curricula 2020, a literature review of relevant domain ontology models, and a design research phase using the NeOn methodology framework. The ontology building involves the ontology reuse and reengineering of existing models, along with the construction of some classes from a non-ontological resource. The approach to ontology reuse and reengineering demonstrates ontology reusability. The final domain ontology model is then evaluated using two ontology syntactic metrics: Relationship Richness and Information Richness. These metrics reflect the diversity of relationships and the breadth of knowledge in the model, respectively. In conclusion, the current research contributes to the Computing Curricula by providing an ontology model for a multidisciplinary database course. The model, developed through ontology reuse and reengineering and the integration of non-ontological resources, exhibits more diverse relationships and represents a broader range of knowledge.\",\"PeriodicalId\":507934,\"journal\":{\"name\":\"IAES International Journal of Artificial Intelligence (IJ-AI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IAES International Journal of Artificial Intelligence (IJ-AI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11591/ijai.v13.i2.pp1339-1347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IAES International Journal of Artificial Intelligence (IJ-AI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijai.v13.i2.pp1339-1347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An enhanced domain ontology model of database course in computing curricula
The ACM/IEEE Computing Curricula 2020 includes the study of relational databases in four of its six disciplines. However, a domain ontology model of multidisciplinary database course does not exist. Therefore, the current study aims to build a domain ontology model for the multidisciplinary database course. The research process comprises three phases: a review of database course contents based on the ACM/IEEE Computing Curricula 2020, a literature review of relevant domain ontology models, and a design research phase using the NeOn methodology framework. The ontology building involves the ontology reuse and reengineering of existing models, along with the construction of some classes from a non-ontological resource. The approach to ontology reuse and reengineering demonstrates ontology reusability. The final domain ontology model is then evaluated using two ontology syntactic metrics: Relationship Richness and Information Richness. These metrics reflect the diversity of relationships and the breadth of knowledge in the model, respectively. In conclusion, the current research contributes to the Computing Curricula by providing an ontology model for a multidisciplinary database course. The model, developed through ontology reuse and reengineering and the integration of non-ontological resources, exhibits more diverse relationships and represents a broader range of knowledge.