{"title":"跨界研究合作的社区绘图","authors":"S. Konomi","doi":"10.1109/C5.2011.10","DOIUrl":null,"url":null,"abstract":"Making sense of research community patterns can be a challenging task since they are often complex, dynamic, and inseparable from the \"messiness\" of the real world. This paper introduces a data-centric community mapping tool that extracts and visualizes research communities in Computer Science, based on the DBLP publication database [1]. Initial experiences with the community mapping tool suggest a possibility to facilitate the process of initiating cross-boundary research collaboration using multiple network structures.","PeriodicalId":386991,"journal":{"name":"2011 Ninth International Conference on Creating, Connecting and Collaborating through Computing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Community Mapping for Cross-Boundary Research Collaboration\",\"authors\":\"S. Konomi\",\"doi\":\"10.1109/C5.2011.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Making sense of research community patterns can be a challenging task since they are often complex, dynamic, and inseparable from the \\\"messiness\\\" of the real world. This paper introduces a data-centric community mapping tool that extracts and visualizes research communities in Computer Science, based on the DBLP publication database [1]. Initial experiences with the community mapping tool suggest a possibility to facilitate the process of initiating cross-boundary research collaboration using multiple network structures.\",\"PeriodicalId\":386991,\"journal\":{\"name\":\"2011 Ninth International Conference on Creating, Connecting and Collaborating through Computing\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Ninth International Conference on Creating, Connecting and Collaborating through Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/C5.2011.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Ninth International Conference on Creating, Connecting and Collaborating through Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/C5.2011.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Community Mapping for Cross-Boundary Research Collaboration
Making sense of research community patterns can be a challenging task since they are often complex, dynamic, and inseparable from the "messiness" of the real world. This paper introduces a data-centric community mapping tool that extracts and visualizes research communities in Computer Science, based on the DBLP publication database [1]. Initial experiences with the community mapping tool suggest a possibility to facilitate the process of initiating cross-boundary research collaboration using multiple network structures.