{"title":"可视化关联的开放统计数据以支持公共管理","authors":"E. Tambouris, E. Kalampokis, K. Tarabanis","doi":"10.1145/3085228.3085304","DOIUrl":null,"url":null,"abstract":"Open data have tremendous potential which however remains unexploited. A large part of open data is numerical and highly structured. We concentrate on those data and capitalize on linked open data (LOD) as the underlying technology. In this paper, we present a number of tools to facilitate publishing and reusing of linked open statistical data. We propose an architecture and implementation that allows developing custom visualization and analysis tools without knowledge of LOD technologies. We further present work towards deploying relevant tools in six different countries to improve decision-making and transparency and thus support public administration.","PeriodicalId":416111,"journal":{"name":"Proceedings of the 18th Annual International Conference on Digital Government Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Visualizing Linked Open Statistical Data to Support Public Administration\",\"authors\":\"E. Tambouris, E. Kalampokis, K. Tarabanis\",\"doi\":\"10.1145/3085228.3085304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Open data have tremendous potential which however remains unexploited. A large part of open data is numerical and highly structured. We concentrate on those data and capitalize on linked open data (LOD) as the underlying technology. In this paper, we present a number of tools to facilitate publishing and reusing of linked open statistical data. We propose an architecture and implementation that allows developing custom visualization and analysis tools without knowledge of LOD technologies. We further present work towards deploying relevant tools in six different countries to improve decision-making and transparency and thus support public administration.\",\"PeriodicalId\":416111,\"journal\":{\"name\":\"Proceedings of the 18th Annual International Conference on Digital Government Research\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 18th Annual International Conference on Digital Government Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3085228.3085304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th Annual International Conference on Digital Government Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3085228.3085304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visualizing Linked Open Statistical Data to Support Public Administration
Open data have tremendous potential which however remains unexploited. A large part of open data is numerical and highly structured. We concentrate on those data and capitalize on linked open data (LOD) as the underlying technology. In this paper, we present a number of tools to facilitate publishing and reusing of linked open statistical data. We propose an architecture and implementation that allows developing custom visualization and analysis tools without knowledge of LOD technologies. We further present work towards deploying relevant tools in six different countries to improve decision-making and transparency and thus support public administration.