Ana Eliza Duarte, João Bárbara, Adriano Machado, C. Burle, Wagner Meira, Jr, Leticia Alves
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When analyzing a set of portals that publish open data, it was noticed that there is no standardization of published data, which prevents or hinders access to open data by users. In this context, this work proposes a methodology created to evaluate this heterogeneous environment and present an estimate capable of mapping the use and recommendations of good practices for publication and availability of open data in Brazilian government portals. A new Open Data Evaluation Model in Brazilian Governmental Portals was created with an analysis process that presents an agile and simplified approach, capable of identifying and evaluating the data commonly presented in the various portals of open data publication, given the 10 Principles of Open Data Governance, document built by the Federal University of Minas Gerais, in the press, taking into account the W3C Recommendation Best Practices for Data on the Web.","PeriodicalId":401026,"journal":{"name":"Proceedings of the 24th Annual International Conference on Digital Government Research","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Open Data Evaluation Model in Brazilian Governmental Portals\",\"authors\":\"Ana Eliza Duarte, João Bárbara, Adriano Machado, C. Burle, Wagner Meira, Jr, Leticia Alves\",\"doi\":\"10.1145/3598469.3598510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the great challenges related to the publication and consumption of data on the web is the standardization of informational structures. Many organizations publish their datasets privately, without regard to developed publishing standards and principles established by the web community to facilitate the sharing and leveraging of information. Considering this scenario, it is necessary to create mechanisms that are capable of guiding publishers to use principles and best practices for publishing open data on the web and, in the future, allow better data governance in their information portals. This would result in several benefits, such as a better understanding of the data, and easier discovery, processing, reuse, and sharing of data by consumer users. 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Open Data Evaluation Model in Brazilian Governmental Portals
One of the great challenges related to the publication and consumption of data on the web is the standardization of informational structures. Many organizations publish their datasets privately, without regard to developed publishing standards and principles established by the web community to facilitate the sharing and leveraging of information. Considering this scenario, it is necessary to create mechanisms that are capable of guiding publishers to use principles and best practices for publishing open data on the web and, in the future, allow better data governance in their information portals. This would result in several benefits, such as a better understanding of the data, and easier discovery, processing, reuse, and sharing of data by consumer users. When analyzing a set of portals that publish open data, it was noticed that there is no standardization of published data, which prevents or hinders access to open data by users. In this context, this work proposes a methodology created to evaluate this heterogeneous environment and present an estimate capable of mapping the use and recommendations of good practices for publication and availability of open data in Brazilian government portals. A new Open Data Evaluation Model in Brazilian Governmental Portals was created with an analysis process that presents an agile and simplified approach, capable of identifying and evaluating the data commonly presented in the various portals of open data publication, given the 10 Principles of Open Data Governance, document built by the Federal University of Minas Gerais, in the press, taking into account the W3C Recommendation Best Practices for Data on the Web.