{"title":"Research on Transparent Access Technology of Government Big Data","authors":"Honghui Li, XU Yi, Yunjuan Peng, Xiaorui Yang, Dalin Zhang","doi":"10.17559/tv-20230630000775","DOIUrl":null,"url":null,"abstract":": E-governance is capable of driving the transition of government from an administrative power allocation of public resources to a citizen-service-oriented governance model. However, during this transformation, various governmental bodies often face the challenge of \"data silos\" caused by factors such as cross-regional, cross-business, and cross-departmental operations. Without altering the existing information platforms, transparent access technology serves as a key solution for data access within e-governance systems. It enables convenient access to information resources stored in different mediums and formats, facilitating the sharing and consolidation of information and data within and between governmental departments, thereby addressing the issue of \"data silos\" and enhancing the comprehensive service capabilities of e-governance. This paper firstly provides an overview of the concept, levels, characteristics, and application scenarios of transparent access to government big data. Secondly, it conducts a comprehensive comparative analysis of transparent access technologies in the context of cloud computing and big data. Lastly, based on the requirements of various transparent access technologies and the application of transparent access to government big data, this paper proposes a visionary framework for transparent access to government big data based on cross-domain semantics and channel coupling. This framework includes modules for cross-domain semantic interoperability, coupling of heterogeneous information channels based on knowledge graph, and tracing of multi-source heterogeneous data, aiming to provide innovative solutions for achieving transparent access to government big data.","PeriodicalId":510054,"journal":{"name":"Tehnicki vjesnik - Technical Gazette","volume":"7 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tehnicki vjesnik - Technical Gazette","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17559/tv-20230630000775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
: E-governance is capable of driving the transition of government from an administrative power allocation of public resources to a citizen-service-oriented governance model. However, during this transformation, various governmental bodies often face the challenge of "data silos" caused by factors such as cross-regional, cross-business, and cross-departmental operations. Without altering the existing information platforms, transparent access technology serves as a key solution for data access within e-governance systems. It enables convenient access to information resources stored in different mediums and formats, facilitating the sharing and consolidation of information and data within and between governmental departments, thereby addressing the issue of "data silos" and enhancing the comprehensive service capabilities of e-governance. This paper firstly provides an overview of the concept, levels, characteristics, and application scenarios of transparent access to government big data. Secondly, it conducts a comprehensive comparative analysis of transparent access technologies in the context of cloud computing and big data. Lastly, based on the requirements of various transparent access technologies and the application of transparent access to government big data, this paper proposes a visionary framework for transparent access to government big data based on cross-domain semantics and channel coupling. This framework includes modules for cross-domain semantic interoperability, coupling of heterogeneous information channels based on knowledge graph, and tracing of multi-source heterogeneous data, aiming to provide innovative solutions for achieving transparent access to government big data.