Syed Iftikhar Hussain Shah , Vassilios Peristeras , Ioannis Magnisalis
{"title":"政府大数据生态系统(\"datagov.eco\")概念框架","authors":"Syed Iftikhar Hussain Shah , Vassilios Peristeras , Ioannis Magnisalis","doi":"10.1016/j.datak.2024.102348","DOIUrl":null,"url":null,"abstract":"<div><p>The public sector, private firms, and civil society constantly create data of high volume, velocity, and veracity from diverse sources. This kind of data is known as big data. As in other industries, public administrations consider big data as the “new oil\" and employ data-centric policies to transform data into knowledge, stimulate good governance, innovative digital services, transparency, and citizens' engagement in public policy. More and more public organizations understand the value created by exploiting internal and external data sources, delivering new capabilities, and fostering collaboration inside and outside of public administrations. Despite the broad interest in this ecosystem, we still lack a detailed and systematic view of it. In this paper, we attempt to describe the emerging Government Big Data Ecosystem as a <em>socio-technical network</em> of people, organizations, processes, technology, infrastructure, standards & policies, procedures, and resources. This ecosystem supports <em>data functions</em> such as data collection, integration, analysis, storage, sharing, use, protection, and archiving. Through these functions, <em>value is created</em> by promoting evidence-based policymaking, modern public services delivery, data-driven administration and open government, and boosting the data economy. Through a Design Science Research methodology, we propose a conceptual framework, which we call ‘datagov.eco’. We believe our ‘datagov.eco’ framework will provide insights and support to different stakeholders’ profiles, including administrators, consultants, data engineers, and data scientists.</p></div>","PeriodicalId":55184,"journal":{"name":"Data & Knowledge Engineering","volume":"154 ","pages":"Article 102348"},"PeriodicalIF":2.7000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A conceptual framework for the government big data ecosystem (‘datagov.eco’)\",\"authors\":\"Syed Iftikhar Hussain Shah , Vassilios Peristeras , Ioannis Magnisalis\",\"doi\":\"10.1016/j.datak.2024.102348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The public sector, private firms, and civil society constantly create data of high volume, velocity, and veracity from diverse sources. This kind of data is known as big data. As in other industries, public administrations consider big data as the “new oil\\\" and employ data-centric policies to transform data into knowledge, stimulate good governance, innovative digital services, transparency, and citizens' engagement in public policy. More and more public organizations understand the value created by exploiting internal and external data sources, delivering new capabilities, and fostering collaboration inside and outside of public administrations. Despite the broad interest in this ecosystem, we still lack a detailed and systematic view of it. In this paper, we attempt to describe the emerging Government Big Data Ecosystem as a <em>socio-technical network</em> of people, organizations, processes, technology, infrastructure, standards & policies, procedures, and resources. This ecosystem supports <em>data functions</em> such as data collection, integration, analysis, storage, sharing, use, protection, and archiving. Through these functions, <em>value is created</em> by promoting evidence-based policymaking, modern public services delivery, data-driven administration and open government, and boosting the data economy. Through a Design Science Research methodology, we propose a conceptual framework, which we call ‘datagov.eco’. We believe our ‘datagov.eco’ framework will provide insights and support to different stakeholders’ profiles, including administrators, consultants, data engineers, and data scientists.</p></div>\",\"PeriodicalId\":55184,\"journal\":{\"name\":\"Data & Knowledge Engineering\",\"volume\":\"154 \",\"pages\":\"Article 102348\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data & Knowledge Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0169023X24000727\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data & Knowledge Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169023X24000727","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A conceptual framework for the government big data ecosystem (‘datagov.eco’)
The public sector, private firms, and civil society constantly create data of high volume, velocity, and veracity from diverse sources. This kind of data is known as big data. As in other industries, public administrations consider big data as the “new oil" and employ data-centric policies to transform data into knowledge, stimulate good governance, innovative digital services, transparency, and citizens' engagement in public policy. More and more public organizations understand the value created by exploiting internal and external data sources, delivering new capabilities, and fostering collaboration inside and outside of public administrations. Despite the broad interest in this ecosystem, we still lack a detailed and systematic view of it. In this paper, we attempt to describe the emerging Government Big Data Ecosystem as a socio-technical network of people, organizations, processes, technology, infrastructure, standards & policies, procedures, and resources. This ecosystem supports data functions such as data collection, integration, analysis, storage, sharing, use, protection, and archiving. Through these functions, value is created by promoting evidence-based policymaking, modern public services delivery, data-driven administration and open government, and boosting the data economy. Through a Design Science Research methodology, we propose a conceptual framework, which we call ‘datagov.eco’. We believe our ‘datagov.eco’ framework will provide insights and support to different stakeholders’ profiles, including administrators, consultants, data engineers, and data scientists.
期刊介绍:
Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.