Understanding the development of public data ecosystems: From a conceptual model to a six-generation model of the evolution of public data ecosystems

IF 7.6 2区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
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Abstract

There is a lack of understanding of the elements that constitute different types of value-adding public data ecosystems and how these elements form and shape the development of these ecosystems over time, which can lead to misguided efforts to develop future public data ecosystems. The aim of the study is twofold: (1) to explore how public data ecosystems have developed over time and (2) to identify the value-adding elements and formative characteristics of public data ecosystems. Using an exploratory retrospective analysis and a deductive approach, we systematically review 148 studies published between 1994 and 2023. Based on the results, this study presents a typology of public data ecosystems and develops a conceptual model of elements and formative characteristics that contribute most to value-adding public data ecosystems. Moreover, this study develops a conceptual model of the evolutionary generation of public data ecosystems represented by six generations that differ in terms of (a) components and relationships, (b) stakeholders, (c) actors and their roles, (d) data types, (e) processes and activities, and (f) data lifecycle phases. Finally, three avenues for a future research agenda are proposed. This study is relevant for practitioners suggesting what elements of public data ecosystems have the most potential to generate value and should thus be part of public data ecosystems. As a scientific contribution, this study integrates conceptual knowledge about the elements of public data ecosystems, the evolution of these ecosystems, defines a future research agenda, and thereby moves towards defining public data ecosystems of the new generation.
了解公共数据生态系统的发展:从概念模型到公共数据生态系统演变的六代模型
人们对构成不同类型增值公共数据生态系统的要素以及这些要素如何随着时间的推移形成和塑造这些生态系统的发展缺乏了解,这可能会导致发展未来公共数据生态系统的努力受到误导。本研究有两个目的:(1) 探讨公共数据生态系统是如何随着时间的推移而发展的;(2) 确定公共数据生态系统的增值要素和形成特征。我们采用探索性回顾分析和演绎法,系统回顾了 1994 年至 2023 年间发表的 148 项研究。在此基础上,本研究提出了公共数据生态系统的类型学,并建立了一个概念模型,其中包括对公共数据生态系统增值贡献最大的要素和形成特征。此外,本研究还建立了公共数据生态系统演化世代的概念模型,该模型由六个世代组成,这六个世代在以下方面各不相同:(a) 组件和关系;(b) 利益相关者;(c) 参与者及其角色;(d) 数据类型;(e) 流程和活动;以及 (f) 数据生命周期阶段。最后,提出了未来研究议程的三个途径。本研究对从业人员具有重要意义,它提出了公共数据生态系统中哪些要素最有可能产生价值,因此应成为公共数据生态系统的一部分。作为一项科学贡献,本研究整合了有关公共数据生态系统要素、这些生态系统演变的概念性知识,确定了未来的研究议程,从而朝着定义新一代公共数据生态系统的方向迈进。
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来源期刊
Telematics and Informatics
Telematics and Informatics INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
17.00
自引率
4.70%
发文量
104
审稿时长
24 days
期刊介绍: Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.
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