A fourth way to the digital transformation: The data republic as a fair data ecosystem

被引:4
作者
Calzati, Stefano [1 ]
van Loenen, Bastiaan [1 ]
机构
[1] Delft Univ Technol, Dept Urbanism, Urban Data Sci Grp, Delft, Netherlands
来源
DATA & POLICY | 2023年 / 5卷
关键词
Data commons; data governance; ecosystem; EU; fairness; inclusiveness; democratic participation; and environmental sustainability (von der Leyen; 2019; SPATIAL DATA INFRASTRUCTURES; CITIES; DESIGN; CHINA; INFORMATION; POLICY; SMART;
D O I
10.1017/dap.2023.18
中图分类号
C93 [管理学]; D035 [国家行政管理]; D523 [行政管理]; D63 [国家行政管理];
学科分类号
12 ; 1201 ; 1202 ; 120202 ; 1204 ; 120401 ;
摘要
To harness the promises of digital transformation, different players take different paths. Departing from corporate-driven (e.g., the United States) and state-led (e.g., China) approaches, in various documents, the European Union states its goal to establish a citizen-centric data ecosystem. However, it remains contentious the extent to which the envisioned digital single market can enable the creation of public value and empower citizens. As an alternative, in this article, we argue in favor of a fair data ecosystem, defined as an approach capable of representing and keep in balance the data interests of all actors, while maintain a collective outlook. We build such ecosystem around data commons-as a third path to market and state approaches to the managing of resources-coupled with open data (OD) frameworks and spatial data infrastructures (SDIs). Indeed, based on literature, we claim that these three regimes complement each other, with OD and SDIs supplying infrastructures and institutionalization to data commons' limited replicability and scalability. This creates the preconditions for designing the main roles, rules, and mechanisms of a data republic, as a possible enactment of a fair data ecosystem. While outlining here its main traits, the testing of the data republic model is open for further research.
引用
收藏
页数:18
相关论文
共 106 条
[51]   Chinese Social Media and Big Data: Big Data, Big Brother, Big Profit? [J].
Jiang, Min ;
Fu, King-Wa .
POLICY AND INTERNET, 2018, 10 (04) :372-392
[52]  
Kalpokas I, 2022, ROUTLEDGE HDB ARCHIT, VI, P496
[53]   Design global, manufacture local: Exploring the contours of an emerging productive model [J].
Kostakis, Vasilis ;
Niaros, Vasilis ;
Dafermos, George ;
Bauwens, Michel .
FUTURES, 2015, 73 :126-135
[54]   Why distance matters: The relatedness between technology development and its appropriation in smart cities [J].
Kummitha, Rama Krishna Reddy .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2020, 157
[55]  
Latour B, 2004, POLITICS NATURE
[56]  
Lee K.-F., 2019, AI Superpowers: China, Silicon Valley, and the New World Order
[57]   The Landscape and Gaps in Open Source Fairness Toolkits [J].
Lee, Michelle Seng Ah ;
Singh, Jat .
CHI '21: PROCEEDINGS OF THE 2021 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2021,
[58]  
Lee Michelle Seng Ah, 2021, AI and Ethics, V1, P529, DOI [DOI 10.1007/S43681-021-00067-Y, 10.1007/S43681-021-00067-Y]
[59]  
Lippert Barbara, 2020, SWP Research Paper 4/2020, DOI DOI 10.18449/2020RP04
[60]  
Ludwig Thomas, 2018, Proceedings of the ACM on Human-Computer Interaction, V2, DOI 10.1145/3274382