Socio-technical system analysis of responsible data sharing in water systems as critical infrastructure

被引:0
|
作者
Hazell, Peter [1 ,2 ]
Novitzky, Peter [3 ,4 ]
van den Oord, Steven [4 ,5 ,6 ]
机构
[1] Yorkshire Water UK, Bradford, England
[2] Univ Huddersfield, Sch Comp & Engn, Dept Comp Sci, Huddersfield, England
[3] UCL, Dept Sci Technol Engn & Publ Policy, Technol, Engn & Publ Policy, London, England
[4] Avans Univ Appl Sci, Breda, Netherlands
[5] Univ Antwerp, Antwerp, Belgium
[6] Antwerp Management Sch, Antwerp, Belgium
来源
FRONTIERS IN BIG DATA | 2023年 / 5卷
基金
英国工程与自然科学研究理事会;
关键词
water systems; critical infrastructure; socio-technical system analysis; Capabilities Approach; datafication; SOCIAL-EXCHANGE THEORY; URBAN WATER; INFORMATION-TECHNOLOGY; INSTITUTIONS; FIRM; PERSPECTIVE; PERFORMANCE; CHOICE;
D O I
10.3389/fdata.2022.1057155
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Attention is increasingly focused on the protection of water systems as critical infrastructure, including subsystems of supply, sanitation, hygiene, and management. Similarly increasing consideration is paid to the growing role and impact of data on water systems and management. We explore key challenges associated with data-driven water systems as critical infrastructure. First, we describe the status of water infrastructure as a part of national critical infrastructure. Second, as this infrastructure increasingly relies on the constant flow of data from a huge variety, quality, and complexity of sensors, we provide a descriptive framework to map in detail the particular expertise needed across data-driven water management, applied to the UK water infrastructure as our use case. Third, through the framework of Capabilities Approach (CA) we analyze the specific challenges of data-driven water management, and argue that the current predominant narratives in the water infrastructure discourse have difficulties to effectively convey existing and emerging challenges. Fourth, we further demonstrate the widening gap between infrastructure services and consumer goods, arguing for increased convergence of the utilization of consumer data, and developing open data ecosystems.
引用
收藏
页数:18
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