The Role of a Data Marketplace for Innovation and Value-Added Services in Smart and Sustainable Cities

Alvsvåg, Rebekka; Anthony, Bokolo; Petersen, Sobah Abbas

doi:10.1007/978-3-031-06668-9_16

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…The data driven strategies aim to get the right amount of data from the right source and at the right place to make evidence-based planned decisions in relation to sustainability of the city. Data driven strategies provide access to data that enables seamless administration and planning of the city services (Watson et al , 2020; Alvsvåg et al , 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

Data driven approaches for smart city planning and design: a case scenario on urban data management

Anthony

2023

DPRG

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Purpose Because of the use of digital technologies in smart cities, municipalities are increasingly facing issues related to urban data management and are seeking ways to exploit these huge amounts of data for the actualization of data driven services. However, only few studies discuss challenges related to data driven strategies in smart cities. Accordingly, the purpose of this study is to present data driven approaches (architecture and model), for urban data management needed to improve smart city planning and design. The developed approaches depict how data can underpin sustainable urban development. Design/methodology/approach Design science research is adopted following a qualitative method to evaluate the architecture developed based on top-level design using a case data from workshops and interviews with experts involved in a smart city project. Findings The findings of this study from the evaluations indicate that the identified enablers are useful to support data driven services in smart cities and the developed architecture can be used to promote urban data management. More importantly, findings from this study provide guidelines to municipalities to improve data driven services for smart city planning and design. Research limitations/implications Feedback as qualitative data from practitioners provided evidence on how data driven strategies can be achieved in smart cities. However, the model is not validated. Hence, quantitative data is needed to further validate the enablers that influence data driven services in smart city planning and design. Practical implications Findings from this study offer practical insights and real-life evidence to define data driven enablers in smart cities and suggest research propositions for future studies. Additionally, this study develops a real conceptualization of data driven method for municipalities to foster open data and digital service innovation for smart city development. Social implications The main findings of this study suggest that data governance, interoperability, data security and risk assessment influence data driven services in smart cities. This study derives propositions based on the developed model that identifies enablers for actualization of data driven services for smart cities planning and design. Originality/value This study explores the enablers of data driven strategies in smart city and further developed an architecture and model that can be adopted by municipalities to structure their urban data initiatives for improving data driven services to make cities smarter. The developed model supports municipalities to manage data used from different sources to support the design of data driven services provided by different enterprises that collaborate in urban environment.

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Section: Literature Reviewmentioning

confidence: 99%

Data driven approaches for smart city planning and design: a case scenario on urban data management

Anthony

2023

DPRG

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Establishing a Health Data Marketplace: A Framework for Success

Erdvik,

Intaraphasuk,

Pappas

et al. 2023

Lecture Notes in Computer Science

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Decentralized brokered enabled ecosystem for data marketplace in smart cities towards a data sharing economy

Anthony

2023

Environ Syst Decis

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Presently data are indispensably important as cities consider data as a commodity which can be traded to earn revenues. In urban environment, data generated from internet of things devices, smart meters, smart sensors, etc. can provide a new source of income for citizens and enterprises who are data owners. These data can be traded as digital assets. To support such trading digital data marketplaces have emerged. Data marketplaces promote a data sharing economy which is crucial for provision of available data useful for cities which aims to develop data driven services. But currently existing data marketplaces are mostly inadequate due to several issues such as security, efficiency, and adherence to privacy regulations. Likewise, there is no consolidated understanding of how to achieve trust and fairness among data owners and data sellers when trading data. Therefore, this study presents the design of an ecosystem which comprises of a distributed ledger technology data marketplace enabled by message queueing telemetry transport (MQTT) to facilitate trust and fairness among data owners and data sellers. The designed ecosystem for data marketplaces is powered by IOTA technology and MQTT broker to support the trading of sdata sources by automating trade agreements, negotiations and payment settlement between data producers/sellers and data consumers/buyers. Overall, findings from this article discuss the issues associated in developing a decentralized data marketplace for smart cities suggesting recommendations to enhance the deployment of decentralized and distributed data marketplaces.

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The Role of a Data Marketplace for Innovation and Value-Added Services in Smart and Sustainable Cities

Cited by 5 publications

References 22 publications

Data driven approaches for smart city planning and design: a case scenario on urban data management

Data driven approaches for smart city planning and design: a case scenario on urban data management

Establishing a Health Data Marketplace: A Framework for Success

Decentralized brokered enabled ecosystem for data marketplace in smart cities towards a data sharing economy

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