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ITU Journal: ICT Discoveries

The ITU Journal: ICT Discoveries publishes original research on ICT technical developments and their policy and regulatory, economic, social and legal dimensions. It builds bridges between disciplines, connects theory with application, and stimulates international dialogue. This interdisciplinary approach reflects ITU’s comprehensive field of interest and explores the convergence of ICT with other disciplines. It also features review articles, best practice implementation tutorials and case studies. The ITU Journal welcomes submissions at any time, on any topic within its scope.

English

Data as economic goods

Definitions, properties, challenges, enabling technologies for future data markets

The notion that data has value is commonly recognized. However, data value is different from that associated with consumable goods. There is a number of initiatives to create data markets and data exchange services. Existing business models of paid or commercial data (sets) services such as data archives are based on service subscription fees. However, emerging data-driven technologies and economies facilitate interest in making data a new economic value (data commoditization) and consequently identification of the new properties of data as economic goods. The following properties are leveraging FAIR data properties and defined as STREAM properties for industrial and commoditized data: sovereign, trusted, reusable, exchangeable, actionable, and measurable. Other properties to be considered and necessary for defining workable business and operational models are non-rival nature of data, data ownership, data quality, value, privacy, integrity, and provenance. The paper refers to other discussions and projects on defining data as consumable goods and market mechanisms that can be applied to data exchange, such as data markets, data exchange, and industrial data space.

English

Keywords: big data, data management, data markets, data exchange, STREAM data properties, big data infrastructure, open data, FAIR principles
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