Towards an understanding of data work in context: Emerging issues of economy, governance, and ethics

Purpose - It is a commonplace that innovation in the digital economy is now driven by data. Business organizations, media companies, and government for example all create economic and societal value from the digital traces left by the user population. At the same time the data captured also contains information that personally identifies consumers, citizens and patients as individuals. The purpose of this paper is to place this new form of data work in the context of previous approaches to information work; to identify the differences between information and data work and the resulting challenges for data professionals.

Design/methodology/approach - Informed by a review of previous approaches to information work, the article argues that the shift in value from information to data as an economic asset and a societal good entails a new form of human-oriented data work. One that is more sensitive to the contextual conditions and consequences of the capture, processing and use of data than has been the case hitherto. The implications of this for a shift in emphasis from the data scientist to the data professional is addressed, as are emerging challenges of governance and education.

Findings - The main consequence for data professionals is to ensure that processes are in place not only to enable the creation of valued products and services from data, but also to mitigate the risks related to their development. The paper argues that ensuring this involves taking a contextual view that locates data processing within the user, governance, legal, and ethical conditions related to data work. The consequences for the governance of data, and the education of data professionals are addressed.

Originality/value - The value of the paper rests in its development of an analytical and methodologically driven framework, that places new forms of data work in the context of their conditions and consequences. The framework builds on prior approaches to information work, current approaches to data work, and addresses the governance, and educational challenges arising from organisations' emphasis on data-driven innovation in a digital economy.