Call for book chapter proposals: Valuing public data: data governance for economic, environmental and social development - editors: Esperanza Miyake (University of Strathclyde) & Angela Daly (University of Dundee) We are looking for chapter contributions for an interdisciplinary collection which brings together different research and policy insights around how public sector data can be best managed and used to ensure its value is of public benefit from social, economic and environmental perspectives. We have been liaising with the open access publisher, Scottish Universities Press, and aim to submit our book proposal in April/May. Public sector data gathering and use for government objectives, for research and for innovation and development are key issues for stakeholders internationally. This is due to the richness and comprehensiveness of data collected by the public sector, its functions to provide better government services but also its potential value for onward and secondary uses in research, innovation and development both within the public sector and by the private sector, third sector and academia. Another issue too is public authorities’ access to data held by other actors, especially in the private sector. These issues are highly relevant to the policy agenda in many countries throughout the world. We are seeking chapter proposals including but not limited to the following topics, from different disciplinary perspectives including but not limited to law, policy, sociology, political science, digital and internet studies, race and gender studies concerning public sector data collection and use, and issues relating to the ethics of big data and artificial intelligence (AI): - inequalities and bias in public data, and how this can be reproduced through onwards uses; - deriving value and benefit from public data for economic, environmental and social developments, including frameworks and processes for doing this; - dialogue and harmonisation between different countries and regions on these topics; - the impact of new technologies and applications including AI/machine learning trained on public data. Please send proposals of 250 words maximum for this edited collection along with a title and very short biographies of contributors to Angela Daly ( ADaly001@dundee.ac.uk) by 31 March 2024.