I am currenlty working on a book for teaching about data with Sabina Leonelli, developing a major research project focusing on infrastructures for sustainability with Selen Eren and Theunis Piersma, and writing up an analysis of how knowledge of the SDGs is produced.
Acknowledgements: Research is an essentially social entreprise. Wonderful collaborators, co-authors, mentors and friends have contributed to the development of these activities in big and small ways. Support from many funding bodies is also gratefully acknowledged. Most photos on this site taken by Maarten Derksen.
With Sabina Leonelli. A Critical Introduction to Data and Society provides analytical tools to understand the role of data in contemporary society and foster good data practices. It addresses the growing attention to the social embedding of data across different settings, from business to policy and government, from sports to health and climate change, and the challenges that such embedding brings both for the governance and regulation of data flows and for the technical management and use of data. It is an interdisciplinary introductory textbook for undergraduate that connects the phenomenon of datafication and related technologies to social, technological and economic change. Its conceptual framework relates ideas and principles with concrete cases, to help readers understand the growing importance of data in different spheres of knowledge production and its implications for a wide variety of sectors.
In this project, pursued with Selen Eren at Campus Fryslan and in collaboration with team Theunis Piersma of the University of Groningen, I examine how different actors use the interfaces to such infrastructures to know and intervene responsibly. Knowledge infrastructures are essential to how we define and establish urgency around issues like climate change or loss of biodiversity, and they are also key to monitoring our progress in addressing these issues.
At the heart of this research are questions about how values and practices are reinforced by current knowledge infrastructures, which adaptations are needed to develop more responsible and sustainable practices based on knowledge and how to make complex, multi-dimensional data tractable. The aim is better knowledge infrastructures, better in the sense that they bring issues of intention, responsibility and accountability to the forefront and that they garner sufficient trust and reliability to enable us to act.
In a related project with Clarisse Kraamwinkel and Tessa van der Voort, we are developing expertise on Responsible Knowledge Infrastructures for Climate Adaptation, focusing on climate resilience in delta areas.
For Handbook for the Anthropology of Technology (in preparation, 2020), Brit Winthereik and Klaus Hoeyer Eds. Palgrave Handbooks. In this chapter, I analyse knowledge practices enacted around the Sustainable Development Goals (SDGs) to better understand how technologically mediated data practices have become central to formulating, addressing and monitoring progress on pressing global environmental problems and the alleviation of human hardship. This analysis contributes to explaining how the science-policy nexus around global issues SDGs is changing–shaping and being shaped by new data practices. The focus is on claims about what we know, need to know and don’t (yet) know in relation to the SDGs. These claims shape the emerging agenda for infrastructures for knowledge production and give rise to novel data practices and new lines of accountability.
How much insight is added with increasing amounts of data? Does the augmented diversity of larger data sets hamper their scientific value? Is the relationship between ‘Big Data’ and ‘Big Insights’ appropriately understood, or even understandable? Finally, what are the consequences of aiming for greater collection and circulation for individual privacy and collective autonomy, property, responsibility, creativity and freedom? The answers to these questions might have huge implications for future research practices, both for data collection as well as data analysis, and the basis for trusting knowledge.
Together with Oskar Gstrein (CF), Ronald Stolk (UMCG) and a PhD candidate, I expore epistemic issues around how we value big data. Marthe Stevens (EUR) and I are writing about epistemic responsibility in the use of machine learning, engaging with the work on care of Puig de la Bellacasa.
PhD committees and PhD examinations