Andrew S. Hoffman is a postdoctoral researcher at Radboud University’s Interdisciplinary Hub for Security, Privacy and Data Governance (iHub). An ethnographer of information infrastructures, his work draws from a diverse set of fields including science & technology studies, computer supported cooperative work (CSCW), and human-computer interaction (HCI) to probe how the increasing datafication of society is fundamentally shifting work practices, collective life, and the very means by which we know ourselves and our material world. His work is primarily focused on the shifting dynamics of large-scale scientific collaboration; the engagement of users and other stakeholders in the design of sociotechnical systems; the practices and epistemic implications of knowledge representation in data-driven

ORCID: https://orcid.org/0000-0001-6137-4047

RU: https://www.ru.nl/english/people/hoffman-a/ 

LinkedIn: https://www.linkedin.com/in/parrhesiastic/


  • Hoffman, A.S., Jacobs, B., van Gastel, B., Schraffenberger, H., Sharon, T., and Pas, B. 2020. Towards a seamful ethics of Covid-19 contact tracing apps? Ethics & Information Technology. [DOI: 10.1007/s10676-020-09559-7]

  • Slota, S., Hoffman, A.S., Ribes, D., and Bowker, G. 2020. Prospecting (in) the data sciences. Big Data & Society. [DOI: 10.1177/2053951720906849]

  • Ribes, D., Hoffman, A.S., Slota, S. and Bowker, G. 2019. The logic of domains. Social Studies of Science, 49(3):281-309. [DOI: 10.1177/0306312719849709]


  • Standardization, semantic violence,and equifinal closure in semantic interoperability work. Workshop on ‘Conceptual Models of the Socio-Technical.’ 83rd Annual Meeting of the Association for Information Science and Technology (ASIS&T’20).
  • Towards a folded ecology of interoperability work in translational biomedical Research. Workshop on ‘Interrogating Data Science.’ The 23rd ACM conference on Computer Supported Cooperative Work (CSCW’20).
  • From principle(s) to practice(s): socio-technical features and implications of interoperability in data-intensive scientific work.’ UM Data Science Research Seminar Series, Institute for Data Science. University of Maastricht, NL.