Hugh Williamson

Hugh-Williamson

Postdoctoral Research Fellow

Hugh F. Williamson is a Research Fellow in the DIGIT Lab, at the University of Exeter. Trained as a Social Anthropologist and Science and Technology Studies researcher, his research investigates governance, responsible practice and social organisation in digital agriculture and plant biology.

Hugh joined Exeter in 2019 and worked for over three years as Research Fellow in the Department of Social and Political Sciences, Philosophy and Anthropology and the Institute for Data Science and Artificial Intelligence (IDSAI), on the Alan Turing Institute-funded project ‘From Field Data to Global Indicators’. He is the co-editor, with Sabina Leonelli, of Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development (Springer, 2022). He has also conducted impact tracing work for IDSAI.

Prior to joining Exeter, Hugh was based at the University of Cambridge, where he conducted long-term ethnographic research on rural transformation in Eastern Europe.

H.Williamson@exeter.ac.uk
View LinkedIn page

Publications

Books

Choudhary A, Fox G, Hey T (2022). Artificial Intelligence for Science., WORLD SCIENTIFIC DOI.
Williamson HF, Leonelli S (2022). Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development., Springer  Abstract. DOI.

Journal articles

Williamson HF, Brettschneider J, Caccamo M, Davey RP, Goble C, Kersey PJ, May S, Morris RJ, Ostler R, Pridmore T, et al (2023). Data management challenges for artificial intelligence in plant and agricultural research. F1000Research, 10, 324-324.  Abstract. DOI.
Williamson HF, Leonelli S (2022). Accelerating agriculture: Data-intensive plant breeding and the use of genetic gain as an indicator for agricultural research and development. Studies in History and Philosophy of Science, 95, 167-176. DOI.
Williamson HF, Brettschneider J, Caccamo M, Davey RP, Goble C, Kersey PJ, May S, Morris RJ, Ostler R, Pridmore T, et al (2021). Data management challenges for artificial intelligence in plant and agricultural research. F1000Research, 10, 324-324.  Abstract. DOI.
Williamson HF, Brettschneider J, Caccamo M, Davey RP, Goble C, Kersey PJ, May S, Morris RJ, Ostler R, Pridmore T, et al (2021). Data management challenges for artificial intelligence in plant and agricultural research. F1000Research, 10  Abstract. DOI.
Fedirko T, Samanani F, Williamson HF (2021). Grammars of liberalism. Social Anthropology, 29(2), 373-386. DOI.

Chapters

Williamson H, Leonelli S (2023). Cultivating Responsible Plant Breeding Strategies: Conceptual and Normative Commitments in Data-Intensive Agriculture. In Williamson H, Leonelli S (Eds.) Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, Springer DOI.
Leonelli S, Williamson H (2023). Introduction: Towards Responsible Plant Data Linkage. In Williamson H, Leonelli S (Eds.) Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, Springer DOI.
Leonelli S, Williamson H (2022). Artificial Intelligence in Plant and Agricultural Research. In Choudhary A, Fox G, Het T (Eds.) AI for Science, World Scientific Publishers  Abstract.
just updated