I am currently working on two main projects:
Spaces of Biomedicine in East Asia
Laboratory studies has been a critical aspect of science & technology studies and anthropology of science since the publication of Latour and Woolgar’s Laboratory Life (1979). This project is a multi-sited ethnography of labs and other biomedical spaces in Southeast and East Asia, but attempts to push laboratory studies in some new (methodological) directions.
First, it draws on the field of performance studies as a resource for understanding scientific life and its various enactments. This project is based on a collaboration with performance studies scholar Eddie Paterson (University of Melbourne). Using concepts such as “dramaturgy” as well as paying attention to “theatrical” elements in science, such as costume and movement, we hope to add new dimensions to the understanding of lives in (and around) laboratories.
Second, and as part of this attention to the broader context in which science takes place, this project is especially interested in the urban settings within which laboratories exist. What is the relationship between labs and geographic spaces around them? How do they influence cities socially and culturally? How does this affect the science that goes on inside them? Here we hope to bring laboratory studies into dialogue with urban studies.
So far, we have conducted fieldwork in Singapore and at BGI in Shenzhen and Hong Kong. A short piece we wrote about BGI was published in the Life Sciences Foundation Magazine Winter 2015 issue.
Data Infrastructures in Biology (and Beyond)
Biology has been dealing with the problems of “big data” for several decades. Even before the Human Genome Project began, biologists struggled cope with rapidly accumulating protein and DNA sequence data. My project examines the recent history of data in biology, paying particular attention to the ‘infrastructures’ (hardware, software, databases, data structures) that make data-work possible. For instance, the work of assembling a human genome from hundreds of thousands of small sequenced fragments required not only massive computational power, but also software capable of dealing with large, messy, and heterogeneous data sets. What sorts of knowledge and practices are required to perform such work, and in what ways does they differ from non-computational work in biology?
In exploring such examples, I aim to highlight some of the novelties of big data and big data practices. This novelty has less to do with size and more to do with how data are manipulated and used within computer-based infrastructures. I will suggest that this novelty demands new methods for studying data that allows us to follow it inside machines, software, and databases – that is, we need to supplement material culture approaches with ‘data culture’ approaches. Ultimately, such analysis will help us to understand the manifold consequences of ‘big data’ as it moves from science into a range of other social, economic, and political domains.
- Why Big Data Requires the Social Sciences
- Following the Data
- Data Infrastructures
- Gigascience: A Science Journal that Provides Full Data Sets
- The N-Gram and The Book: “Uncharted: Big Data as a Lens On Human Culture”