What is a domain?
Below are four articles tracking (sometimes critiquing) the genealogy, practices, and consequences of the logic of domains. There is more to come.
"Domain" is a pervasive vernacular term within the computer, information and data sciences. It serves to identify and demarcate human spheres of expertise or experience - such as biology as the ‘domain science of life’, or travel agents as the ‘domain experts of ... travel’. The logic of domains is both an organizing principle for how to develop general, — domain ‘independent’, ‘agnostic,’ ‘invariant’ — computational systems and, today, has become a de facto approach encoded in science policy and funding.
The keystone paper on the logic of domains, outlining its early crystalization in Artificial Intelligence circles during the 1960's and 1970s, and then tracking as the logic became a de facto organizing principle for developing information technologies, and encoded in science policy and funding.
How I learned what a domain was
A reflexive paper that tracks i) my first encounters with the term ‘domain’ in computational circles and ii) how I approached the investigation as a grounded theory analysis.
This paper is both substantive (about ‘domains’) and methodological (grounded theory). The title is a play on Howie Becker’s classic paper, How I Learned What Crock Was.
STS, Meet Data Science, Once Again
A reflection on the envisioned role of social scientists in data science projects. I argue for an ‘elective affinity’ (Weber) between data science and STS, with both fields learning by working across disciplines and fields, but doing so for very different reasons.
Prospecting (in) the data sciences
Data science is characterized by engaging heterogeneous data to tackle real world questions and problems. But data science has no data of its own and must seek it within real world domains.
Of the four LOD papers thus far this is certainly the most critical. Hmm.