Data science

Philippe's dissertation project focuses on the emerging field of "data science": To be a data scientist has been promoted as “the sexiest job of the 21st century” (Davenport & Patil 2012) and analysts are constantly warning of a serious "talent shortage" in this field. "Data science" has been described as an interdisciplinary field that includes people trained in statistics, computer sciences, machine learning, mathematics, and engineering, who are equipped with strong programming skills.

The research interest lies in differing concepts of "data science" as they are articulated in various fields. First, political reports and documents outline specific scenarios for further development of data science in scientific research as well as in the economic field. Secondly, study programmes and curricula at universities and colleges implement this heterogeneous field of knowledge into a certain form and thereby shape the next generation of educated data scientists. The analysis of documents is supplemented by qualitative interviews with professors and researchers who formulate their own perspectives. Thirdly, companies and other organisations address specific profiles of job seekers through job advertisements for data scientists in the labour market. Through such discursive practices, formats and materializations, the various actors formulate field-specific perspectives on what constitutes "data science" for them. In this way, they open up a space between their own established fields, which is characterized by polyphony and multi-perspectivity, and thus contribute to the constitution and further development of "data science".

Philippe will analyze this data using a combination of qualitative and automated text analysis in order to identify the respective definitions, concepts and categories in the different fields, to relate them to each other and to make them analytically comprehensible.