Paper short abstract:

This paper presents a survey of emerging data work coming out of the professionalization and 'trickle down' effects of the institutionalization and enrollment of data science into higher education and the professionalization of information workers.

Paper long abstract:

Currently, we are witnessing the emergence of new kinds of evidence generated by human trace data, supported by networked infrastructures, captured in vast digital collections, and mediated through new kinds of data work. The scales of these digital collections (big, small, unstructured, and sometimes dark) are subject to a range of problems, particularly related to that of data storage and data processing. The nature of these "data problems" rest on a figurative seesaw of expertise and technical constraints: at one end are issues of where data goes, how it is accessed, how it lives. On the other end of the plank are the actual motives, skills, techniques, models, and frameworks for processing data in digital collections into some meaningful evidence and put to use. At the fulcrum of this seesaw are the new data workers, solidifying and continuing to grow around these specialized problems of storing and processing such data collections at scale. These new data workers themselves are gradually becoming experts at mediating different kinds of evidence in order to be seen as legitimate information professionals. This paper presents a survey of emerging data work coming out of the professionalization and 'trickle down' effects of the institutionalization and enrollment of data science into higher education and the professionalization of information workers.