When a Few Data Points are Not Enough



Digitization and digital media have generated a rapid proliferation of data that is unprecedented in the history of man. This data deluge is transforming knowledge discovery and understanding in every domain of human inquiry. Large-scale computing and data-intensive methods have therefore gained acceptence in most research domains. With a preference for myopic and qualitative approaches to cultural heritage, culture researchers do in many ways represent the anti-thesis of this development. We insist on manually scrutinizing small sets of cultural expressions and mentally synthesizing our results. A “Culture Analytics” is however emerging as domain experts in history, language, and literature are starting to utilize computation and digital data to test well-established theories and find new cultural patterns. While the need for high performancing computing is still quite limited, culture analytics is changing the scale and scope of multiple disciplines in the social sciences and humanities. This talk will outline the emerging research field of culture analytics with examples from historical, literary and ethnographic research. For culture analytics to prosper, it is necessary to establish lasting collaborations between culture researchers and the computational sciences grounded in mutual interest and understanding. We argue that culture analytics can contribute with valuable domain expertise and a human perspective in data-driven research.


Culture Analytics, Cultural Heritage, Humanities at Scale, Social Sciences and Humanities