A Map for Big Data Research in Digital Humanities
Frédé́ric Kaplan · Frontiers in Digital Humanities · 2015
This article is an attempt to represent Big Data research in digital humanities as a structured research field.A division in three concentric areas of study is presented.Challenges in the first circlefocusing on the processing and interpretations of large cultural datasets -can be organized linearly following the data processing pipeline.Challenges in the second circle -concerning digital culture at large -can be structured around the different relations linking massive datasets, large communities, collective discourses, global actors, and the software medium.Challenges in the third circledealing with the experience of big data -can be described within a continuous space of possible interfaces organized around three poles: immersion, abstraction, and language.By identifying research challenges in all these domains, the article illustrates how this initial cartography could be helpful to organize the exploration of the various dimensions of Big Data Digital Humanities research. ImmersiveHow can effective immersion be designed?How can full-fledged environment be created based on big cultural datasets (Greengrass and Hughes 2008)?How can collective experiences occur in immersive situations?How can uncertainty in 3d world be conveyed (Bentkowska-Kafel et al. 2012)?How can the effectiveness of immersive environment be evaluated in various contexts (museum, schools, etc.)?