Human-Data Interaction: Thinking beyond individual datasets

arXiv (Cornell University)

Abstract

Having greater access to data leads to many benefits, from advancing science to promoting accountability in government to boosting innovation. However, merely providing data access does not make data easy to use; even when data is openly available online, people may struggle to work with it. In this article, we draw on prior work, including our own, and a case study of Kaggle (a large online data science community) to discuss the importance of moving away from viewing datasets as static resources. Instead, we describe the view of data as a process with its own interactional affordances that offer many different possibilities for data, as well as for social interaction. We advocate for the notion of Human Data Interactions and their potential implications for various audiences.

Authors 3

1. Laura M. Koesten

   University of Vienna

   Affiliation as printed

   University of Vienna Jude Yew , Google

2. Jude Yew
3. Kathleen Gregory Aachen Centre for Science and Technology Studies

   Leiden University

   Affiliation as printed

   Centre for Science and Technology Studies , Leiden University