"Big data approaches initially suggest that objective conclusions can be drawn on a statistical basis if only comprehensive samples are available," explains Prof. Dr. Thomas Stodulka, who heads the project at Freie Universität. However, when collecting and evaluating such large data sets, there are many opportunities for one-sidedness or systematic errors. "These include, among other things, particular cultural features, linguistic complexity, the influence of historical bias, and inequalities," says Stodulka. The researchers from the Institute of Social and Cultural Anthropology will use "emotions" as an example to examine how data are collected in different disciplines and to investigate how "human factors" influence the design of data sets and how disparate sources in emotion research are leveled out.

A total of four European partners are working together in the KPLEX project: Trinity College Dublin in Ireland, Data Archiving and Networked Services in the Netherlands, and the machine translation company Tilde from Latvia, in addition to Freie Universität Berlin.