Digitising Cultural Complexity: Representing Rich Cultural Data in a Big Data environment

One of the major terminological forces driving ICT integration in research today is that of "big data." While the phrase sounds inclusive and integrative, "big data" approaches are highly selective, excluding input that cannot be effectively structured, represented, or digitised. Data of this complex sort is precisely the kind that human activity produces, but the technological imperative to enhance signal through the reduction of noise does not accommodate this richness. Data and the computational approaches that facilitate “big data” have acquired a perceived objectivity that belies their curated, malleable, reactive, and performative nature. In an input environment where anything can “be data” once it is entered into the system as “data,” data cleaning and processing, together with the metadata and information architectures that structure and facilitate our cultural archives, acquire a capacity to delimit what data are. This engenders a process of simplification that has major implications for the potential of future innovation within research environments that depend on rich material yet are increasingly mediated by digital technologies. It is the objective of the KPLEX project, lead by Trinity College Dublin, to explore the impact of bias in big data approaches to knowledge creation, by investigating the delimiting effect digital mediation and datafication has on rich, complex cultural data. The issues of concern to this project are all of relevance to our ways of being in the digital age, but for the purposes of this presentation, we will focus on three of the themes that the larger KPLEX project is teasing out, namely: