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

TL;DR

This paper examines how digital datafication and metadata practices in big data environments often simplify complex cultural data, limiting interpretative potential and impacting future research innovation.

Contribution

It offers a systematic review of data definitions, discusses implications of digital mediation, and proposes a reconceptualization of data to preserve cultural richness.

Findings

Digital mediation constrains interpretative potential of cultural data

Metadata and computational practices can lead to data simplification

Strategies exist to bridge the gap between analogue and digital data practices

Abstract

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 for future innovation within research environments that depend on rich material yet are increasingly mediated by digital technologies. This paper presents the preliminary findings of the European-funded KPLEX (Knowledge Complexity) project which investigates the delimiting effect digital mediation and datafication has on rich, complex cultural data. The paper presents a systematic review of existing implicit definitions of data, elaborating on the implications of these definitions and highlighting the ways in which metadata and computational technologies can restrict the interpretative potential of data. It sheds light on the gap between analogue or augmented digital practices and fully computational ones, and the strategies researchers have developed to deal with this gap. The paper proposes a reconceptualisation of data as it is functionally employed within digitally-mediated research so as to incorporate and acknowledge the richness and complexity of our source materials.