Big data, bigger dilemmas: A critical review

Abstract

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate amongst its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with an eye on a domain-specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socio-economic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that need to receive more attentionautonomy, opacity, and generativity, disparity, and futurity -leading to questions and ideas for moving beyond dilemmas.

Digital Service Innovation Enabled by Big Data Analytics - A Review and the Way Forward

“…While the generativity of digital platforms has been studied thoroughly [17] [74], that of big data has been rarely discussed [83]. In addition, the relationship between platform generativity and big data remains untapped in the context of service innovation.…”

A Framework for the Assessment of Research and Its Impacts

“…Availability refers to general alternatives and choices that affect the data to be used, for instance (without being complete): sampling vs census, freely available vs controlled or undisclosed ones, data as consumption vs participation (see Ekbia et al (2015) for a critical discussion). Obviously, the minimal requirement for the elaboration of data refers to its availability in a usable way.…”

“…It is crucial for data integration of heterogeneous sources (see Daraio Glänzel (2016). See also the discussion on continuity vs innovation in Ekbia et al (2015)). A great improvement in data integration for research assessment could come by the adoption of an Ontology-Based-Data-Management (OBDM) approach (Lenzerini, 2011).…”

“…There is little agreement in the literature. More balanced views emerging from a critical analysis of the current literature are also available (Debackere, 2016;Ekbia et al, 2015), leading the information systems community to further deeply analyze the critical challenges posed by the big data development (Agarwal & Dhar, 2014).…”

Big Data Revisited: A Rejoinder

“…Other issues touch upon long--standing epistemological conundrums, being tied to modes of scientific inquiry and the role data as encoded evidence plays in this process (see e.g. Gitelman, 2013;Ekbia et al, 2014). The list can no doubt be expanded.…”