Guest Editors: Andrew Iliadis (Purdue University) and Federica
Russo (Universiteit van Amsterdam).
Critical Data Studies (CDS) is a growing field of research that
focuses on the unique theoretical, ethical, and epistemological challenges
posed by “Big Data.” Rather than treat Big Data as a scientifically empirical,
and therefore largely neutral phenomena, CDS advocates the view that data
should be seen as always-already constituted within wider data assemblages.
Assemblages is a concept that helps capture the multitude of ways that
already-composed data structures inflect and interact with society, its
organization and functioning, and the resulting impact on individuals’ daily
lives. CDS questions the many assumptions about data that permeate contemporary
literature on information and society by locating instances where data may be
naively taken to denote objective and transparent informational entities. CDS may be viewed as an emerging field connected to Information
Ethics, Software Studies, and Critical Information Studies in that it seeks to
question the ethical import of information and Big Data for society. Problems
of causality, quality, security, and uncertainty concern CDS scholars. Recent
articles outlining the theoretical program of CDS offer a new platform from
which to question data in this manner. We seek essays for this special volume
that broaden these latest commitments in CDS to include new empirical research
projects on information and communication technologies (ICTs) that fall under
the umbrella of Big Data, while also seeking to question their attendant
epistemological shifts. Through the critical lens of ethics and morality, this
special volume opens up CDS to localizations where Big Data can no longer be
seen as neutral, and where an ethics of Big Data might emerge. Issues of interest include (but are not limited to):
- Causality: how should we find causes in the
era of ‘data-driven science?’ Do we need a new conception of causality to fit
with new practices?
- Quality: how should we ensure that data are
good enough quality for the purposes for which we use them? What should we make
of the open access movement; what kind of new technologies might be needed?
- Security: how can we adequately secure
data, while making it accessible to those who need it? How do we protect
databases?
- Uncertainty: can Big Data help with
uncertainty, or does it generate new uncertainties? What technologies are
essential to reduce uncertainty elements in data-driven sciences?
Proposals
of 1000 words are invited for consideration and inclusion in the Special Theme for an Original Research
Article, Commentary, or essay in the
Early Career Research Forum section. All submissions of Original Research Articles are double-blind, and triple peer-reviewed. Commentaries and
ECR submissions are reviewed by the Guest Editors.
Proposals should be sent to the Guest Editors: ailiadis@purdue.edu and f.russo@uva.nl
Proposal Deadline: July 10, 2015
Notification of Acceptance: end of July
Submission Deadline: October 4, 2015
Reviews Returned: end of December
Revised Paper Deadline: February 29, 2016
Anticipated Publication Date: Spring/Summer
2016
Update: We have extended the proposal deadline to July 24th