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Big Data & Society

Big Data & Society


eISSN: 20539517 | ISSN: 20539517 | Current volume: 11 | Current issue: 3 Frequency: Quarterly

Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies.

The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business and government relations, expertise, methods, concepts and knowledge.

BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practices that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes.

BD&S seeks contributions that analyse Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realised (ontologies) and governed (politics).

This journal is a member of the Committee on Publication Ethics (COPE).


Article processing charge (APC)


The article processing charge (APC) for this journal is currently 2100 USD.

The article processing charge (APC) is payable when a manuscript is accepted after peer review, before it is published. The APC is subject to taxes where applicable. Please see further details here.

Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor the APC will be waived.


Digital Enhancements

Big Data & Society is a digital-only journal and its platform accommodates a variety of multimedia to present complex images and dynamic visualisations and video and audio content. It is more than simply the mere transposition of a paper version as it is published on a platform that attends to the presentational issues that Big Data analyses demand (e.g., visualisation, multimedia, interactivity, code) and the challenges that digitisation presents for the future of scientific publishing (e.g., scholarly standards, protocols and scrutiny).

While still adhering to limits in article length, we encourage authors to use rich media and multiple visualisations and, when possible, to include links to data sources in the body of their article. We avoid the use of supplementary files and instead embed all components (figures, tables, video, and any additional data files) in the article whenever possible.

We also use the power of open access to make our content as widely available as possible. We have designed a platform that allows for simple and clean presentation of a variety of content. The initial platform launched in 2014 has gone through several changes and we continue to make improvements to the design and presentation of content.

Journal Sections

While peer reviewed original research articles are the Journal's core content, we also publish a variety of other content to advance research on and communication about Big Data practices:

Peer reviewed original research articles. The core content of the Journal is double blind, triple peer reviewed original research articles of up to 10,000 words including all references and notes.

Commentaries. Short submissions (up to 3000 words) on issues, controversies, and questions that are timely and novel such as emerging theories, topics, and methods. Contributions from researchers at all career stages are encouraged and submissions are reviewed by the Editorial Team to facilitate quick turn around.

Special Themes. Collections of articles and commentaries on a focused discussion of a specific topic related to Big Data. An annual call for proposals is made every June and submissions are co-edited by the Journal Editors and Guest Editors.

Editorials. Written by Guest Editors of the annual special theme to provide an overview of the contributions.

Demos. Annual multi-media demonstrations curated by the Journal Editorial Team of new methods, visualizations, experiments and approaches to the analysis of Big Data.

Blog Sections

The Journal invites contributions to its blog site at http://bigdatasociety.net.

Essays and Provocations. Dedicated to short essays and provocations on topics relevant to the study of Big Data practices.

Blogs and Video Abstracts. Authors of articles and commentaries are invited to write short blogs and produce 3-5 minute videos about their contributions.

Please see our FAQs page for further information:
http://bigdatasoc.blogspot.co.uk/p/faqs.html

ISSN: 20539517
E-ISSN:20539517

Please direct any inquires to: bdseditors@gmail.com.

Submit your manuscript today at https://mc.manuscriptcentral.com/BDAS.

 

Big Data & Society (BD&S) is an Open Access peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies.

The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business and government relations, expertise, methods, concepts and knowledge.
BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practices that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes.
BD&S seeks contributions that analyse Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realised (ontologies) and governed (politics).
BD&S is a digital-only journal and its platform accommodates a variety of multimedia to present complex images and dynamic visualisations and video and audio content. Contents include peer reviewed research articles and colloquia as well as sections on bookcasts, think pieces, state-of-the art methods, and work by early career researchers.
 

Journal Sections

While peer reviewed original research articles are the Journal's core content, we also publish a variety of other content to advance research on and communication about Big Data practices:

Peer reviewed original research articles. The core content of the Journal is double blind, triple peer reviewed original research articles of up to 10,000 words inclusive of all references and notes.

Commentaries. Short submissions (up to 3000 words) on issues, controversies, and questions that are timely and novel such as emerging theories, topics, and methods. Contributions from researchers at all career stages are encouraged and submissions are reviewed by the Editorial Team to facilitate quick turn around. 

Special Themes. Collections of articles and commentaries on a focused discussion of a specific topic related to Big Data. Calls for special theme proposals, co-edited by the Journal Editors and Guest Editors, are posted via the journal's blog and Twitter account.

Editorials. Written by Guest Editors of the annual special theme to provide an overview of the contributions.

Demos. Annual multi-media demonstrations curated by the Journal Editorial Team of new methods, visualizations, experiments and approaches to the analysis of Big Data.

Editor-in-Chief
Matt Zook University of Kentucky, USA
Managing Editor
Jennifer Gabrys University of Cambridge, UK
Co-Editors
Rocco Bellanova Vrije Universiteit Brussels, Belgium
Dhiraj Murthy University of Texas at Austin, USA
Sung-Yueh Perng National Yang-Ming University, Taiwan
Sachil Singh York University, Canada
Ana Valdivia University of Oxford, UK
Jing Zeng Utrecht University, Netherlands
Co-Editors – Demos
Paolo Ciuccarelli Northeastern University, USA
Richard Rogers University of Amsterdam, Netherlands
Editorial Assistant
Natalia Orrego Tapia Pontifical Catholic University of Chile, CL
Assistant Editors
Sungwon Jung The University of Texas at Austin, USA
Anastassija Kostan Paderborn University, Germany
Sanjana Krishnan University of Kentucky, USA
Jianfeng Lan Shanghai Jiao Tong University, China
Kathryne Metcalf University of California San Diego, USA
Kaelynn Narita Goldsmiths, University of London, UK
El No University of Cambridge, UK
Jun Zhang University of Sheffield, UK
Advisory Board Founding Co-Editors
Adrian Mackenzie Australian National University, Australia
Irina Shklovski University of Copenhagen, Denmark
Judith Simon University of Hamburg, Germany
Editorial Board
Payal Arora Utrecht University, The Netherlands
Jo Bates University of Sheffield, UK
David Beer University of York, UK
Anders Blok University of Copenhagen
Geoffrey C. Bowker UC Irvine (Emeritus), USA
Matthew Bui University of Michigan, USA
Anita Say Chan University of Illinois, Urbana-Champaign, USA
Wen-Tsong Chiou Institutum Iurisprudentiae, Academia Sinica, Taiwan
Wendy Hui Kyong Chun Simon Fraser University, Canada
Jonathan Cinnamon University of British Columbia, Canada
Paul Dourish University of California, Irvine, USA
Nora A. Draper University of New Hampshire, USA
Ulrike Felt  
Marcus Foth Queensland University of Technology, Australia
Rafael Grohmann University of Toronto, Canada
Jeanette Hofmann WZB Berlin Social Science Center, Germany
Rob Kitchin Maynooth University, Ireland
Tahu Kukutai The University of Waikato, New Zealand
Sabina Leonelli University of Exeter, UK
Wen-yuan Lin National Tsing-Hua University, Taiwan
Deborah Lupton University of New South Wales (UNSW) Sydney, Australia
Adrian Mackenzie Australian National University, Australia
Anders Koed Madsen TANTLab - Aalborg University Copenhagen, Denmark
Noortje Marres University of Warwick, UK
Tobias Matzner Paderborn University, Germany
Stefania Milan University of Amsterdam, The Netherlands
Andrea Miller Pennsylvania State University, USA
Brent Mittelstadt University of Oxford, UK
Dawn Nafus Intel, USA
Han Woo Park Yeungnam University, South Korea
Ate Poorthuis KU Leuven, Belgium
Joanna Redden Western University, Canada
Abdul Rohman RMIT University, Vietnam
Camille Roth Humboldt-Universität, Germany
Alyssa Saiphoo Maru/Matchbox, Canada
Nick Seaver Tufts University, USA
Irina Shklovski University of Copenhagen, Denmark
Gavin J.D. Smith Australian National University, Australia
Harrison Smith University of Sheffield, UK
Monica Stephens Durham University, UK
Hallam Stevens James Cook University, Australia
Linnet Taylor Tilburg University, Netherlands
Jim Thatcher University of Washington, Tacoma, USA
José van Dijck Utrecht University, The Netherlands
Tommaso Venturini French National Centre for Scientific Research (CNRS), France
Ben Williamson University of Edinburgh, UK
Sally Wyatt Maastricht University, the Netherlands
  • Clarivate Analytics: Social Sciences Citation Index (SSCI)
  • Directory of Open Access Journals (DOAJ)
  • Google Scholar: h-5 index - 11, h-5 median - 13
  • Scopus
  • Manuscript submission guidelines can be accessed on Sage Journals.