We are pleased to announce that the journal Big Data & Society has been accepted into the multidisciplinary Social Sciences Citation Index (SSCI) by Clarivate Analytics. The journal's Impact Factor of 4.577 ranks it as the second highest journal (out of 108) in the Social Sciences Interdisciplinary domain of the SSCI. More information on SSCI can be found here: https://clarivate.com/webofsciencegroup/solutions/webofscience-ssci/.
We are proud of this accomplishment and thank our authors, reviewers and editors for all their hard work. The journal could not have achieved this without you. We look forward to continuing to offer feedback and space for thoughtful and innovative research on big data practices.
BD&S is a SAGE open access, double blind peer-reviewed scholarly journal. It publishes interdisciplinary research 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. After launching in 2014, it has published over 300 original research articles, commentaries, demonstrations, and editorials in a series of special theme collections. Visit the journal web site at https://journals.sagepub.com/home/bds.
Showing posts with label Announcements. Show all posts
Showing posts with label Announcements. Show all posts
Thursday, 9 July 2020
Tuesday, 10 December 2019
Winter break
The journal Big Data and Society will be on winter break from December 21st to January 5th. Please accept any delays in processing and reviewing your submission, and in related correspondence during that time.
Happy Holidays!
Happy Holidays!
Monday, 8 July 2019
Summer break
The Big Data and Society Editorial Team will be on summer break from July 15th until August 15th. Please accept delays in processing and reviewing your submission during that time.
Many thanks for your understanding.
Many thanks for your understanding.
Friday, 14 June 2019
Call for Special Theme Proposals for Big Data & Society
The SAGE open access journal Big Data & Society (BD&S) is soliciting proposals for a Special Theme to be published in late 2020 or early 2021. BD&S is a peer-reviewed, interdisciplinary, scholarly journal that publishes research 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 crowd-sourced 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.
Special Themes can consist of a combination of Original Research Articles (8000 words; maximum 6), Commentaries (3000 words; maximum 4) and one Editorial (3000 words). All Special Theme content will be waived Article Processing Charges. All submissions will go through the Journal’s standard peer review process.
Past special themes for the journal have included: Knowledge Production, Algorithms in Culture, Data Associations in Global Law and Policy, The Cloud, the Crowd, and the City, Veillance and Transparency, Environmental Data, Spatial Big Data, Critical Data Studies, Social Media & Society, Assumptions of Sociality, Health Data Ecosystems and Data & Agency. See http://journals.sagepub.com/page/bds/collections/index to access these special themes.
Format of Special Theme Proposals
Researchers interested in proposing a Special Theme should submit an outline with the following information.
- An overview of the proposed theme, how it relates to existing research and the aims and scope of the Journal, and the ways it seeks to expand critical scholarly research on Big Data.
- A list of titles, abstracts, authors and brief biographies. For each, the type of submission (ORA, Commentary) should also be indicated. If the proposal is the result of a workshop or conference that should also be indicated.
- Short Bios of the Guest Editors including affiliations and previous work in the field of Big Data studies. Links to homepages, Google Scholar profiles or CVs are welcome, although we don’t require CV submissions.
- A proposed timing for submission to Manuscript Central. This should be in line with the timeline outlined below.
Information on the types of submissions published by the Journal and other guidelines is available at https://us.sagepub.com/en-us/nam/journal/big-data-society#submission-guidelines.
Timeline for Proposals
Please submit proposals by September 1, 2019 to the Managing Editor of the Journal, Prof. Matthew Zook at zook@uky.edu. The Editorial Team of BD&S will review proposals and make a decision by November 2019. Manuscripts would be submitted to the journal (via manuscript central) by or before March 2020. For further information or discuss potential themes please contact Matthew Zook at zook@uky.edu.
Monday, 18 June 2018
Data Associations in Global Law and Policy
Lyria Bennett Moses, Fleur Johns, Daniel Joyce
Shifting forms can create toeholds for thought and action. Complex social phenomena that tend to confound diagnosis may sometimes be grasped obliquely in the course of their transformation. The aim of this special issue is to trace mutations underway in associations rendered or experienced in data. In particular, contributors to this issue reflect upon associations traceable in data that are of a juridical nature (or could be so understood), or that have salience for legal institutions and norms. This is something other than inviting consideration of ‘problems’ that technology makes for law. It is something other, too, than thinking about whether law does or does not determine or reflect socio-technical practice, or vice versa, and how some law-technology correspondence might ‘properly’ be maintained. Instead, contributors engage here in a collective experiment of envisioning data as vectors of lawful relations on the global plane, and at other scales.
This is unfinished business for Big Data & Society. In this journal’s opening issue, Rob Kitchin argued that “the development of digital humanities and computational social sciences… propose radically different ways to make sense of culture, history, economy and society”. But what “sense” could “Big Data empiricism”, as Kitchin described it, make in, of and for global law and policy? This is among the questions that the contributors to this special issue take up. Neither digital technology nor law is pivotal to this inquiry, so much as their irrepressible leaking and morphing into would-be or could-be versions of the other.
As paradigmatic a shift as the turn to epistemologies of Big Data might seem, making connections between these emergent epistemologies and older associations is also an important task of this collection. Sheila Jasanoff traces, for instance, the history of the production of “a panoptic viewpoint from which the entire diversity of human experience can be seen, catalogued, aggregated, and mined” from the mid-twentieth century, especially in the emergence of the “global environment” as an “actionable object for law and policy”. Naveen Thayyil likewise draws an analogy between change in weather and climatological studies from the 1960s onwards (from instrument reading techniques to computer modeling) and parallel shifts in approaches to risk regulation (from conventional risk assessment to precautionary approaches, the latter increasingly advanced through “big data” automation). Ben Hurlbut similarly connects “scientifically authorized imaginations of future risk” on the global plane to earlier incarnations of the “republic of science” assembled around pandemic risk since the nineteenth century. Other contributions to this volume re-frame contemporary phenomena by reference to associations of more recent provenance: Sarah Logan analyses “post 9-11 mass surveillance” and the “anxious information state” it enshrines. Likewise, Gavin Smith; Kath Albury, Jean Burgess, Ben Light, Kane Race, Rowan Wilken; and Daniel Joyce focus on “data cultures” ascendant during the past decade and the legal and political conflicts and connections that surface amid them.
The protagonists and environs of the stories told in these pages vary greatly. Not all are of a kind that one might expect to find featured in a journal about “Big Data and Society”. Scientists keep company with museum designers; government officials rub shoulders with journalists and activists; terrorists and those who hunt them mingle with weather forecasters; software and search engine developers are interspersed with “quantified selves”; dating app users fraternize with bird watchers contributing to citizen science initiatives. What Daniel Joyce calls “the challenge and opportunity of big data” turns out to have stakes for many who may not see themselves as so invested or enrolled. Nonhuman protagonists are similarly diverse and varied in sophistication and scale. They include files (both paper and digitized), reports, remote sensors, satellites and diverse forms of scientific equipment, viruses and the organisms that transmit them, government computer systems and the smart phones ubiquitous across many parts of the world. Settings range from Hawaii’s Mauna Loa observatory to the ICRC’s Red Cross and Red Crescent Museum in Geneva, from Indonesian bird markets to gatherings of scientific experts, from courtrooms and security agencies to the hybrid space of screen-mediated sexual encounters. To draw all these persons, places and things into a collective account of contemporary juridical mediation in data is, from one angle, preposterous. And yet the very preposterousness of this agglomeration conveys something of the voracious indifference, roving opportunism, and endless repurposing characteristic of new analytical methods and software designs that aim to extract actionable insight from massive datasets using machine learning and other automated techniques.
The dilemmas with which these protagonists grapple, or the conditions under which they come to be datafied, are similarly diverse. Nonetheless, common quandaries recur in the stories that our contributors relate. One is the difficulty of trying to generate or project a sense of a whole out of unresolved difference, or making the global – as such – available to experience and asserting sovereignty over its scalar elements. As this volume makes plain, this quintessentially modern challenge persists amid tendencies that seem aimed in another direction: towards data-driven personalization, nano-surveillance and therapeutic attention to the singular.
A second theme that emerges from this collection surrounds the actual and potential substance of legal order. Long-held ideas endure about sociality and culture, on one hand, and market-based exchange, on the other, as that which comprises the “stuff” of which order is made, and that which legal norms and institutions must foster and defend. Yet this collection entertains a further, speculative idea: that there may be forms of relation of growing significance, manifest or realised in data, not reducible to the expression or defence of exchange or socio-emotional connection, but which nonetheless have legal ramifications. That is, digital data may be “lay[ing] the groundwork for new claims and appeals to conscience” and responsibility (Jasanoff in this volume) and constituting “moral and technical borderland[s] where powerful agencies… coalesce” (Smith in this volume). Consider, for example, relations of correlation between data patterns associated with a terror suspect, and data patterns identified with other persons, in the surveillance work of which Sarah Logan writes in this volume. Correlations in data create a basis for supposition and the visualization of juridical futures, in such a setting, without necessarily corresponding to any apparent economic or social relation. Consider, also, the celebrity-follower relation maintained online, of which Daniel Joyce writes in this volume when discussing recent judicial efforts to protect reputation online. This tie is not quite explicable in terms of economic relations, nor in terms of conventional sociality, although both may be imbricated within it.
Thus, when the contributors to this volume write of data associations in global law and policy, they write not just of pre-existing relations finding expression (accurately or otherwise) in data or being reoriented or “nudged” by data-driven operations and designs. They write also of data as a medium for publicly imagining and re-imagining those relations. Distinct legal and political cultures predispose publics towards adopting quite divergent ways of perceiving and representing global conditions in data, contributors to this volume show. Only by taking account of this divergence and variety, Sheila Jasanoff contends herein, might we recognize “official forgetfulness and underestimation” in the “data practices of ruling institutions” and discern the unanswered pleas for justice embedded in those. We invite you to read and engage with these provocative works and look forward to tracing their afterlife in your writings.
Shifting forms can create toeholds for thought and action. Complex social phenomena that tend to confound diagnosis may sometimes be grasped obliquely in the course of their transformation. The aim of this special issue is to trace mutations underway in associations rendered or experienced in data. In particular, contributors to this issue reflect upon associations traceable in data that are of a juridical nature (or could be so understood), or that have salience for legal institutions and norms. This is something other than inviting consideration of ‘problems’ that technology makes for law. It is something other, too, than thinking about whether law does or does not determine or reflect socio-technical practice, or vice versa, and how some law-technology correspondence might ‘properly’ be maintained. Instead, contributors engage here in a collective experiment of envisioning data as vectors of lawful relations on the global plane, and at other scales.
This is unfinished business for Big Data & Society. In this journal’s opening issue, Rob Kitchin argued that “the development of digital humanities and computational social sciences… propose radically different ways to make sense of culture, history, economy and society”. But what “sense” could “Big Data empiricism”, as Kitchin described it, make in, of and for global law and policy? This is among the questions that the contributors to this special issue take up. Neither digital technology nor law is pivotal to this inquiry, so much as their irrepressible leaking and morphing into would-be or could-be versions of the other.
As paradigmatic a shift as the turn to epistemologies of Big Data might seem, making connections between these emergent epistemologies and older associations is also an important task of this collection. Sheila Jasanoff traces, for instance, the history of the production of “a panoptic viewpoint from which the entire diversity of human experience can be seen, catalogued, aggregated, and mined” from the mid-twentieth century, especially in the emergence of the “global environment” as an “actionable object for law and policy”. Naveen Thayyil likewise draws an analogy between change in weather and climatological studies from the 1960s onwards (from instrument reading techniques to computer modeling) and parallel shifts in approaches to risk regulation (from conventional risk assessment to precautionary approaches, the latter increasingly advanced through “big data” automation). Ben Hurlbut similarly connects “scientifically authorized imaginations of future risk” on the global plane to earlier incarnations of the “republic of science” assembled around pandemic risk since the nineteenth century. Other contributions to this volume re-frame contemporary phenomena by reference to associations of more recent provenance: Sarah Logan analyses “post 9-11 mass surveillance” and the “anxious information state” it enshrines. Likewise, Gavin Smith; Kath Albury, Jean Burgess, Ben Light, Kane Race, Rowan Wilken; and Daniel Joyce focus on “data cultures” ascendant during the past decade and the legal and political conflicts and connections that surface amid them.
The protagonists and environs of the stories told in these pages vary greatly. Not all are of a kind that one might expect to find featured in a journal about “Big Data and Society”. Scientists keep company with museum designers; government officials rub shoulders with journalists and activists; terrorists and those who hunt them mingle with weather forecasters; software and search engine developers are interspersed with “quantified selves”; dating app users fraternize with bird watchers contributing to citizen science initiatives. What Daniel Joyce calls “the challenge and opportunity of big data” turns out to have stakes for many who may not see themselves as so invested or enrolled. Nonhuman protagonists are similarly diverse and varied in sophistication and scale. They include files (both paper and digitized), reports, remote sensors, satellites and diverse forms of scientific equipment, viruses and the organisms that transmit them, government computer systems and the smart phones ubiquitous across many parts of the world. Settings range from Hawaii’s Mauna Loa observatory to the ICRC’s Red Cross and Red Crescent Museum in Geneva, from Indonesian bird markets to gatherings of scientific experts, from courtrooms and security agencies to the hybrid space of screen-mediated sexual encounters. To draw all these persons, places and things into a collective account of contemporary juridical mediation in data is, from one angle, preposterous. And yet the very preposterousness of this agglomeration conveys something of the voracious indifference, roving opportunism, and endless repurposing characteristic of new analytical methods and software designs that aim to extract actionable insight from massive datasets using machine learning and other automated techniques.
The dilemmas with which these protagonists grapple, or the conditions under which they come to be datafied, are similarly diverse. Nonetheless, common quandaries recur in the stories that our contributors relate. One is the difficulty of trying to generate or project a sense of a whole out of unresolved difference, or making the global – as such – available to experience and asserting sovereignty over its scalar elements. As this volume makes plain, this quintessentially modern challenge persists amid tendencies that seem aimed in another direction: towards data-driven personalization, nano-surveillance and therapeutic attention to the singular.
A second theme that emerges from this collection surrounds the actual and potential substance of legal order. Long-held ideas endure about sociality and culture, on one hand, and market-based exchange, on the other, as that which comprises the “stuff” of which order is made, and that which legal norms and institutions must foster and defend. Yet this collection entertains a further, speculative idea: that there may be forms of relation of growing significance, manifest or realised in data, not reducible to the expression or defence of exchange or socio-emotional connection, but which nonetheless have legal ramifications. That is, digital data may be “lay[ing] the groundwork for new claims and appeals to conscience” and responsibility (Jasanoff in this volume) and constituting “moral and technical borderland[s] where powerful agencies… coalesce” (Smith in this volume). Consider, for example, relations of correlation between data patterns associated with a terror suspect, and data patterns identified with other persons, in the surveillance work of which Sarah Logan writes in this volume. Correlations in data create a basis for supposition and the visualization of juridical futures, in such a setting, without necessarily corresponding to any apparent economic or social relation. Consider, also, the celebrity-follower relation maintained online, of which Daniel Joyce writes in this volume when discussing recent judicial efforts to protect reputation online. This tie is not quite explicable in terms of economic relations, nor in terms of conventional sociality, although both may be imbricated within it.
Thus, when the contributors to this volume write of data associations in global law and policy, they write not just of pre-existing relations finding expression (accurately or otherwise) in data or being reoriented or “nudged” by data-driven operations and designs. They write also of data as a medium for publicly imagining and re-imagining those relations. Distinct legal and political cultures predispose publics towards adopting quite divergent ways of perceiving and representing global conditions in data, contributors to this volume show. Only by taking account of this divergence and variety, Sheila Jasanoff contends herein, might we recognize “official forgetfulness and underestimation” in the “data practices of ruling institutions” and discern the unanswered pleas for justice embedded in those. We invite you to read and engage with these provocative works and look forward to tracing their afterlife in your writings.
Photo credit: Dominik Bartsch via Flickr CC BY 2.0
Monday, 4 June 2018
Call for Special Theme Proposals for Big Data & Society
The SAGE open access journal Big Data & Society (BD&S) is soliciting proposals for a Special Theme to be published in early 2019. BD&S is a peer-reviewed, interdisciplinary, scholarly journal that publishes research 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 crowd-sourced 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.
Special Themes can consist of a combination of Original Research Articles (8000 words; maximum 6), Commentaries (3000 words; maximum 4) and Editorial (3000 words). All Special Theme content will be waived Article Processing Charges. All submissions will go through the Journal’s standard peer review process.
Past special themes for the journal have included: Knowledge Production, Algorithms in Culture, Data Politics, Data Associations in Global Law and Policy, The Cloud, the Crowd, and the City, Veillance and Transparency, Environmental Data, Spatial Big Data, Critical Data Studies, Social Media & Society, Assumptions of Sociality and Data & Agency. See http://journals.sagepub.com/page/bds/collections/index for more information.
Format of Special Theme Proposals
Researchers interested in proposing a Special Theme should submit an outline with the following information.
Information on the types of submissions published by the Journal and other guidelines is available at https://us.sagepub.com/en-us/nam/journal/big-data-society#submission-guidelines.
Timeline for Proposals
Please submit proposals by Tuesday July 3, 2018 to the Managing Editor of the Journal, Prof. Matthew Zook at zook@uky.edu. The Editorial Team of BD&S will review proposals and make a decision by mid- to late-July 2018.
For further information or discuss potential themes please contact Matthew Zook at zook@uky.edu.
Special Themes can consist of a combination of Original Research Articles (8000 words; maximum 6), Commentaries (3000 words; maximum 4) and Editorial (3000 words). All Special Theme content will be waived Article Processing Charges. All submissions will go through the Journal’s standard peer review process.
Past special themes for the journal have included: Knowledge Production, Algorithms in Culture, Data Politics, Data Associations in Global Law and Policy, The Cloud, the Crowd, and the City, Veillance and Transparency, Environmental Data, Spatial Big Data, Critical Data Studies, Social Media & Society, Assumptions of Sociality and Data & Agency. See http://journals.sagepub.com/page/bds/collections/index for more information.
Format of Special Theme Proposals
Researchers interested in proposing a Special Theme should submit an outline with the following information.
- An overview of the proposed theme, how it relates to existing research and the aims and scope of the Journal, and the ways it seeks to expand critical scholarly research on Big Data.
- A list of titles, abstracts, authors and brief biographies. For each, the type of submission (ORA, Commentary) should also be indicated. If the proposal is the result of a workshop or conference that should also be indicated. Short Bios of the Guest Editors including affiliations and previous work in the field of Big Data studies. Links to homepages, Google Scholar profiles or CVs are welcome, although we don’t require CV submissions.
- A proposed timing for submission to Manuscript Central.
Information on the types of submissions published by the Journal and other guidelines is available at https://us.sagepub.com/en-us/nam/journal/big-data-society#submission-guidelines.
Timeline for Proposals
Please submit proposals by Tuesday July 3, 2018 to the Managing Editor of the Journal, Prof. Matthew Zook at zook@uky.edu. The Editorial Team of BD&S will review proposals and make a decision by mid- to late-July 2018.
For further information or discuss potential themes please contact Matthew Zook at zook@uky.edu.
Sunday, 21 January 2018
2018 Update on BD&S
After three
years of operation, we have established a strong foundation, with over 160
articles and commentaries published. We have also assembled 11 special
themes overseen by Guest Editors that cover topics such as ‘the cloud, the
crowd and the city’ and ‘practicing, materializing and contesting environmental
data.’ We have been accepted into the Emerging Sources Citation Index (ESCI),
which will benefit our authors by giving our published papers greater
discoverability, leading to increased citations. We have calculated our Impact
Factor (IF) for 2016 at 1.925 (we are still waiting for Clarivate
Analytics’ response to our request to be indexed). And we have migrated to a
new platform - Atypon’s Literatum platform - that has improved
functionality and navigation possibilities.
We have also
merged the Early Career Researcher Forum with the Commentaries section and will
be actively soliciting contributions from researchers at different stages of
their careers. Guidelines on all types of submissions to the Journal can
be found here.
Finally, after
a successful beginning to our section on Special Themes we will now be making
an annual call for proposals in June of each year. These will be announced on
the blog and Twitter.
Open Access
We are an Open
Access journal but our initial three year waiver of article processing charges
(APCs) has ended. As of July 2017 original research articles (ORA) accepted
after peer review are now subject to an Open Access APC of $800. Authors who do
not have funding for Open Access publishing can request a waiver from the
publisher, SAGE, once their ORA is accepted after peer review. For all other
content (Commentaries, Editorials, Demos) and ORAs commissioned by the Editor
as part of Special Themes, the APC will be waived. We look forward to your
submissions and continuing to publish critical work on the changing landscape
of Big Data and society.
Saturday, 20 January 2018
Renewing the Journal Leadership
With the ringing in of the New Year we are
happy to announce changes to the Journal as part of our objective to
periodically renew its leadership.
Editorial Team and Board
We have renewed the Editorial leadership of
the Journal to ensure it remains dynamic. Three new co-editors joined our
Editorial Team (ET) in 2017: Agnieszka Leszczynski, Environment Department, The
University of Auckland, NZ; Dhiraj Murthy, Department of Journalism and
Sociology at the University of Texas at Austin, US; and Jennifer Gabrys,
Department of Sociology at Goldsmiths University of London, UK. Additionally,
we have introduced a new position, that of Managing Editor.
Co-editor Matt Zook, Department of Geography, University of Kentucky, US
has moved into this position and Evelyn Ruppert will continue as Editor.
We are also pleased to announce that Age Poom, Department of Geography, University of Tartu, EE will assume the position of Editorial Assistant. We have also renewed our Editorial Board to ensure that we expand the range of researchers engaged in the Journal. To that end, some existing members are not continuing and we are pleased to welcome a dozen new members. The new list of ET and EB members can be found here.
Thank you
We acknowledge with thanks the
contributions of previous members of our Editorial Team: Co-Editors, Adrian
Mackenzie and Irina Shklovski; Editorial Assistant Ville Takala; and all the
Editorial Board members not continuing with the Journal. Additionally,
the Journal would not be possible and successful without the work of
innumerable reviewers. We have learned greatly from their insights and the
quality of the Journal attests to their efforts and commitment.
Tuesday, 16 May 2017
The Cloud, the Crowd, and the City: How New Data Practices Reconfigure Urban Governance
Phil Ashton, Rachel Weber and Matthew Zook
The urban archetype of the flâneur, so central to the concept of modernity, can now experience the city in ways unimaginable one hundred years ago. Strolling around Paris, the contemporary flâneur might stop to post pictures of her discoveries on Instagram, simultaneously identifying points of interest to the rest of her social network and broadcasting her location (perhaps unknowingly). The café she visits might be in the middle of a fundraising campaign through a crowdfunding site such as Kickstarter, and she might be invited to tweet to her followers in exchange for a discount on her pain au chocolate. As she ambles about Paris, the route of her stroll is captured by movement sensors positioned on top of street lights, and this data – aggregated with that of thousands of other pedestrians – could be used by the City of Paris to sync up transit schedules. And if those schedules were not convenient, she might tap Uber to whisk her home to her threadbare pension booked on AirBnB.
This vignette attests to the transformation of the urban experience through technology-enabled platforms that allow for the quick mobilization and exchange of information, public services, surplus capacity, entrepreneurial energy, and money. However, these changes have implicated more than just consumers, as multiple technologies have been taken up in urban governance processes through platforms variously labeled as Big Data, crowd sourcing, or the sharing economy. These systems combine inexpensive data collection and cloud-based storage, distributed social networks, geotagged locational sensing, mobile access (often through “app” platforms), and new collaborative entrepreneurship models to radically alter how the needs of urban residents are identified and how services are delivered and consumed in so-called “smart cities” (Townsend 2013).
In the rhetoric used by their boosters, the vision and practice of these technologies “disrupts” existing markets by harnessing the power of “the crowd” – a process fully evident in sectors such as taxi (Uber/Lyft), hoteling (AirBnB), and finance (peer-to-peer lending). However, the notion of disruption has also targeted government bureaucracies and public services, with new initiatives seeking to insert crowd mechanisms or characteristics – at once self-organizing and collectively rational (Brabham 2008) – into public policy. These mechanisms envision reconfiguring the traditional relationship of public powers with planning and governance by vesting data collection and problem-solving in crowd-like institutional arrangements that are partially or wholly outside the purview of government agencies. While scholars are used to talking about “governance beyond-the-state” (Swyngedouw 2005) in terms of privatization and a growing scope for civil society organizations, technological intermediation potentially changes the scale and techniques of governance as well as its relationship to sovereign authority.
For instance, civic crowdfunding models have emerged as new means of organizing public service provision and funding community economic development by embracing both market-like bidding mechanisms and social-network technologies to distribute responsibility for planning and financing socially-desirable investments to laypeople (Brickstarter 2012; Correia de Freitas and Amado 2013; Langley and Leyshon 2016). Other practices are even more radical in their scope. Toronto’s Urban Repair Squad – an offshoot of the aptly named Critical Mass bike happenings – urges residents to take transportation planning into their own hands and paint their own bike lanes. Their motto: “They say city is broke. We fix. No charge.” (All that is missing is the snarky “you’re welcome” at the end.)
Combined, these emerging platforms and practices are challenging the tactics, capabilities, and authorizations employed to define and govern urban problems. This special theme of Big Data & Society picks up these issues, interrogating the emergence of digital platforms and smart city initiatives that rely on both the crowd and the cloud (new on-demand, internet-based technologies that store and process data) to generate and fold Big Data into urban governance. The papers contained herein were presented as part of a one-day symposium held at the University of Illinois at Chicago (UIC) in April 2015 and sponsored by UIC’s Department of Urban Planning and Policy. Setting aside the tired narratives of individual genius and unstoppable technological progress, workshop participants sought to understand why these practices and platforms have recently gained popularity and what their implementation might mean for cities. Papers addressed numerous questions: How have institutional supports and political-economic contexts facilitated the ascendance of “crowd” and “cloud” models within different spheres of urban governance? How do their advocates position them relative to imaginaries of state or market failure/dysfunction? What kinds of assumptions and expectations are embedded in the design and operation of these platforms and practices? What kinds of institutional reconfigurations have been spurred by the push to adopt smart city initiatives? How is information collected through these initiatives being used to advance particular policy agendas? Who is likely to benefit from them?
The four articles in this special theme take different slices on these questions. Robert Lake’s analysis reviews the ontology and politics of Big Data practices beginning with the recognition that issues of definition and politics are fundamental to data collection in cities. From this foundation, he focuses his paper on the concern that Big Data suffers not only from the politicization of practice, but from its foundational ontological premise of “hyper-individualism” – i.e., or treating persons, events and phenomenon within a city as independent units unconnected to each other or to any larger context. Similarly, John West’s research focuses on the abstracting logics of Big Data in the case of a large public school in the Bronx and how Big Data systems, implemented with the laudable goal of increasing transparency, instead resulted in what he terms new “opacities.” West argues that by opening new scales of analysis for comparison and benchmarking – the teacher, the classroom, the school – this Big Data exercise transferred knowledge and power from classroom and principals to central city administrators, facilitating systemic reorganization to the detriment of the quality of this particular high school.
Taylor Shelton’s article draws on the concept of “performativity” to argue that the sources of Big Data are changing the way decision makers are conceptualizing the city, resulting in changes to the types of policies and interventions that are planned. He critiques the “new urban science” that seeks to borrow methods drawn from the natural sciences and apply them to urban geography and planning. Such a borrowing ensures that quantitative analysis is the only correct approach, resulting in an ontological definition of the city reduced to whatever is most easily counted and valorizing technical expertise while issues of injustice or local concerns are rendered less important. Matthew Zook first reviews the genealogy of key ideas within smart city governance and earlier antecedents generated by motivations for social justice and progressive socio-economic reform that differ quite markedly from the goals emerging from today’s technology and neoliberal rhetoric. Recognizing the promise of Big Data for urban governance, he also cautions that “metrics don’t simply measure; in the process of deciding what is important and possible to measure, these data are simultaneously defining what cities are” (p. 15).
As a collection, these papers offer insights into how future research into smart city initiatives might examine the nexus of Big Data and urban governance. Their contributions can be read as both methodological and political. By combining close attention to the work of socio-technical systems of measurement with institutional ethnographies or studies of policy-making controversies, the papers show how data is enmeshed in the dynamics of austerity, privatization, or neoliberal urbanism more generally. Here, smart city initiatives might be read as institutional practices of control, rooted in attempts to produce an actionable future out of a chaotic and ever-changing present. Whereas this necessarily highlights how data systems strip urban problems out of their context to make them actionable for policymakers – a point reinforced by all the papers – it also shows Big Data's highly-productive role in animating the thick relational entities known as institutions. Whether we're looking at the apparatuses of urban security or the role of data analytics in restructuring public school systems, the hyper-individualism of measurement (as noted in Lake's paper) is but one moment in a rich process of institutional transformation.
The urban archetype of the flâneur, so central to the concept of modernity, can now experience the city in ways unimaginable one hundred years ago. Strolling around Paris, the contemporary flâneur might stop to post pictures of her discoveries on Instagram, simultaneously identifying points of interest to the rest of her social network and broadcasting her location (perhaps unknowingly). The café she visits might be in the middle of a fundraising campaign through a crowdfunding site such as Kickstarter, and she might be invited to tweet to her followers in exchange for a discount on her pain au chocolate. As she ambles about Paris, the route of her stroll is captured by movement sensors positioned on top of street lights, and this data – aggregated with that of thousands of other pedestrians – could be used by the City of Paris to sync up transit schedules. And if those schedules were not convenient, she might tap Uber to whisk her home to her threadbare pension booked on AirBnB.
This vignette attests to the transformation of the urban experience through technology-enabled platforms that allow for the quick mobilization and exchange of information, public services, surplus capacity, entrepreneurial energy, and money. However, these changes have implicated more than just consumers, as multiple technologies have been taken up in urban governance processes through platforms variously labeled as Big Data, crowd sourcing, or the sharing economy. These systems combine inexpensive data collection and cloud-based storage, distributed social networks, geotagged locational sensing, mobile access (often through “app” platforms), and new collaborative entrepreneurship models to radically alter how the needs of urban residents are identified and how services are delivered and consumed in so-called “smart cities” (Townsend 2013).
In the rhetoric used by their boosters, the vision and practice of these technologies “disrupts” existing markets by harnessing the power of “the crowd” – a process fully evident in sectors such as taxi (Uber/Lyft), hoteling (AirBnB), and finance (peer-to-peer lending). However, the notion of disruption has also targeted government bureaucracies and public services, with new initiatives seeking to insert crowd mechanisms or characteristics – at once self-organizing and collectively rational (Brabham 2008) – into public policy. These mechanisms envision reconfiguring the traditional relationship of public powers with planning and governance by vesting data collection and problem-solving in crowd-like institutional arrangements that are partially or wholly outside the purview of government agencies. While scholars are used to talking about “governance beyond-the-state” (Swyngedouw 2005) in terms of privatization and a growing scope for civil society organizations, technological intermediation potentially changes the scale and techniques of governance as well as its relationship to sovereign authority.
For instance, civic crowdfunding models have emerged as new means of organizing public service provision and funding community economic development by embracing both market-like bidding mechanisms and social-network technologies to distribute responsibility for planning and financing socially-desirable investments to laypeople (Brickstarter 2012; Correia de Freitas and Amado 2013; Langley and Leyshon 2016). Other practices are even more radical in their scope. Toronto’s Urban Repair Squad – an offshoot of the aptly named Critical Mass bike happenings – urges residents to take transportation planning into their own hands and paint their own bike lanes. Their motto: “They say city is broke. We fix. No charge.” (All that is missing is the snarky “you’re welcome” at the end.)
Combined, these emerging platforms and practices are challenging the tactics, capabilities, and authorizations employed to define and govern urban problems. This special theme of Big Data & Society picks up these issues, interrogating the emergence of digital platforms and smart city initiatives that rely on both the crowd and the cloud (new on-demand, internet-based technologies that store and process data) to generate and fold Big Data into urban governance. The papers contained herein were presented as part of a one-day symposium held at the University of Illinois at Chicago (UIC) in April 2015 and sponsored by UIC’s Department of Urban Planning and Policy. Setting aside the tired narratives of individual genius and unstoppable technological progress, workshop participants sought to understand why these practices and platforms have recently gained popularity and what their implementation might mean for cities. Papers addressed numerous questions: How have institutional supports and political-economic contexts facilitated the ascendance of “crowd” and “cloud” models within different spheres of urban governance? How do their advocates position them relative to imaginaries of state or market failure/dysfunction? What kinds of assumptions and expectations are embedded in the design and operation of these platforms and practices? What kinds of institutional reconfigurations have been spurred by the push to adopt smart city initiatives? How is information collected through these initiatives being used to advance particular policy agendas? Who is likely to benefit from them?
The four articles in this special theme take different slices on these questions. Robert Lake’s analysis reviews the ontology and politics of Big Data practices beginning with the recognition that issues of definition and politics are fundamental to data collection in cities. From this foundation, he focuses his paper on the concern that Big Data suffers not only from the politicization of practice, but from its foundational ontological premise of “hyper-individualism” – i.e., or treating persons, events and phenomenon within a city as independent units unconnected to each other or to any larger context. Similarly, John West’s research focuses on the abstracting logics of Big Data in the case of a large public school in the Bronx and how Big Data systems, implemented with the laudable goal of increasing transparency, instead resulted in what he terms new “opacities.” West argues that by opening new scales of analysis for comparison and benchmarking – the teacher, the classroom, the school – this Big Data exercise transferred knowledge and power from classroom and principals to central city administrators, facilitating systemic reorganization to the detriment of the quality of this particular high school.
Taylor Shelton’s article draws on the concept of “performativity” to argue that the sources of Big Data are changing the way decision makers are conceptualizing the city, resulting in changes to the types of policies and interventions that are planned. He critiques the “new urban science” that seeks to borrow methods drawn from the natural sciences and apply them to urban geography and planning. Such a borrowing ensures that quantitative analysis is the only correct approach, resulting in an ontological definition of the city reduced to whatever is most easily counted and valorizing technical expertise while issues of injustice or local concerns are rendered less important. Matthew Zook first reviews the genealogy of key ideas within smart city governance and earlier antecedents generated by motivations for social justice and progressive socio-economic reform that differ quite markedly from the goals emerging from today’s technology and neoliberal rhetoric. Recognizing the promise of Big Data for urban governance, he also cautions that “metrics don’t simply measure; in the process of deciding what is important and possible to measure, these data are simultaneously defining what cities are” (p. 15).
As a collection, these papers offer insights into how future research into smart city initiatives might examine the nexus of Big Data and urban governance. Their contributions can be read as both methodological and political. By combining close attention to the work of socio-technical systems of measurement with institutional ethnographies or studies of policy-making controversies, the papers show how data is enmeshed in the dynamics of austerity, privatization, or neoliberal urbanism more generally. Here, smart city initiatives might be read as institutional practices of control, rooted in attempts to produce an actionable future out of a chaotic and ever-changing present. Whereas this necessarily highlights how data systems strip urban problems out of their context to make them actionable for policymakers – a point reinforced by all the papers – it also shows Big Data's highly-productive role in animating the thick relational entities known as institutions. Whether we're looking at the apparatuses of urban security or the role of data analytics in restructuring public school systems, the hyper-individualism of measurement (as noted in Lake's paper) is but one moment in a rich process of institutional transformation.
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