Abstract for “Fog of Finance? Visualising Offshore and the Aesthetics of Uncertainty” at MoneyLab #6, University of Siegen

Following is the abstract for our contribution on “The Fog of Finance? Visualising Offshore and the Aesthetics of Uncertainty” at the upcoming MoneyLab #6: Infrastructures of Money hosted by the Institute of Network Cultures and the University of Siegen. This is based on a collaboration between the Tax Justice Network, the University of Sussex, Density Design and the Public Data Lab. The MoneyLab #6 programme is available here, and the abstracts are available here.

Fog of Finance? Visualising Offshore and the Aesthetics of Uncertainty
Chris Anderson (University of Leeds)
Angeles Briones (DensityDesign Lab, Politecnico di Milano)
Jonathan Gray (King’s College London)
Daniel Haberly (University of Sussex)
Michele Mauri (DensityDesign Lab, Politecnico di Milano)
Tommaso Venturini (CNRS)


What can be learned from data practices to render offshore financial flows visible and actionable for advocacy, policy and public debate? How can data visualisations be used to narrate the scale and dynamics of offshore financial activity? How can they convey uncertainty without insinuating sublime unfathomability? How might the communication of what we know and what we don’t know about offshore finance both draw on, complement and modify existing visual cultures, practices and aesthetics of uncertainty? What might critical or inventive data practices for visualising offshore finance look like?

This paper explores the making of an Atlas of Offshore FDI as a collaboration between the Tax Justice Network, a network of researchers and research centres and the Public Data Lab. Foreign Direct Investment (FDI) is supposed to reflect bricks-and-mortar investments and “real” acquisitions by multinational corporations, and is often considered to be the backbone of globalization (Haberly & Wójcik, 2015). However, roughly two thirds of total global FDI is either from or in jurisdictions widely used as domiciles for shell companies and corporate inversions – most often for purposes of tax avoidance. Despite international action to address offshore tax avoidance and financial secrecy, there is still no publicly available dataset that allows for the FDI entering countries via particular offshore jurisdictions to be traced back to its ultimate origin. The Atlas of Offshore FDI aims to explore the scale and significance of this offshore activity, as well as to shed new light onto its contents, by creating the first publicly available database of global offshore investment.

The project explores combination and modification of visual practices for making sense of transnational economic activity and financial flows (Gray, Bounegru, Milan, & Ciuccarelli, 2016), as well as visual practices for representing uncertainty. While public data practices often emphasise and value the production of certainty (Anderson, 2018), this project considers what data projects may learn from diverse cultures for visually representing, managing and articulating uncertainty, including in physics (electron clouds), meteorology (weather conditions), statistics (confidence margins) and art history (landscape painting).

As well as reflecting on the prospects of critical data practice around financial flows (Gray & Bounegru, forthcoming), the paper situates the atlas project against broader debates around the knowability, unknowability and governability of transnational economic activity (Slobodian, 2018) and the infrastructural configurations of relations between markets, states and citizens (Roberts, 2011).

References

Anderson, C. W. (2018). Apostles of Certainty: Data Journalism and the Politics of Doubt. Oxford: Oxford University Press.

Gray, J., & Bounegru, L. (forthcoming). Introduction. In The Data Journalism Handbook: Towards a Critical Data Practice. Amsterdam: Amsterdam University Press.

Gray, J., Bounegru, L., Milan, S., & Ciuccarelli, P. (2016). Ways of Seeing Data: Toward a Critical Literacy for Data Visualizations as Research Objects and Research Devices. In Kubitschko, Sebastian & Kaun, Anne (Eds.), Innovative Methods in Media and Communication Research (pp. 227–251). London: Palgrave Macmillan.

Haberly, D., & Wójcik, D. (2015). Tax havens and the production of offshore FDI: an empirical analysis. Journal of Economic Geography, 15, 75–101.

Roberts, A. (2011). The Logic of Discipline: Global Capitalism and the Architecture of Government. Oxford: Oxford University Press.

Slobodian, Q. (2018). Globalists: The End of Empire and the Birth of Neoliberalism. Cambridge, MA: Harvard University Press.

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Talk: “What Does Data Do? Making Data Public, Keeping Data Private and Other Data Worlds”, Privacy Camp 2019, Brussels

Notes from my contribution to a panel on “Reimagining Data Futures: Data and Agency” at Privacy Camp 2019 with Minna Ruckenstein (Consumer Society Research Centre, University of Helsinki), Mirko Tobias Schäfer (Utrecht Data School, University of Utrecht) and Stefania Milan (DATACTIVE, University of Amsterdam), moderated by Imge Ozcan (Law, Science, Technology & Society, Vrije Universiteit Brussel).

Picture from Monique Mann.

Thank you so much for inviting me to join you today. I wish I could be there in person, but I’m happy to be able to “dial in”.

I wanted to start by stepping back and asking:

  • What is data?
  • What is datafication?
  • What can data do?
  • How might we intervene around it?
  • Who gets to shape the future of the “data society”?

It is important to keep asking such questions because the answers we give – about what data is, why it matters and what is at stake – can inform different kinds of responses and interventions, perhaps different kinds of data politics. Answering such questions involves empirical specification, conceptual elaboration and critical reflection (perhaps one of the areas where activists, organisations and researchers convened by Privacy Camp may work together).

There are many ways in which data and data infrastructures can become what the science and technology studies scholar Bruno Latour calls “matters of concern”.

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New Book Chapter: “Making Data Public? The Open Data Index as Participatory Device” in Good Data (Amsterdam, Institute of Network Cultures: 2019)

A book chapter on “Making Data Public? The Open Data Index as Participatory Device” co-authored with Danny Lämmerhirt has just been published in a new open access book on Good Data. The book is part of the Theory on Demand series of the Institute of Network Cultures in Amsterdam, founded by media theorist and activist Geert Lovink. You can find more about the book here and a direct link to the PDF is here.

The chapter draws on ongoing research around my Data Worlds book, research collaborations and experiments around doing participation with data (including with the Public Data Lab) as well as research, policy and advocacy work at the civil society organisation Open Knowledge International. Here’s the abstract:

The Open Data Index is a ‘civil society audit’ which strives to shape the availability and openness of public sector data from around the world. In this chapter we examine the social life of this project, including how it evolved, the changing visions and practices associated with it, and how it serves to assemble and involve different publics in the assessment of institutional practices and forms of datafication. Drawing on recent work on statactivism, data activism and the performative effects of numbers, rankings and indices, we look at how the index organises participation and data politics in specific ways, raising questions about not only making data public but also the making of public data. It plays two roles which are sometimes in tension: (i) conventionalising assessment to facilitate comparability, and (ii) reflecting the diversity of different interests, issues and settings involved in opening up public sector data. It also facilitates the creation of ‘enumerated entities’ as objects of concern in open data advocacy and policy. The Open Data Index may thus be viewed as a site where participation is both configured and contested, and where practices of valuation and enumeration are both conventionalised and brought into question.

The full reference for our chapter is:

Gray, J., & Lammerhirt, D. (2019). Making Data Public? The Open Data Index as Participatory Device. In A. Daly, S. K. Devitt, & M. Mann (Eds.), Good Data. Amsterdam: Institute of Network Cultures.

The book is edited by Angela Daly, S. Kate Devitt and Monique Mann, and there are chapters on indigenous data sovereignty, “good enough data”, energy data, data journalism, communal data sharing, data ethics, data activism, accounting for network practices, designing with data and more.

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Interview on new edition of Data Journalism Handbook

As Liliana Bounegru and I are preparing the manuscript of the Data Journalism Handbook: Towards A Critical Data Practice (forthcoming, Amsterdam University Press), here is the full transcript of an interview we did about the book with the European Journalism Centre in December 2018, selections of which were published here and here.

Why another Data Journalism Handbook

We were really lucky with the previous edition, which seemed a good fit for the moment in 2012. It has been widely translated and adopted as a core text on data journalism courses and trainings around the world. We designed it to age well, providing not just practical guidance on how to work with data, but also a diverse snapshot of the hopes and practices of data journalists at that particular moment in time.

The field of data journalism has travelled a long way since 2012. Not just because of more sophisticated technologies, but also because the social, cultural, political and economic settings of the field have changed. We’ve seen not only major initiatives like the Snowden leaks and the Panama Papers, but also debates and controversies around the role of data, platforms and digital technologies in society. Lots of tough questions have been raised about what data journalism is, who it is for and what it might do in digital societies.

Rather than just having a narrower focus on data practices, we take a broader look at these questions and consider what we might learn from them. In parallel to doing the first edition of the handbook, we’ve also gone through our graduate studies and into universities where we’ve been researching these kinds of questions about the societal implications of digital data, methods and platforms. The new edition of the book is our attempt to make sense of the field of data journalism and its changing role in the contemporary world, thinking along with a diverse mix of practitioners and researchers.

A lot has changed since 2012 in the data journalism landscape, what does it mean for the book and for you as editors?

To use a metaphor: there was a time when the number of readily available books in the world was small enough that it was not considered crazy for a librarian to try to build what they could consider a pretty comprehensive collection of books. Their acquisitions policy could just be: “whatever we can get our hands on”. In 2012, it might have not have seemed so crazy to, for example, have a go at making a list of data journalists and their projects from around the world. One very practical consequence for us as editors is that we cannot kid ourselves about our partiality: can only hope to cover a comparatively small number of the projects, practices and themes in this ever-growing field, and it was a difficult job to decide what to focus on in the book.

Also, as we’ve mentioned above, there have been many debates and controversies about the role and status of data journalism, which we’ve sought unpack and address in the book, as well as examining its relation to other developments. Since 2012 we have seen the rise of questions about the societal implications of technology precipitated by actors, events and issues as diverse as Snowden, Trump, Brexit, Bolsonaro, Xi Jinping, the Syrian civil war, Cambridge Analytica, Gamergate, #metoo, #IdleNoMore, Black Lives Matter, strikes and walkouts from tech workers, Uber riots, the European refugee crisis, Facebook’s News Feed algorithms, “fake news” and misinformation, the Gab platform and the rise of far-right populism and extremism. Several chapters in the book suggest how data journalists might attend to and position themselves in relation to such phenomena.

In 2012, there were not so many resources for learning data journalism. Now there are plenty more. How will this book be different from other data journalism resources out there?

There are indeed now so many useful resources (and there were too in 2012) – from practical tutorials and MOOCs on tools, code, visualisations, design and machine learning techniques, to “behind the scenes” blog posts and commentaries. Such resources will continue to evolve and are “best served fresh” from a variety of different sources.

The new edition of the book takes a step back from this more “hands on” material, and provides space to reflect on different aspects of contemporary data journalism practice. We have felt such a need for such a book when teaching data journalism on several courses – and in particular to complement more practical materials with practitioner perspectives as well as research perspectives from fields such as science and technology studies, media studies, internet studies and journalism studies. This provides a richer context for introducing data journalists’ particular blend of methods and approaches for working with data – examining not just the “how” but also the “what”, “where”, “when”, “why” and “for whom”.

How did you personally fall into data journalism? What fascinates you about it?

We both have a professional background in this area, and met at a data journalism conference which Liliana organised in Amsterdam in 2010. At that time Jonathan was working at an NGO called Open Knowledge International and particularly interested in data visualisations and the politics of public data (also going back to early 20th century experiments such as the Isotype Institute), at the same time as pursuing his graduate studies in London. Liliana was leading data journalism activities at the European Journalism Centre, at the same time as undertaking graduate studies at the Digital Methods Initiative at the University of Amsterdam (where she later became Managing Director).

We were both fascinated by emerging practices around how the world is accounted for through data – not just through established institutions such as national statistics bodies, but also through experimental and inventive modes of storytelling and participation with data in journalism and civil society. Such data practices would not just produce accounts of the world through data, but they’d also have to assemble publics for their work. We were also interested in how such projects would aspire to attend to collective life at scale, including environmental, social, political, economic and cultural dynamics beyond the to-and-fro of talking heads.

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Table of contents and chapter previews for “The Data Journalism Handbook: Towards a Critical Data Practice”

As we announced last year, Liliana Bounegru and I are currently co-editing a new edition of the The Data Journalism Handbook which will be published on Amsterdam University Press next year.

As it says in the introduction, the book is “a collective experiment in accounting for data journalism practices and a collective invitation to explore how such practices may be modified”. This includes broadening accounts of data journalism projects to further explore their various settings:

The collection of chapters gathered in the book aim to provide a richer story about what data journalism does, with and for whom. Through our editorial work we have encouraged both reflection and a kind of modesty in articulating what data journalism projects can do, and the conditions under which they can succeed. This entails the cultivation of a different kind of precision in accounting for data journalism practice: specifying the situations in which it develops and operates. Such precision requires broadening the scope of the book to include not just the ways in which data is analysed, created and used in the context of journalism but also more about the social, cultural, political and economic circumstances in which such practices are embedded.

We’ve also proposed “twelve challenges for critical data practice”, drawing on Agre’s notion of “critical technical practice” which he describes in terms of having “one foot planted in the craft work of design and the other foot planted in the reflexive work of critique”.

Ahead of the book’s publication next year, and as part of the process of gathering feedback on its content and our editorial approach, we’re publishing online previews of several of the chapters. A working version of the full table of contents for the book is included below.

Beyond these online previews of chapters, if you’re interested testing out further material from the book in the context of teaching or training, please do get in touch. We’re particularly interested in hearing from those who are considering adopting it as on university or higher educational courses for undergraduate and graduate students.

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New project: What can citizen-generated data do? Research collaboration around UN Sustainable Development Goals

Yellow Bar Island Habitat Creation balloon mapping from July 2012,
Gena Wirth, Public Lab.

A new research initiative led by the Public Data LabKing’s College London and Open Knowledge International in collaboration with the Global Partnership for Sustainable Development Data and the UN Foundation will map and explore what “citizen-generated data” can do, with a particular focus on the UN Sustainable Development Goals. It will be undertaken ahead of the World Data Forum in October.

The initiative will explore projects, practices and visions associated with citizen-generated data, including: What does citizen-generated data do? How is it imagined, created and used by different actors? What kinds of participation, experience, subjectivity and politics do citizen-generated data projects enable and engender?

It is informed by our recent work on “data infrastructure literacy”, “data worlds”, the “data city as public experiment”, experimentation around air quality data, as well as our previous research collaborations around how citizens and civil society groups can assemble data to attempt to change what is officially accounted for.

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Panel on “Data Worlds” at EASST2018

I’m co-convening a panel on “Data Worlds? Public Imagination and Public Experimentation with Data Infrastructures” at EASST2018 – the latest edition of the conference of the European Association for the Study of Science and Technology – which takes place on 25-28th July 2018 at Lancaster University, UK.

The panel is organised by several colleagues at the Public Data Lab, including Noortje Marres (University of Warwick), Carolin Gerlitz (University of Siegen), Tommaso Venturini (École Normale Supérieure Lyon) and myself.

We had a very interesting set of papers submitted in response to the CFP that went out in December, and further details about the panel (including talks and abstracts) are available here and copied below.

For more about this theme you can also refer to two recent open access articles on “Data Infrastructure Literacy” and “Data Worlds”.

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New Essay: “The Data City as Public Experiment?”

An essay on “The Data City as Public Experiment?” that I wrote with Noortje Marres (Centre for Interdisciplinary Methodologies, University of Warwick) has just come out in London Ideas, a new publication from the Centre for London. You can download a PDF of the piece here. The précis is as follows:

Cities have long been imagined as “machines for living”, and today’s data technologies carry the promise of making them more “intelligent” – more attuned to the lives of citizens; better able to ensure feedback and the re-adjustment of relations between people, environments, and institutions. How might data, and data culture, play a role in reshaping city life, for whom, and to what end?

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New Article: “Data Infrastructure Literacy”, Big Data & Society

An article on “Data infrastructure literacy” that I co-authored with with Carolin Gerlitz and Liliana Bounegru has just been published in Big Data & Society. The abstract and full reference for the article are copied below. The article is open access and you can download the PDF here.

Data infrastructure literacy

Jonathan Gray, Carolin Gerlitz, Liliana Bounegru

A recent report from the UN makes the case for “global data literacy” in order to realise the opportunities afforded by the “data revolution”. Here and in many other contexts, data literacy is characterised in terms of a combination of numerical, statistical and technical capacities. In this article, we argue for an expansion of the concept to include not just competencies in reading and working with datasets but also the ability to account for, intervene around and participate in the wider socio-technical infrastructures through which data is created, stored and analysed – which we call “data infrastructure literacy”. We illustrate this notion with examples of “inventive data practice” from previous and ongoing research on open data, online platforms, data journalism and data activism. Drawing on these perspectives, we argue that data literacy initiatives might cultivate sensibilities not only for data science but also for data sociology, data politics as well as wider public engagement with digital data infrastructures. The proposed notion of data infrastructure literacy is intended to make space for collective inquiry, experimentation, imagination and intervention around data in educational programmes and beyond, including how data infrastructures can be challenged, contested, reshaped and repurposed to align with interests and publics other than those originally intended.


Gray, J., Gerlitz, C., & Bounegru, L. (2018). Data Infrastructure Literacy. Big Data & Society, 5, 1–13.

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New Project: “Save Our Air”

Today the Public Data Lab is launching its Save Our Air project, which explores how data can be used to attend to and assemble people around different aspects of air pollution.

As well as focusing on how data can represent air pollution levels in the context of science and policy, it looks at how “situating techniques” can provide new perspectives and involve different publics – such as experiments in “personalised” measurement with school pupils, mapping the landscape of issues and actors associated with air pollution on digital media and examining how different actors apportion blame and responsibility.

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