The ongoing Research Themes in 2017 are:
• Temporalities of Data
• Data Citizenship
• Digital Labour
• Materialities of Computation
• Methods, Methods
Research Themes also aim at supporting Junior Research projects and new grant applications. Please contact the affiliated researchers if you have a PhD proposal or would like to initiate collaboration through a project that falls under one of these themes. Please note that some researchers have more than one affiliation, so do specify the area you are interested in!
Temporalities of Data
Affiliated Researchers: Rachel Douglas-Jones, Marisa Cohn, Laura Watts
This research area puts questions of data temporality centre stage. In a world where immediacy is highlighted, we ask about the long duree. In logics of linearity, we ask about alternative evolutions, branchings and lifecycles. In a culture of the sparkling new, we look at creaking deaths and forgettings, as systems, codes and interfaces are painstakingly repaired or made obsolete. This is a research area which thinks there is sufficient experience to know that decay comes, systems built are lived with, formats change over time, and the futures we make in the present rapidly become our pasts. We advocate for the wisdom to counter a techno-optimistic hubris, and seek solutions for living with and caring for data in all its temporalities.
Keywords: maintenance, obsolesence, formats, care, temporality, futures
Data Citizenship
Affiliated Researchers : Christina Neumayer, Luca Rossi
This research area addresses problems of citizenship being increasingly defined by (big) data. Modern forms of citizenship assume that large quantities of information produced by people everyday and turned into data, might be a credible source to understand the needs of citizens in a democratic society. The idea of “data citizenship” assumes that the citizens will be visible to the state with the data they produce in their everyday life (such as registration in an online portal to access public services, or data produced by using public transport using a ‘smart’ payment method). The underlying ratio of big-data shifts citizenship from an intrinsic status of a group of people to a status achieved through (consumerist) action that leaves traces of data. Big data analysis is understood as a viable way to describe existing phenomena by categorization and to predict future developments. Large quantities of information and their automated analyses give big-data an apparently neutral, effective and efficient appearance. These two dimensions – size and unobstrusiveness – frame the contemporary big-data discussion without offering a critical exploration of the underlying assumption for collecting data to challenge the idea of the existence of raw data.
Through critical inquiry ETHOS researchers aim to debunk the misconception that the application of data-mining techniques on large quantities ‘raw data’, provides insights about citizens’ behaviour. Four key questions in this research area are:
1. What processes of data citizenship can we observe and what are the effects?
2. How does the relationship between data, citizen, public services and data analysts increasingly define citizenship?
3. How can automated categorisation and sorting processes lead to new marginalization and exclusion of citizens?
4. Which problems do we encounter at the intersection of data citizenship and surveillance?
Keywords: citizenship, big data, categorisation, exclusion, mining, behaviour, surveillance
Digital Labour
Affiliated Researchers: Christopher Gad, Morten Hjelholt, Ingmar Lippert, Vasilis Galis
Digial Labour is a research area organised around three core issues for contemporary organisations in an era of intensifying data work.
1. How do data – in various forms – occupy a growing role in how organisations see themselves and make knowledge about their surroundings, whether that is clients, customers, citizens, or publics.?How this information is organised and put to use is an empirical question we pursue by investigating data based strategy and data management in the reflexive organisation.
2. How are new forms of data are used as a basis for decisions? What does it take to generate organizational priorities from data sets and what form does that data need to take to be persuasive? As scholars in STS, we posit that orgnisations and their data work could always be otherwise. They are political, a matter of situated practice: organising and doing data. Ethnographic work with data driven decisions therefore provides the opportuity to show the possibilities for data-working to stablise policy and practice, maintain or subvert ideological organisational agendas and trajectories in the context of decisionmaking.
3. What is the labour of data-work? Both data and digitalisation efforts involve work. This work is shaped both by information infrastructures and by people who work with data – to manage and govern it, to generate, select, curate, store and maintain datasets and databases. We are therefore interested in data work as a form of labour, in the situated politics and micropolitical economies of data work, and in the tactics data workers pursue within and on their organisational infrastructures.
Keywords: data, work, organizations, management, decisions, labour, policy, publics
Materialities of Computation
Affiliated Researchers : Marisa Cohn, Lucian Lehu, Esther Fritsch, James Maguire Nanna Gorm
Computation may seem to be composed of abstractions and algorithms, but recent research has focused on its materialities: the forms that computation takes – from databases to IoT devices – as well as the infrastructures – undersea cables, data centers, and services – that sustain computing and make it possible.
Taking a lens of materiality on computing enables us to consider computation as an accomplishment that requires many kinds of artifacts from notes on a whiteboard, to software architecture diagrams, to wires, storage devices, micro-controllers and censors. This research area takes up the concern of how computational methods become materialized in different projects. In particular we are interested in considering how data might be generated through an approach that takes this material embodiment of computation seriously.
• What are the material forms of computation and how do we study them?
• What does it mean to take the material embodiment of computation seriously?
• How does the lens of materiality change our analytic attention?
• How might the design of a computational technique or method, consider computation embedded within material environments, or performed in material spaces?
Keywords: materialities, infrastructures, design, artifacts
Methods, Methods
Affiliated Researchers: Brit Ross Winthereik,
As a techno-humanities laboratory, we fuse the potential of big data with the insights of thick, ethnographic observation. Asking questions about what data ‘is’ and ‘does’ involves attending to data in both its material and representational forms, and asking how the mode of enquiry informs research findings.
Projects under the Methods, Methods research area explore the affordances of new data collection and analysis methods, alongside the power of ethnographic analysis. We are interested in the new availabilities of data, in the way methods choices inform the questions that can be asked, and the key moments of translation and transformation in analysis. Data colleciton and analysis happen in research and in industry, both subject to organizational contingencies.
• What are the characteristics of high-speed, high-volume analysis, and what are its limitations?
• How do borrowed cartographic languages inform how data is conceptualised?
• What are the politics of choice in representation?
Keywords: methods, description, observation, computation, data, analysis, translation
