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Jonathan Gray, Carolin Gerlitz and Liliana BounegruDigital Methods Winter School 2016
University of Amsterdam
TOWARDS A LITERACY FOR DATA INFRASTRUCTURES
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1. Rethinking Data Literacy
2. De- and Re-Assembling Data Infrastructures
3. Data-Infrastructures and their Publics
4. Data-infrastructural Turn?
FOUR PARTS
1. Rethinking Data Literacy
2. De- and Re-Assembling Data Infrastructures
3. Data-Infrastructures and their Publics
4. Data-infrastructural Turn?
1.
EVERYBODY LOVESDATA LITERACY
● Data literacy as “the most important new skill of the 21st century”.
● It will “help solve world's biggest challenges”.
● The “road to the future” is paved with it.
● UN report calls for “global data literacy”.
● G8: data literacy will help to “unlock the value of open data”.
DATA LITERACIES FOCUSING ON DATASETS AS A RESOURCE
● Current conceptions of data literacy emphasize “competencies of an extractive and transformative industry” (Letouzé et al., 2015)?
● Focus on “information as a resource” (Braman, 2009: 12-15).
● Do they emphasise “auditorial” or “entrepreneurial” modes of action (Ruppert, 2012, Birchall, 2015)?
FROM DATASETSTO DATA INFRASTRUCTURES?
● Socio-technical systems implicated in the creation, processing and distribution of data.
● Relations of heterogeneous socio-technical components, rather than “things” (Star & Ruhleder, 1996)
● Between methodological inscription and multivalence?
1. Rethinking Data Literacy
2. De- and Re-Assembling Data Infrastructures
3. Data-Infrastructures and their Publics
4. Data-infrastructural Turn?
2.
DE- ASSEMBLING DATA INFRASTRUCTUREs
● Much data results from grammars of action (Agre 1994).
● Such pre-structured actions are subject to “Interpretative flexibility” (van Dijck 2013) and cross-platform syndication.
● Grammars lead to dynamic & “lively metrics” (Gerlitz & Rieder 2015).
● Data come with methodological inscriptions.
● Assembly of data & tools leads to “cascades of inscriptions” (Ruppert et al. 2013).
ALIGNMENT & MAL-ALIGNMENT
● How to re-assemble data infrastructures in imaginative ways?
● Data & methods do not come with fixed in-build purposes but need to be aligned with the research objective.
● Lure objects to pose their own problems (Lury & Wakeford 2012).
● “Interface methods” embrace productive capacities of alignment and mal-alignment (Gerlitz & Marres 2015).
1. Rethinking Data Literacy
2. De- and Re-Assembling Data Infrastructures
3. Data-Infrastructures and their Publics
4. Data-infrastructural Turn?
3.
DATA HAVE PUBLICS
● Data have publics with specific objectives, needs & skills (Ruppert 2015).
● Emerge in relation to data infrastructures.
● Operate within the tension between inscription and multi-valence of data infrastructures.
● Require specific methodological alignment.
● Mal-alignment as opportunity for intervention.
● Journalism, activism and social research as data publics.
1. Rethinking Data Literacy
2. De- and Re-Assembling Data Infrastructures
3. Data-Infrastructures and their Publics
4. Data-infrastructural Turn?
4.
CONCEPTUAL VOCABULARY
● An expansion of the concept of data literacy to go beyond competencies in reading and working with datasets.
● Accounting for wider data infrastructures which create the socio-technical conditions for the creation, extraction and analysis of data.
● Vocabulary and tactics to respond to inscriptions and biases of data infrastructures.
REMAKING DATA INFRASTRUCTURES
● Re-envisioning and re-configuring data infrastructures through methodological inventiveness and “infrastructural imagination” (Bowker 2014).
● Tactics for re-aligning them with the interests and concerns of different publics.
“DATA WORLDS”
● Data infrastructures articulate and project social worlds – or “data worlds” – which afford their own ways of knowing and possibilities for action.
● Data literacies should aim to cultivate the capacities for re-thinking, re-configuring, re-aligning, and re-imagining these data worlds, not just inhabiting them or harvesting their fruits.