Live notes from the day.
Starting the day with Dorothy Meill, Head of CHSS introducing the third annual day of ideas as a forum for those interested in digital scholarship across the University and College. Today has a mixture of internal and external speakers. Also mentions the other digital HSS activities including the website and the other events listed there.
Todays’ focus is on data as a contested but popular term. What does it mean for HSS and what traction does it have in the humanities and what currency does big data have for humanities and what are the implications for the computational turn for digital scholarship?
The event is being streamed on the website and the presentations will be posted there later.
Sian Bayne introducing Annette Markham as a theorist of the internet and is currently at Aarhus University. Her focus is on ethnographic research and the ethics of online research. She also has a good line on paper titles.
Annette Markham asking “‘Data’ what does that mean anyway?”. For the last five years or so she has been particularly pushing at thinking about method to better represent the complexities of 21st Century life. She works with STS, informatics, ethnographers, social scientists, linguists, machine learning scholars etc. The presentation is based on a series of workshops published in First Monday special issues October 2013.
Annette argues that we need to be careful about using the term data as it assumes we’re all meaning the same term. Taking a post-humanist perspective or at least non-positivist stance. It is our repsonsibility to critique the word “data”. For other researchers, data and big data are terms that seem unproblematic.
Annette is providing an overview of the debates on data and a provocation to start the day. Asking what does method mean for our forms of inquiry requires ‘method’ to be looked at sideways or from above and below ‘method’ to take account of the epistemological and political conditions for inquiry. Such conditions include funding constraints and demands around, for example, developing evidence bases and requirements for the archiving of data. But the latter is problematic in terms of capturing and tracing ethnographic research and ‘data’. Also look below ‘method’ in terms of the practices of inquiry that involve the gathering and analysing of data as well as the practices of “writing up”.
The notion of framing inquiry (Goffman) involves drawing attention to some things and excludes others – those outside the frame. Changes the frame changes the focus of inquiry and perspective of the phenomenon. Different images such as frames, a globe/ sphere, a cluster of connected nodes (sociogram or DNA) are used to critique the notion of a ‘frame’. A frame guides our view of the world but is often invisible until it is disrupted. So it is important to make the frame visible.
The term data acts as a frame but is highly ambiguous yet is often perceived as being universally understood, eg, not visible as a framing mechanism.
How are our research sensibilities being framed? To understand the question, we need to ask how are we framing culture, objects and processes of analysis and how do we frame legitimate inquiry. Culture is framed in internet studies through the changes due to the internet, as a networked culture but also how our understanding of the internet as embodied informational spaces. Interfaces developed from an interest in architecturalised spaces towards standardised interfaces to simplification as represented by Google. This is linked to the rise of commercial interests in the internet. the frame of objects and processes of inquiries has not changed much and not changed sufficiently. Inquiry involves entangled processes of social interaction online yet methods remain largely based on 19th century practices. Research models are generally based on linear processes (deductive) which acts to value linear research over messy and complex. We are still expected to draw conclusions for example. The framing of legitimate inquiry has gone backwards from the feminist work on situated knowledge and practice in the 1960s towards evidence and solutions based practices.
So what is data? An easy term to toss around to cover a lot of stuff. It is a vague term and arguably powerful rhetorical term shaping what we see and think. The term comes from 18th century sciences and popularised via translation of scientific works. As a term, ‘data’ was used as preceding an argument or analysis so data is unarguable and pre-existing – it has an “itness”. Data cannot be falsified. Data as a term refers to what a research seeks and needs for inquiry. Yet there are alternative sociological approaches involving the collection of ‘material’ to construct ‘data’ through practices of interpretation. So a very different meaning from ‘data’ as more widely used.
Refers to boyd and Crawfords 2011 provocations on big data and Baym’s 2013 work arguing that all social metrics are partial and non-representative and thereis ambiguity involved in decontextualising material from its context.
Technology now pervasive in everyday life as repsented in a Galaxy S II advert. Experiences are flattened and equalised with everything else and than flattened again as informational bits that can be diffused shared through technology.
Humans as data argument. She has nothing against data and computational analysis as such analysis is important and powerful. But wants to critique the idea that data speaks for itself and that human interaction with technology produces just data. Not all human experience is reduceable to data points. Data is never raw, it is always filtered and framed. Data operates in a larger framework of inquiry and other frameworks of inquiry exist that do not focus on data. Rather, this is inquiry that is focused on the analysis of phenomena involving play around with understanding that phenomena (not data).
Data functions powerfully as a term and acts as a frame on inquiry and this should be subject critique. Inquiry can and should be playful and generative in its entanglements with ‘the world’.
Q: what is the alternative to data? What is human experience reducible to?
A: that’s not the key question. We don’t want to think in terms of reduction which is how data generally frames inquiry.
This talk was followed by a fascinating use of crowd-sourced data coding by Prof Ken Benoit. This included completing an analysis of a UKIP manifesto during the course of the talk via cloudflower.