"The theme of the conference is the permeation of science and research with computational seeing. How does computer mediated vision as a mode of engagement with information as well as with one another effect what we see (or think we see), and what we take ourselves to know?"
The event is structured along three main topics: Changing Notions of Cognition, Changing Notions of Objectivity and Changing ontologies of scientific vision.
Image taken from onlinejournalism blog / for a viral-friendly piece of visualisation, it’s hard to beat this image of festival rainfall in the past 3 decades.
Speakers include: Peter Galison, Department of the History of Science, Harvard University, Michael Lynch, Department of Science and Technology Studies, Cornell University, Steve Woolgar, InSIS, Saïd Business School, University of Oxford and the summarising discussants are: Anne Beaulieu, Virtual Knowledge Studio, Paolo Quattrone, IE Business School and Fulbright New Century Scholar
I will be presenting a paper together with Tim Webmoore on ethics and visualisation of large scale dataset mined from the web, with a focus on twitter. We'll be using the NCL mapping project for examples, to develop an illustrated argument for ethics in this field. However, the aim is to use ethics to support this kind of research, using ethics and a clear position as a framework. We believe that such structures are of additional value to the research and researchers and ensure in the long term academic research quality and standards.
Abstract: In this paper, we examine some of the implications of born-digital research environments by discussing the emergence of data mining and analysis of social media platforms. With the rise of individual online activity in chat rooms, social networking platforms and now micro-blogging services new repositories for social science research have become available in large quantities. The change in sample sizes, for instances, from 100 participants to 100,000 is a dramatic challenge in numerous ways, technically, politically, but also in terms of ethics and visualisation. Given the changes of scale that accompany such research, both in terms of data mining and communication of results, we term this type of research 'massified research'. These challenges circle around how the scale of, and coordination work involved with, this digitally enabled research enacts different researcher-participant relationships. Consequently, much of the very innovative and creative research resulting from mining such open data sets operates on the boundaries of institutional guidelines for accountability. In this paper we argue that while the private and commercial processing of these new massive datasets is far from unproblematic, the use by academic practitioners poses particular challenges. These challenges are manifold by the augmentation of the capacity to distribute and access the results of such research, particularly in the form of web-based visualisations.
Specifically we are looking at the spatial and temporal implications of raw data and processed data. We consider the case study of using Twitter's public API or application programming interface for research and visualisation. An important spatial consequence of such born-digital research is the embedding of geo-locative technology into many of these platforms. A temporal consequence has to do with the creation of 'digital heritage', or the archiving of online traces that would otherwise be erased. To unpack these implications we consider how a selection of tweets can be collected and turned into data sets amenable to content and spatial analysis. Finally, we step through how visualisation transforms such vast quantities of tabular data into a more comprehensible format through the presentation of several visualisations generated from Twitter's API. These include what one of us has developed as 'Tweetographies' of urban landscapes, as well as examples of recent Twitter activity surrounding the disasters in Japan.
Such analysis raises issues of privacy and ethics in relation to academic ethical approval committees' standards of informed consent and risk reduction to participants. Such massified research and its outputs operate in a grey area of undefined conduct with respect to these concerns. For instance, what are the shifting boundaries of public and private space when using Twitter and other platforms like it? Are Twitter and other social media platforms' disclaimers as to privacy sufficient justification for academic and commercial use? Are the standards of social science research protocols applicable to research on and for 'the masses'?
To conclude, we discuss propose some potential best practices or protocols to extend current procedures and guidelines for such massified research.
Image taken from Nora Oberle's blog / Another beautiful data visualisation. Even though in this case, the topic is not that hilarious- it’s about news coverage of scare stories. Remember tumours and cellphones or “killer wifi”?
Full conference programm to download HERE.
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