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June 26 2017 to July 11 2017 | University of Amsterdam
Deadline: May 05 2017
Updated: March 10 2017Gillian Rose employs the term visual methodologies for “researching with visual materials” (2016). Iconography, semiotics, framing analysis and multimodal analysis are among the approaches that may be applied to digital materials. One may also ask, does the online make a difference to the study of the visual? That is, with which approaches is the image considered primarily, or secondarily, as a digital object embedded in online media? Apart from the change in the setting of the object, there may also be methods that emerge from the new media, engines and platforms. What kinds of so-called ‘natively’ digital methods can be repurposed productively for visual analysis? How to make use of the Google’s reverse image search? More broadly, with the increasing focus on selfies and memes but also on Instagram stories, animated gifs, filters, stickers and emoticons, social media and digital communications are pushing for a visual turn in the study of digital culture. Such a push invites visual analysis into the realm of digital studies, too. One may begin to open the discussion of interplay by examining the new outputs such as journalists’ data visualisations as well as policy-makers’ dashboards like the open data city platforms.
One may similarly compare visual literacies. Are there new ways of interpreting images through data, both substantively (which are the related materials?) and temporally (how do they develop over time? do they resonate? are they memes?). In digital methods, the image is not only a research object but also a research device. Making images “that can be seen and manipulated” (Venturini, Jacomy & Pereira 2015) enables scholars to access and actively explore datasets. How to make them and read them? At the same time, the technical properties of digital images both in terms of their color, resolution, and timestamp, as well as their ‘networkedness’, traceability and resonance, become available for research, allowing one to think with images (as visual guides and narratives) as well as through them (as data objects). Novel visual methodologies then emerge.
There is the ‘active’ data visualisation, which includes research protocol diagrams, data dashboards, visual network analysis, and issue mapping. Protocol diagrams (Figure 1) guide analysts, programmers and designers through their collaborative research project. Data dashboards offer a visual aid for data metrics and analytics, in side-by-side graphs and tables; or become critical tools (as in the People’s Dashboard
It is not a setting for ‘just’ tool training or for principally tool-driven research. Substantive research projects are conceived and carried out. Participants are encouraged to ‘span time with their issue’ and the materials. In other words, we heed Alexander Galloway’s admonition about data and tool-driven work: “Those who were formerly scholars or experts in a certain area are now recast as mere tool users beholden to the affordances of the tool — while students spend ever more time mastering menus and buttons, becoming literate in a digital device rather than a literary corpus” (Galloway 2014:127). We encourage device and corpus literacy! The device training we ask you to do prior to the Summer School through online tutorials, and at the Summer School itself, in a kind of flipped learning environment (if you'll excuse the overused phrase), we would like to believe that you have familiarised yourself already with the tools and completed the tutorials available online. During the Summer School we will discuss and tinker with the nitty-gritty, aim to invent new methods, techniques and heuristics and create the first iterations of compelling work to be shared. About Digital Methods as a Concept Digital methods is a term coined
That is, the challenge is to study both the info-web as well as the social web with the tools that organize them. There is a general protocol to digital methods. At the outset stock is taken of the natively digital objects that are available (links, tags, threads, etc.) and how devices such as search engines make use of them. Can the device techniques be repurposed, for example by remixing the digital objects they take as inputs? Once findings are made with online data, where to ground them? Is the baseline still the offline, or are findings to be grounded in more online data? Taking up these questions more theoretically (but also practically) there is also a Digital Methods book