{"id":2763,"date":"2013-06-25T10:53:07","date_gmt":"2013-06-25T10:53:07","guid":{"rendered":"http:\/\/blog.soton.ac.uk\/digitalhumanities\/?p=2763"},"modified":"2014-04-14T15:50:27","modified_gmt":"2014-04-14T15:50:27","slug":"digital-transformations-in-the-arts-and-humanities-big-data-workshop","status":"publish","type":"post","link":"https:\/\/digitalhumanities.soton.ac.uk\/blog\/2763","title":{"rendered":"Digital Transformations in the Arts and Humanities: Big Data Workshop"},"content":{"rendered":"
I spent today at the fascinating AHRC Big Data workshop: If you got lost (like me) @ahrcdigitrans<\/a> Big Data workshop is under here :-) pic.twitter.com\/Cyo124y4tb<\/a><\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n I made notes of what I saw as the headline issues, relating to the forthcoming funding call and what the AHRC considers of interest in the context of Big Data. The workshop was intended to influence the call. Herewith my evolving summary:<\/p>\n Working definitions of Big Data at the workshop:<\/p>\n \u00a0 Key issues:<\/p>\n His talk introduced the following examples:<\/p>\n Recently Tim Hitchcock disconnected data underlying these resources from the representation of the data via websites. Designed to support longevity of the data and respond to ever changing web design style and technologies. Need a sustainable model to revisit these. Now analysing the data e.g. distribution of trial lengths in words via word counts including references to murders in the Old Bailey Online. This allowed the identification of interesting outlying cluster related to plea bargaining. Remixing, remediation and translation of Big Data rather than making: including curated and realtime data:<\/p>\n Living media repositories: Data Flower (VRML + Java 2010); it generates flora but not in the sense of generative architecture. He prefers non-deterministic methods based on code + changing environment. He uses A-life models textured by realtime samples of flickr images tagged with \u201cflower\u201d.<\/p>\n Data_sea v1.0 (VRML + Java 2009); linking broadcast media and astronomy by visualising the \u201cradiosphere\u201d \u2013 the spread of radio throughout the universe and looking at where they interact with exoplanets. This work took abstract information and provided a visceral experience. Now looking at how to visualise ATLAS Detector data from CERN. Using artistic responses as a means to assist in data analysis through visualisation<\/p>\n Extending the idea of artwork as interface and uncovering hidden narratives e.g.<\/p>\n I am afraid looking back these notes are rather random. Hopefully something of value in there. Needs a bit of text mining :-)<\/p>\n View slides from the presentation on slide share<\/a><\/p>\n Where do images fit in the era of Big Data @flygirltwo<\/a> Discussed #readingtheriots<\/a> and the 2.6M tweets from 700,000 accounts sent during the riots (donated by Twitter). Focused on the role of rumours, the role of bots, etc.. Did incitement take place \u2013 no e.g. #riotcleanup<\/a> What was the role of different actors on twitter. (I was reminded here of work by @raminetinat<\/a>i)<\/p>\n \nFascinating talk by @flygirltwo<\/a> on social media analysis and images < reminded of http:\/\/t.co\/Mih49BEQZx<\/a> @AHRCDigiTrans<\/a> \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a>\n<\/p><\/blockquote>\n What are the role of data visualisations and how do we critically interrogate them? Is it dangerous for a visualisation to help us to understand (or think we understand) complex information? Images are not looked at a great deal in social media analysis. [One example that occurred to me was http:\/\/eprints.soton.ac.uk\/352460<\/a>]. Fascinating analysis by Farida of types of image sharing e.g. reuse of google streetmap data. You can see content being shared through different channels e.g. high quality camera footage going on via flickr and smartphone via twitpic. Also interested in deleted content e.g. image of someone with looted material that was deleted by the person but had already proliferated online. \u00a0People were also taking pictures of their TV screens as they watched the riots, and sharing these online. Journalists joined in doing this. Some people even pretended to be at the riots by sharing photos from TV. Also lots of material that was altered e.g. Tottenham presented as a war zone using Tour of Duty game imagery. Quality of imagery e.g. blurry imagery was reinforcing the veracity of the image. Really interesting aspect here of collective viewing practices. Referencing here John Berger 1992 \u2013 \u201cI have decided that this image is worth sharing\u201d. Direct visualisation rather than abstraction e.g. Lev Manovich, and reflecting on previous ideas e.g. Aby Warburg\u2019s Mnemosyne. What is the relationship between the algorithm and visibility e.g. edge rank making an image visible.<\/p>\n \nGreat insight into issues of image veracity in social media by @flygirltwo<\/a> @AHRCDigiTrans<\/a> notes @storyful<\/a> guidelines http:\/\/t.co\/LdL0RsF4XL<\/a> \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a>\n<\/p><\/blockquote>\n Storyful guidelines for social media image verification e.g. who is the photographer, image altered? Always try and get the sequence of images around the specific image. Also TinEye would be possibility.<\/p>\n Providing an overview of the existing Big Data landscape in archaeology:<\/p>\n @keith_may<\/a> introducing Archaeology and Big Data projects at @ahrcdigitrans<\/a> workshop pic.twitter.com\/w8QS2WOiA8<\/a><\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n <\/p>\n Talking about massive digital resources and activities in the British Library:<\/p>\n Talking about ResearchSpace \u2013 www.researchspace.org Talking about the Portable Antiquities Scheme \u2013 finds.org.uk Exemplary @portableant<\/a> lightning talk http:\/\/t.co\/M3gM65n7Zy<\/a> 900k objects, each 200 metadata items; 400k images; 360 projects @AHRCDigiTrans<\/a><\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n <\/p>\n Example National Archives data sets e.g. UK gov web archive. Very interested in Big Data applications to their data, and improving searchability and how you deal with poor quality (meta)data. Also interested in conceptual issues such as is this changing archives, research methods, etc.<\/p>\n @torstenreimer talking about JISC support for Big Data e.g. JANET, data centres, digital repositories, technical advisory services e.g. cloud and grid computing, tool development Re-launched website: www.jisc.ac.uk<\/a> Key messages: Think big about data \u2013 not about big data i.e. be driven by the research. And if you do have a technical need there will be new activities from JISC being planned now and they would welcome suggestions.<\/p>\n I took down the following key issues discussed in the break-out session: AHRC Collaborative skills development activity \u2013 there will be a focus on quantitative methods, and also more generally skills around new technologies, new ways of working e.g. digital literacy. How can the AHRC support more rapid development of effective multi- and inter-disciplinary working? Very positive discussion about sandpits. One legacy of the Big Data investment could be a repository of training materials. What measures? E.g. toolkit for measuring success produced by the OII \u2013 TIDSR \u2013 http:\/\/microsites.oii.ox.ac.uk\/tidsr<\/a> Use of AHRC funded resources in teaching would be a good thing to support e.g. examples integrated as part of MOOCs<\/p>\n @bbcbillt<\/a> @ahrcdigitrans<\/a> discussing Big Data as an old idea: ‘and like Breaking Bad, big data could end up as a big, bloody mess’<\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n I didn’t take many notes from the final breakout but you can get the gist from the tweeted images. The key questions for the session were:<\/p>\n Main things I noted as it went along were:<\/p>\n Breakout session notes from @ahrcdigitrans<\/a> Big Data workshop pic.twitter.com\/AZSqiz5Mav<\/a><\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n <\/p>\n More breakout session notes from @ahrcdigitrans<\/a> Big Data workshop pic.twitter.com\/XUpx1HuPz1<\/a><\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n <\/p>\n Even more breakout session notes from @ahrcdigitrans<\/a> Big Data workshop pic.twitter.com\/4zjAOV0oKV<\/a><\/p>\n \u2014 Graeme Earl (@GraemeEarl) June 25, 2013<\/a><\/p><\/blockquote>\n <\/p>\n Last set of breakout session notes from @ahrcdigitrans<\/a> Big Data workshop pic.twitter.com\/ghzZDw5Xpe<\/a><\/p>\n
\nhttp:\/\/www.ahrc.ac.uk\/News-and-Events\/Events\/Pages\/Big-Data-Workshop.aspx<\/a><\/p>\nMorning Session<\/h3>\n
Emma Wakelin<\/h4>\n
\n
Andrew Prescott<\/h4>\n
\n
\n
Tim Hitchcock<\/h4>\n
\n
\nAlso started mapping coarse-grained semantics onto these resources e.g. relationships between words associated with violence and specific types of trials at different times. Then went onto prediction of trial outcomes based on the record of the trial, and the relationship of this to changing legal and related contexts. Also interested in how you map texts into their topographic or topological location. For example, mapping word occurrence from legal documents onto streets. This provides a point of reference about how an urban space might work. We should have increasing access to context e.g. the idea of the macroscope by B\u00f6rner. Concluded by emphasising a need for Arts and Humanities scholars to look at the original, through the lens of Big Data e.g. the real face of white australia project.<\/p>\nMichael Magruder<\/h4>\n
\n
Case studies:<\/h5>\n
Scientific concepts and contexts:<\/h6>\n
Data archives:<\/h6>\n
\n
\n
Round table breakout session<\/h3>\n
\n
Afternoon<\/h3>\n
Farida Vis<\/h4>\n
Keith May<\/h4>\n
\n
Mark Flashman<\/h4>\n
\n
Adam Farquhar and James Baker<\/h4>\n
\n
Dominic Oldman<\/h4>\n
\n
\ne.g. co-referencing through context such as concepts, names and places<\/p>\nDan Pett<\/h4>\n
\n
\n900,000 objects, each with 200 pieces of metadata and 400,000 images and 360 research projects. All data are pushed through dbpedia, ordnance survey URIs, geonames etc. and about to release as CIDOC CRM.<\/p>\nValerie Johnson<\/h4>\n
Torsten Reimer<\/h4>\n
Break out session two<\/h3>\n
Bill Thompson<\/h4>\n
Final breakout session<\/h3>\n
\n
\n