{"id":4900,"date":"2019-03-15T23:18:08","date_gmt":"2019-03-16T03:18:08","guid":{"rendered":"http:\/\/studentwork.prattsi.org\/foundations\/?p=4900"},"modified":"2019-03-15T23:20:17","modified_gmt":"2019-03-16T03:20:17","slug":"a-little-messiness-some-clutter-and-ongoing-revelationss","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/foundations\/2019\/03\/15\/a-little-messiness-some-clutter-and-ongoing-revelationss\/","title":{"rendered":"(A Little) Messiness, (Some) Clutter, and (Ongoing) Revelations(s)"},"content":{"rendered":"\n
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Vi\u00e9gas and Wattenberg, presenting in the clutter<\/figcaption><\/figure><\/div>\n\n\n\n

As introduced by Miya Masaoka (Director of the Sound Art Program at Columbia\u2019s School of the Arts and coordinator of the Artists Using Data series), Fernanda Vi\u00e9gas and Martin Wattenberg are \u201cpioneers in data visualization and analytics\u201d who have \u201cshaped the field\u201d and crafted tools and interactions that have been \u201cused by millions of people.\u201d (A similar description is on their collaborative site<\/a>.)<\/p>\n\n\n\n

Working to a more succinct description, their business cards would formally present them as members of Google\u2019s PAIR (People+AI Research) initiative and Big Picture team. As simply defined by themselves at this presentation, they are scientists and artists \u2014 a dichotomy that would give many pause, but is no doubt a complementary pairing for many in the field.
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While the work of such individuals inevitably links or crosses from one title to another, their presentation on March 8, \u201cMessiness, Clutter, and Revelation,\u201d focused on their work outside of Google, wherein they have explored new ways to use and investigate data, even as they set constraints within which to play with it. In that spirit of limiting parameters (and an eye to brevity), this review will contain itself to their work and philosophies as shared at this event, \u201can informal talk\u201d in a mid-renovation space \u2014 a fitting format and environment for a presentation that ultimately moved toward the playful and iterative natures of both data exploration and artistic expression.
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Vi\u00e9gas and Wattenberg essentially took turns presenting a small selection of work, individual and collaborative, all initially produced between 2003 and 2012, but timeless in their foundational role for the artists and others. Collectively, they defined an arc where the titular elements contributed to insights for the makers but also produced pieces of art \u2014 or at least design that moonlights as art.
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This is evident, perhaps, in a project like History Flow<\/a><\/strong> (2003), explored initially as a \u2018scientific probe\u2019 in response to the then-new(ish) Wikipedia now residing at MoMA. This elegant visual investigation tracked the editing of Wikipedia entries, including the back and forth of dueling ideologies on matters adorable and political. In sharing examples of internet favorites such as \u2018cat\u2019 and hot-button issues like \u2018abortion,\u2019 the patterns of editing and relative passion in each is unmistakable. Yet, when asked if a visualization that compared the different kinds of impassioned debates had been attempted to establish a pattern, Wattenberg responded with a simple \u201cNo, but someone should do that.\u201d
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\u201cUsing data to know things\u201d and questions of technological limitations or permutations were explored in The Art of Reproduction<\/a><\/strong> (2011); specifically an understanding of \u201cHow the internet is lying to you\u201d through the varied representations of a single artwork that can be found online \u2014 from the decaying gold of Klimt (26 Danaes) to the deceptive black-and-white of Mapplethrope (8 Kens and Roberts). Which is the true reproduction work? Or aren\u2019t they all?
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This compilation of a single vision or a larger \u2018truth\u2019 from a messy table was also evident in Flickr Flow<\/a><\/strong> (2009),  a commission that sought to visualize the city of Boston, starting with the particularly \u2018dirty\u2019 data set of Flickr images tagged simply as \u201cBoston Common.\u201d The duo let those limitations and what they brought guide the form, stating: \u201cLet\u2019s work with that messiness; see what we can find.\u201d The result is an elegant abstraction of ribbons that looks nothing like (but also, somehow, very much like) Boston year-round. In the process of its creation, it investigates what we as a society have preserved.
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Other works explored how we search (Web Seer<\/a><\/strong>, 2009) , how \u201cthe alien mind\u201d thinks (Thinking Machine<\/a><\/strong>, 2003) and how music might be visualized (The Shape of Song<\/a><\/strong>, 2002), with the last cited as \u201dan example of clutter yielding something useful.\u201d
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The presentation culminated with Wind Map<\/a><\/strong> (2012\u2013). Also in MoMA, this piece was the most clear presentation of the pair\u2019s iterative approach to data visualization, a case study that showed explorations from the abstract to the psychedelic, with the \u2018final\u2019 version resulting from the addition of a single line of code to an earlier iteration. Starting with the simple, seemingly ethereal (and almost Ono-esque) question \u201cWhat does the wind look like?\u201d and the desire to \u201cmake complex data easily accessible,\u201d they created \u2014 they would have us believe unwittingly \u2014 a practical and emotional tool.
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The resulting real-time visualization was picked up by meteorologists and combined with other data in weather maps, but also caused Louisiana residents in the path of Hurricane Isaac to reach out to the artists as they tracked the storm in real time. It was also picked up by school teachers and other scientists who used it to teach and to study their own passions. None of these were intentions; they were all unexpected results.
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The unexpected results of Wind Map<\/figcaption><\/figure><\/div>\n\n\n\n

Indeed, through almost all of the works presented, Vi\u00e9gas and Wattenberg seemed to speak to the utility of data, while often deferring to others in taking on that utility. They were readily willing to accept their work in a continuum where others (for example) could then take the code and build something new or explore another facet, as the two moved on to a new subject. They were driven not by \u201cWhat can this do?\u201d but by \u201cWhat happens if we do this?\u201d and seemed to view the usefulness of a project like Wind Map with the same wonder that they viewed the initial question of \u201cWhat does the wind look like?\u201d
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Here any observer could be forgiven for a little ambivalence. The work done by Vi\u00e9gas and Wattenberg is \u2014 to those who enjoy visualizing data \u2014 smart and well crafted. The pieces in MoMA deserve that recognition. They do make one think \u2014 but mostly about what can be built upon their efforts.
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For those looking to draw the line, this may fall too much on the ‘art’ side. The pair seem decidedly more interested in the baserate questions over the relational ones. (McGrath 160) Before making things<\/em>, they certainly aren\u2019t asking where the project will be \u201cin ten, twenty, or even fifty years,\u201d and the word \u201cpersona\u201d had no place in the conversation. However, they do \u201cvalue ephemerality and even magic\u201d and seem to believe that \u201cNot everything about a project must be rationalized or demystified.\u201d As seen in those Wind Map explorations, they\u2019re not afraid to \u201cMake a useless [drippy, psychedelic] or disinterested version\u201d of a project. (Sayers)
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Looking to Miriam Posner, the pair’s work (again, as presented here) shies away from a critical engagement. They seem content to pose questions and make tools that others may then utilize \u2014 but the investigation stops at form and leaves impact to others.
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To directly contrast Vi\u00e9gas and Wattenberg with some projects that Posner admires: How does a colorful visualization of Boston compare with Jacqueline Goldsby\u2019s Mapping the Stacks<\/em> that aims \u201cto describe and arrange collections related to African American History in Chicago?\u201d How does the composition of \u201c8 Kens and Roberts\u201d in the Art of Reproduction compare with David Kim\u2019s \u2018Data-izing\u2019 the Images: Process and Prototypes<\/em>, wherein Kim used the visualization to question the photographer\u2019s categorization of his Native American subjects? Both speak to us about perceptions and \u2018lies\u2019 \u2014 one through form, the other through culture. (Posner)
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Of course not all visualization (or art) must address the bigger issues \u2014 and even Posner knows this. Sometimes it just gets the conversation going, placing the data most clearly in front of those with the itch to investigate further. (And it\u2019s another false dichotomy to decide we have to somehow judge one of these approaches over the other.) In the continuum of development, the world needs people who play in the messiness and clutter, those who ask questions, tinker around and leave something half-built on the workbench. Ultimately this research and discovery become tools of their own for those who want to build higher.<\/p>\n\n\n\n

\u2013 Michael Kelly, Info 601, Professor Chris Alen Sula<\/p>\n\n\n\n

References:
\u2022 McGrath, Joseph. (1994). \u201cMethodology matters: doing research in the behavioral and social sciences.\u201d Original paper.
\u2022 Posner, Miriam (2016). \u201cWhat\u2019s Next: The Radical, Unrealized Potential of Digital Humanities.\u201d Keystone DH Conference, University of Pennsylvania, July 22, 2015. http:\/\/miriamposner.com\/blog\/whats-next-the-radical-unrealized-potential-of-digital-humanities<\/a>.
\u2022 Sayers, Jentry (2018). \u201cBefore You Make a Thing: Some Tips for Approaching Technology and Society.\u201d https:\/\/jentery.github.io\/ts200v2\/notes.html<\/a> <\/p>\n","protected":false},"excerpt":{"rendered":"

As introduced by Miya Masaoka (Director of the Sound Art Program at Columbia\u2019s School of the Arts and coordinator of the Artists Using Data series), Fernanda Vi\u00e9gas and Martin Wattenberg are \u201cpioneers in data visualization and analytics\u201d who have \u201cshaped the field\u201d and crafted tools and interactions that have been \u201cused by millions of people.\u201d […]<\/p>\n","protected":false},"author":603,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2,3,245],"tags":[],"class_list":["post-4900","post","type-post","status-publish","format-standard","hentry","category-articles","category-event-reviews","category-sula"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/posts\/4900","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/users\/603"}],"replies":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/comments?post=4900"}],"version-history":[{"count":8,"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/posts\/4900\/revisions"}],"predecessor-version":[{"id":4912,"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/posts\/4900\/revisions\/4912"}],"wp:attachment":[{"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/media?parent=4900"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/categories?post=4900"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/foundations\/wp-json\/wp\/v2\/tags?post=4900"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}