randomosity

The Map Your Moves Chal­lenge fas­cin­ates me. New York’s Pub­lic Radio sta­tion WNYC has devised a data visu­al­isa­tion chal­lenge for their listen­ers. Curi­ous about what makes people move from and to their com­munity they polled stor­ies from their listen­ers and col­lec­ted them into a struc­tured data­set and have released it into the wild. Now this is very cool…they want to take real stor­ies and under­stand how these stor­ies inter­act and how they can learn about their own com­munity from them. Abso­lutely brilliant!

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Data visu­al­isa­tion has become very vogue in the digital human­it­ies com­munity. Although there have been a scat­ter­ing of brave prac­ti­tion­ers over the past few years, only very recently has this inter­dis­cip­lin­ary area star­ted to fea­ture prom­in­ently at DH con­fer­ences as a main­stream prac­tise worthy of consideration.

For the last few months I have been look­ing for an oppor­tun­ity (i.e. a bit of time) to delve into R and Pro­cessing, spe­cific­ally with an eye towards tak­ing some exist­ing visu­al­isa­tions I am work­ing on to a new level.

The first book of interest is R in a Nut­shell by James Adler recently pub­lished by O’Reilly.

R is a lan­guage and an envir­on­ment to sup­port data ana­lyt­ics and visu­al­isa­tion. Its approach­able, extens­ible and open source. One of the advant­ages of R over other comers is the num­ber of rather pol­ished inter­pret­ers avail­able for it and some of the great examples float­ing about that have been con­struc­ted in R. Hence my interest. I come to this interest from a digital human­it­ies back­ground and wondered whether the lan­guage could be of use for work­ing with my own data com­ing from farm diar­ies explor­ing the cycle of sea­sonal farm activities.

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Eric Fisc­her has pos­ted a new series of visu­al­isa­tions ‘Loc­als and Tour­ists’ depict­ing the loc­a­tion of pho­tos taken in urban areas around the world. In this series he attempts to dis­tin­guish between those taken by tour­ists (people who seem to be a local of a dif­fer­ent city and who took pic­tures in this city for less than a month) and those by loc­als (people who have taken pic­tures in this city dated over a range of a month or more). Intriguing.

What imme­di­ately struck me was his ingeni­ous re-use of the exist­ing data to cre­ate new inform­a­tion. By explor­ing indi­vidu­als pos­ted pic­tures over time he was able to hypo­thes­ise as to whether they were vis­it­ing or resid­ing in a par­tic­u­lar area. This allowed for a means to com­pare the gaze of the two groups.

I imme­di­ately star­ted to explore his map of Dub­lin to see if any pat­terns emerged and then to try and sug­gest explan­a­tions for them. There is a healthy and reg­u­lar mix of pho­tos by both groups in the cent­ral core, but imme­di­ately to the east is a large blue box of pho­tos taken by loc­als. It appears to sur­round the new Aviva Lans­downe Sta­dium in Balls­bridge. Addi­tion­ally on the north­side the National Botan­ical Gar­dens have a heavy con­cen­tra­tion of pho­to­graphs by locals.

The most prac­tical applic­a­tion of Loc­als versus tour­ists is to con­sider how a vis­itor might use these visu­al­isa­tions to find the hid­den city known only to its inhab­it­ants — to find those secret spots worthy of cap­ture by loc­als, but seem­ingly missed in the tour­ist guides.

This set builds on his earlier work ‘The Geot­ag­gers’ World Atlas’ look­ing at from where the pic­tures were taken, whether from car, bicyle or when walking.

Faced with find­ing a place to live in Dub­lin, I decided to quickly attempt to cre­ate a mashup of poten­tial prop­er­ties mapped through­out the city. This is, I sense, an increas­ingly com­mon sort of mashup. But when I did a quick scan, I couldn’t find any­thing that accom­plished this for the area I wanted. Yes, you could plot each place manu­ally in either the My Maps sec­tion of Google Maps or cre­ate a KML over­lay for Google Earth. Viable, but I wanted a tool that would allow the list to be dynam­ic­ally gen­er­ated and cap­ture the list cur­rent to when I was look­ing at it. I would note that many sites have their own spa­tial dis­plays, and there are a lot of mashups involving craigslist, but none for me and the Dub­lin scene. The site I was using to look for rental oppor­tun­it­ies is daft.ie. It’s got a great search engine, and it will map your selec­tions on a rental by rental basis, or will present all (unfiltered) list­ings in the area of the list­ing you have chosen. You can addi­tion­ally select a par­tic­u­lar agency and have their list­ings plot­ted on a Google Map, but this was not quite what I wanted. My object­ive was to cre­ate a cus­tom search, take the detailed res­ults, identify the loc­a­tion, geo­code it, and then pipe it into Google Maps. In concept simple — in prac­tise sub­ject to the vagar­ies of daft and the tools used.

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The folks at Many Eyes recently intro­duced their new com­par­ison cloud tool. Basic­ally, it lets you visu­al­ise two frag­ments of text dis­play­ing word fre­quency for each in the same cloud. It’s an inter­est­ing addi­tion to the more famil­iar word cloud. Using a stand­ard word cloud you get a mat­rix of words with rel­at­ive size, weight or col­our high­light­ing fre­quency in a selec­ted text. This quickly allows you to visu­ally per­ceive an author or speaker’s emphasis on a par­tic­u­lar theme or style of writ­ing or speak­ing. With Many Eyes hybrid tool, words which occur in both text are abut­ted. You can now visu­ally com­pare two texts from the same author for sim­ilar empah­sis or quickly determ­ine a dif­fer­ence between texts. In the example presen­ted at Many Eyes, they com­pare the US pres­id­en­tial State of the Union addresses from 2002 and 2003. In this example they note the less fre­quent men­tion of Afgh­anistan and the increase in men­tion of Sad­dam. Whether this allows one to con­clude a change in policy or not, it does demon­strate the use of the tool for pro­vok­ing ques­tions for fur­ther exploration.

On Sat­urday, the Ontario gov­ern­ment offi­cially announced how much fund­ing each uni­ver­sity in Ontario is to receive for main­ten­ance and renewal of facil­it­ies. I just happened to see announce­ments from a few insti­tu­tions appear sim­ul­tan­eously in my RSS reader and was struck by the rather dif­fer­ent ways in which they presen­ted this news.

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I use both GraphViz and Omni­Graffle to con­struct charts involving rela­tion­ships and pro­cesses. Over the last few days I was nood­ling my way through a schem­atic of sec­tarian asso­ci­ations in North­ern Ire­land. Try­ing to get the play­ers and organ­iz­a­tions straight was simply impossible for me without some sort of visual aid. I did a quick scan of the usual sus­pects to determ­ine whether any­one already had some­thing that would suit my needs, but only found tex­tual com­pil­a­tions. Although com­pre­hens­ive, these required more than cas­ual scans to get an imme­di­ate sense of who fits where. I put the chart before the horse this time and star­ted draw­ing on a nap­kin. I pre­sup­posed that I would need to visu­ally dis­tin­guish between polit­ical organ­iz­a­tions and para­mil­it­ary ones, and also between religio/political affil­i­ations. The col­ours green and orange sprang to mind as good visual cues ;-) I was able to access the CAIN data­base which provides a superbly author­it­at­ive com­pen­dium of organ­iz­a­tions on on ‘the Troubles’ and polit­ics in North­ern Ire­land from 1968 to the present. Chro­no­logy was also a factor and I had an addi­tional tem­poral dimen­sion to con­sider. The nap­kin was overwhelmed.

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As I read through my RSS feeds in Google Reader today, I was once again struck by the increas­ing num­ber of famil­iar head­lines. By this I don’t mean sim­ilar themes con­tinue to be explored (although true — Hil­ary is clearly a bad, bad, bad woman and John McCain throws kit­tens into wells), but rather that I had already read the art­icles that were pop­ping as new posts. My imme­di­ate thought was that Reader wasn’t catch­ing my ‘mark as read’ flags, or that I had inad­vert­ently cre­ated duplic­ate feeds. Alas, neither the case. These are the same posts…simply with dif­fer­ent author­ship claimed. Note that I am not even get­ting into the auto­mated blog post pir­acy that is designed only to attract search engine attention.

When you try to stay on top of all your news feeds with a reader and attempt to stra­tegic­ally man­age the mul­ti­tude of feeds, the col­lapsing of feeds into head­lines makes this phe­nomenon rather obvi­ous. As I con­sidered this, I real­ized that there is a cer­tain tier­ing in the blog­go­sphere. Digg, Redit and other aggreg­at­ors are at the low­est level and expli­citly point to other’s posts. At the ‘highest’ level you have blogs that cre­ate abso­lutely ori­ginal, thought­ful and unique posts. Between these there are all man­ners of vari­ants. Review sites are some­where in this milieu and they account for a sub­stan­tial amount of this over­lap. Some new gad­get is released and the sites all tend to either hear about it or get their hands on it around the same time. Yet, it is inter­est­ing to note (when you have far too many RSS feeds com­ing in) post grav­ity and proliferation.

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Yes, iSync has been with us for few years now. It should be rock solid. It’s not — yet. I recently wrote about my impres­sions of data detect­ors. Not rocket sci­ence, but a small and power­ful addi­tion to use­ful work­flow on a Mac. That they also remind me of the prom­ise that was the New­ton makes them all the more wel­come. But what can I say about iSync? One of the things that makes OSX such a com­pel­ling choice for day to day com­put­ing is the con­sist­ency of inter­face between applic­a­tions and their abil­ity to share information…not just data, but con­texts and pref­er­ences and thus recog­ni­tion and adapt­ab­il­ity to user pecu­li­ar­it­ies that anthro­po­moph­ise the laptop. The com­puter becomes some­how just some­thing a little more. A trus­ted com­pan­ion — not merely a clone of mil­lions of other identical col­lec­tions of alu­minum, sil­icon and other substances.

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Reu­ters released the API for their Cal­ais web ser­vice last week. I dabbled with it quickly last week, and then was reminded about it earlier today. I took a closer look and come away very impressed and thought­ful about the applic­a­tion of this tech­no­logy. Cal­ais accepts text and quickly extracts a vari­ety of meta data about your con­tent or as they phrase it : “auto­mat­ic­ally annot­ates your con­tent with rich semantic metadata.” Cur­rently it attempts to determ­ine ref­er­ences to:

• Entit­ies: city, com­pany, con­tin­ent, coun­try, industryTerm, MoneyAmount, Organ­iz­a­tion, Per­son, Province­Or­State, Region and URL;
• Events/Facts: acquis­i­tion, alli­ance, bank­ruptcy, busi­ness­Rela­tion, buy­backs, com­panyEarn­ing­sAn­nouce­ment, com­panyEarn­ings­Guid­ance, com­pa­ny­In­vest­ments, compantLeg­alIs­sues, jointVen­ture, Man­age­mentChange, mer­ger, per­son­Polit­ical, per­son­Polit­ic­al­Past, Per­son­Pro­fes­sion, Per­son­Pro­fes­sion­al­Past, stockSplit

This is a rather rich col­lec­tion of metadata — and they tar­get expand­ing from here.
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Inform­a­tion Aes­thet­ics, a con­sist­ently click­able and not­able blog, has Fernanda Vié­gas report­ing back from the InfoVis Con­fer­ence in Sac­re­mento this week. She has pos­ted a geat sum­mary of the key­note address by Mat­thew Eric­son. Brent Fitzger­ald blogged yes­ter­day about the panel that he, Fernanda, Mar­tin Wat­ten­berg and Hans Rosling are present­ing as well. Tak­ing a look at the con­fer­ence pro­gramme, I could not but wish I was there. Thanks for Fernanda (and hope­fully Brent) for giv­ing us an exper­i­ence as close to being there as possible.

By the way, today is the day of Fig, 7 Bru­maire, An CCXVI.

Update: Some­thing local and excit­ing: Social Net­work­ing Week at the Uni­ver­sity of Toronto. Fernanda is speak­ing on Friday.