Filomena

Time to won­der and find magic

A glimpse behind the scenes of DAHSS 2020

Being a first time par­tic­i­pant with basi­cal­ly no expe­ri­ence in Data Sci­ence and Dig­i­tal Art His­to­ry, this week was intense, excit­ing, frus­trat­ing and most of all real­ly instructive.

This is how I start­ed the week:

Well, and here you see my pre­sen­ta­tion and as you might rec­og­nize, it is most­ly text… dig­i­tal text but still text, this is what art his­to­ri­ans know to do, right? I did cre­ate some things, using data and cloud com­put­ing. But I bare­ly scratched the sur­face of all there is to know and to learn about this top­ic. But what did Har­ald repeat­ed­ly say? “We are not here to become com­put­er spe­cial­ists or pro­gram­mers. We remain art his­to­ri­ans with some knowl­edge in com­put­er sci­ences and with that we will be able to com­mu­ni­cate with pro­gram­mers and explain to them what we want to see as a result.” Well, I’ll take you up on that, Harald!

So what did I learn this week? I learned about the mag­ic of cloud com­put­ing and how to use pub­lic data from the web and how to process it to anoth­er plat­form using Inte­gro­mat. I know how to build a telegram bot now and how to have reg­u­lar updates from an RSS-feed sent do my mail inbox or my Telegram account. I can also mag­i­cal­ly get pic­tures from muse­um APIs and have them show up on Google Docs or Spread­sheets. And I learned about how to present data in inter­ac­tive charts on Datawrap­per. But how does that fur­ther art his­to­ry and is that real­ly the dig­i­tal art his­to­ry that we need and we are look­ing for? What is dig­i­tal art his­to­ry right now and what would I like it to be?

I think, these tools might be use­ful for sci­ences and art his­to­ry. But so far there is only lim­it­ed machine read­able and search­able data avail­able, to be able to con­struct use­ful appli­ca­tions from it. So far I have most­ly seen, that images from muse­um data­bas­es were used to be played around with on muse­um web­pages. That does­n’t seem too appeal­ing in the long run, at least to me. There­fore for art his­to­ri­ans, or at least for myself, I see the main respon­si­bil­i­ty in cre­at­ing data through tra­di­tion­al research and pro­vid­ing this data in a way that it is machine read­able, search­able and in the end might be able to be com­bined with oth­er exist­ing data (with­in the lim­its of pri­va­cy and copy right of course).

My research focus is prove­nance research. This field would­n’t have grown this much in the past decades with­out the pos­si­bil­i­ties of dig­i­tal­iza­tion, the inter­net and the devel­op­ing dig­i­tal human­i­ties. Dig­i­tal­iza­tion of archival mate­r­i­al and cat­a­logues, for exam­ple, has made research a lot eas­i­er. But there is still a long way to go. Dur­ing the past days I tried to extract prove­nance data from the avail­able APIs that were known to us, unfor­tu­nate­ly with­out suc­cess. One of the main prob­lems in mak­ing prove­nance data search­able is that there is no com­mon way to write prove­nances. With­out a com­mon stan­dard it is not pos­si­ble to use the seman­tic web and linked data for prop­er sci­en­tif­ic research. But the prob­lem is known and there are researchers (art his­to­ri­ans and data sci­en­tists) that are already on the track, try­ing to solve these problems.

So there is still a lot to do, but visions exist and hope­ful­ly tech­nol­o­gy and data will be devel­oped to enhance our research and lead to a Dig­i­tal Art His­to­ry that enhances and advances art his­tor­i­cal research. 

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Below you find my first exper­i­ments with Datawrap­per. I used data sam­ples from my mas­ters the­sis where I researched a pri­vate col­lec­tion of mod­ern art between 1918 and 1932. 

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