Showing posts with label Innovations in digital art history. Show all posts
Showing posts with label Innovations in digital art history. Show all posts

Apr 30, 2020

Tracing Jewish Art Collectors and other #LostArtPeople by Place of Death

In our previous post, we introduced the idea of using Wikidata Queries to Trace Jewish art collectors and their collections.


In this post, we begin to look at how we might identify these Jewish individuals, many of whom have been not only forgotten but deliberately written out of history. 


What information or feature might help us to identify them?
What do we know about them?


  • They died after 1932 
  • They were connected to the arts in some way: as collectors, dealers, curators, historians, curators, museum directors, gallery owners, possibly as artists
  • Their names might have appeared in exhibitions or catalogs as owners or lenders or donors or experts, or in books or articles as authors, in the provenance texts of collections, for example.



The above criteria is very large and not specific to Jewish collectors in the Nazi era.  How can we further narrow the criteria? One element that distinguishes the fates of Jewish individuals from others is how and where they died, and whether or not they were interned, spoliated or became refugees. 

What kind of markers can we look for in the data?


  • Place of death
  • Year of death
  • Cause of death
  • Place of internment
  • Significant events like aryanization or arrest or deportation


All of the above correspond to "Properties" that are defined in Wikidata. Not all these properties have been updated for every Wikidata item. But they could be. 


A Wikidata Query can easily show us all the people who are known (in Wikidata) to have died or been interned in a Nazi camp or ghetto.


How to do this?

There were so many Nazi camps in so many countries (see below) that we look for a way to take each one into account without necessarily naming each one in a query.

One way is to use Wikidata's "instance of" (P31).

We can tell the query to list people who died in a place that is defined as any of the following things:


  • Nazi concentration camp (Q328468)
  • concentration camp (Q152081)
  • extermination camp (Q153813)
  • ghetto in Nazi-occupied Europe (Q2583015)


We might still miss a few of the camps (due to the crowdsourcing nature of Wikidata, not every item is coded in exactly the same way,) but this should be a good start.

There are several ways to do OR type queries in Wikidata.

We will use the very straight forward UNION. (Please do not hesitate to suggest better ways).

WHERE {
{ ?placedied wdt:P31 wd:Q328468.} UNION { ?placedied wdt:P31 wd:Q152081. } UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placediedwdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q2583015.}


To make the Wikidata query run faster and avoid time outs, we will first check that the place of death has been entered by someone into Wikidata.


?item wdt:P20 ?placedied.

Then, instead of specifying, as we did in the previous query, that we want to list the people who died in the specific Nazi concentration camp of Auschwitz-Birkenau


  ?item wdt:P20 wd:Q7341.  

we want to request people who died in any place coded as an instance of Q328468, Q152081, Q153813 or Q2583015


{ ?placedied wdt:P31 wd:Q328468.} UNION { ?placedied wdt:P31 wd:Q152081. } UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q2583015.}

This should include all the Nazi camps and ghettos listed at the bottom of this post

_______


SELECT DISTINCT ?item ?itemLabel ?pic ?datedied ?placediedLabel ?placedied ?child ?childLabel ?ownedby ?ownedbyLabel ?depicts ?depictsLabel ?depictedby ?depictedbyLabel ?countryLabel ?ownerof ?ownerofLabel ?spouse ?employer ?employerLabel ?spouseLabel ?mother ?motherLabel ?father ?fatherLabel ?sibling ?siblingLabel ?investby ?investbyLabel ?sigperson ?sigpersonLabel ?party ?partyLabel ?partner ?partnerLabel WHERE {
{ ?item wdt:P106 wd:Q1792450.} UNION { ?item wdt:P31 wd:Q1007870. } UNION { ?item wdt:P106 wd:Q173950.} UNION { ?item wdt:P921 wd:Q328376.} UNION { ?item wdt:P106 wd:Q10732476.} UNION { ?item wdt:P106 wd:Q446966.} UNION { ?item wdt:P106 wd:Q22132694.} UNION { ?item wdt:P106 wd:Q674426.}


SERVICE wikibase:label { bd:serviceParam wikibase:language "en" }
?item wdt:P20 ?placedied.  
{ ?placedied wdt:P31 wd:Q328468.} UNION { ?placedied wdt:P31 wd:Q152081. } UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q2583015.}
OPTIONAL  { ?item wdt:P18 ?pic. }
OPTIONAL { ?item wdt:P127 ?ownedby. }
OPTIONAL { ?item wdt:P570 ?datedied. }
OPTIONAL { ?item wdt:P20 ?placedied. }
OPTIONAL { ?item wdt:P180 ?depicts. }
OPTIONAL { ?item wdt:P921 ?plunder. }
OPTIONAL { ?item wdt:P1830 ?ownerof. }
OPTIONAL { ?item wdt:P108 ?employer. }
OPTIONAL { ?item wdt:P569 ?birth. }
OPTIONAL { ?item wdt:P40 ?child. }
OPTIONAL { ?item wdt:P214 ?VIAF_ID. }
OPTIONAL { ?item wdt:P19 ?place_birth. }
OPTIONAL { ?item wdt:P244 ?Library_of_Congress_authority_ID. }
OPTIONAL { ?item wdt:P227 ?GND_ID. }
OPTIONAL { ?item wdt:P245 ?ULAN_ID. }
OPTIONAL { ?item wdt:P26 ?spouse. }
OPTIONAL { ?item wdt:P27 ?country. }
OPTIONAL { ?item wdt:P3342 ?sigperson. }
OPTIONAL { ?item wdt:P102 ?party. }
OPTIONAL { ?item wdt:P1327 ?partner. }
OPTIONAL { ?item wdt:P1840 ?investby. }
OPTIONAL { ?item wdt:P25 ?mother. }
OPTIONAL { ?item wdt:P22 ?father. }
OPTIONAL { ?item wdt:P3373 ?sibling. }
OPTIONAL { ?item wdt:P1299 ?depictedby. }
OPTIONAL { ?item wdt:P39 ?position. }

FILTER (YEAR(?datedied) >= 1933 )
}
LIMIT 20000

_______

note: careful: the filter should read datedied "greater than or equal to" 1933. Sometimes the greater than symbol gets garbled on this blog

(Notice the word OPTIONAL? We are telling Wikidata to get the information if it is available but not to worry about it if it is not. Since we want to understand who these individuals were, the context of their lives and their relations with others, we have added much optional information to the query. This is not strictly speaking necessary, but possibly useful for future network analysis)
The Wikidata Sparql Query can present the results in many different ways.

As a table. 


As a graph. 












With photos







We can zoom in close to view certain specific elements that are hard to see when looking at lots of data.





We also get an idea of where data might be missing.














Try the query yourself.  It shows only those art people who died in a Nazi camp or ghetto. What one immediately notices is how many are missing. 

How to see what is present and what is absent will be the subject of our next post.

Link to Query
https://query.wikidata.org/#%0A%0ASELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%20%3Fpic%20%3Fdatedied%20%3FplacediedLabel%20%3Fplacedied%20%3Fchild%20%3FchildLabel%20%3Fownedby%20%3FownedbyLabel%20%3Fdepicts%20%3FdepictsLabel%20%3Fdepictedby%20%3FdepictedbyLabel%20%3FcountryLabel%20%3Fownerof%20%3FownerofLabel%20%3Fspouse%20%3Femployer%20%3FemployerLabel%20%3FspouseLabel%20%3Fmother%20%3FmotherLabel%20%3Ffather%20%3FfatherLabel%20%3Fsibling%20%3FsiblingLabel%20%3Finvestby%20%3FinvestbyLabel%20%3Fsigperson%20%3FsigpersonLabel%20%3Fparty%20%3FpartyLabel%20%3Fpartner%20%3FpartnerLabel%20WHERE%20%7B%0A%7B%20%3Fitem%20wdt%3AP106%20wd%3AQ1792450.%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP31%20wd%3AQ1007870.%20%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP106%20wd%3AQ173950.%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP921%20wd%3AQ328376.%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP106%20wd%3AQ10732476.%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP106%20wd%3AQ446966.%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP106%20wd%3AQ22132694.%7D%20UNION%20%7B%20%3Fitem%20wdt%3AP106%20wd%3AQ674426.%7D%0A%0A%0ASERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22%20%7D%0A%3Fitem%20wdt%3AP20%20%3Fplacedied.%20%20%0A%7B%20%3Fplacedied%20wdt%3AP31%20wd%3AQ328468.%7D%20UNION%20%7B%20%3Fplacedied%20wdt%3AP31%20wd%3AQ152081.%20%7D%20UNION%20%7B%20%3Fplacedied%20wdt%3AP31%20wd%3AQ153813.%7D%20UNION%20%7B%20%3Fplacedied%20wdt%3AP31%20wd%3AQ153813.%7D%20UNION%20%7B%20%3Fplacedied%20wdt%3AP31%20wd%3AQ2583015.%7D%0AOPTIONAL%20%20%7B%20%3Fitem%20wdt%3AP18%20%3Fpic.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP127%20%3Fownedby.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP570%20%3Fdatedied.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP20%20%3Fplacedied.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP180%20%3Fdepicts.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP921%20%3Fplunder.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP1830%20%3Fownerof.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP108%20%3Femployer.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP569%20%3Fbirth.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP40%20%3Fchild.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP214%20%3FVIAF_ID.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP19%20%3Fplace_birth.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP244%20%3FLibrary_of_Congress_authority_ID.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP227%20%3FGND_ID.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP245%20%3FULAN_ID.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP26%20%3Fspouse.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP27%20%3Fcountry.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP3342%20%3Fsigperson.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP102%20%3Fparty.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP1327%20%3Fpartner.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP1840%20%3Finvestby.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP25%20%3Fmother.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP22%20%3Ffather.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP3373%20%3Fsibling.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP1299%20%3Fdepictedby.%20%7D%0AOPTIONAL%20%7B%20%3Fitem%20wdt%3AP39%20%3Fposition.%20%7D%0A%23%20FILTER%20%28YEAR%28%3Fbirth%29%20%3D%201860%20%26amp%3B%26amp%3B%20YEAR%28%3Fbirth%29%20%26lt%3B%3D%201990%29%0AFILTER%20%28YEAR%28%3Fdatedied%29%20%3E%3D%201933%20%29%0A%7D%0ALIMIT%2020000




Camps and ghettos listed in the Wikidata Query


SELECT ?placedied ?placediedLabel
WHERE
{
  { ?placedied wdt:P31 wd:Q328468.} UNION { ?placedied wdt:P31 wd:Q152081. } UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q153813.} UNION { ?placedied wdt:P31 wd:Q2583015.}
  SERVICE wikibase:label { bd:serviceParam wikibase:language "[AUTO_LANGUAGE],en". }
}



(Short link to query and result - Try it!)





Sep 24, 2018

Disambiguating the Balls

Is it possible to mix URIs from many sources and obtain something intelligible?
https://tb.semlab.io/share/BALL

BALL, an art dealing family operating in Dresden, Berlin, Paris, New York 

see: Firma Hermann Ball, Firma Ball, Graupe und Ball, A & R Ball, Hermann Ball, Alexander Ball, Richard Ball  

Hermann (Hirsch) Ball (1857 - 1924) and his sons Richard (born 1892) and Alexander operated an art dealership in Dresden, specializing in old masters, furniture and porcelain. The Firma Ball was registered in the Dresden Business Register in 1903 by Hermann Ball. His sons Richard and Alexander Ball joined the business in 1919.*

Alexander Ball, as noted in a previous post, was flagged by the OSS Art Looting Investigation Unit in 1946 for having working closely with notorious art looter Karl Haberstock during the Nazi era.

Yet it is difficult to find out much about him.

Born in Germany, Alexander Ball (also known as Alexandre Ball, Alex Ball or A. Ball) worked in France, before escaping to the USA. In NY, he set up a dealership with his brother Richard Ball, known as  A. and R. Ball, (A&R Ball, A. & R. Ball, etc).