Sep 30, 2021
Sep 2, 2021
DATASET: Carnegie Museum of Art merged with Github provenances
DATASET: Provenance information gathered from the 2015 CMOA Github merged with information from the Carnegie Museum of Art online collections website
Description: This dataset contains publicly available information originally published online by the Carnegie Museum of Art which has been formatted by OAD as a CSV file for easy download and analysis with digital tools. Many of the artworks in the list also appear on the Nazi Era Provenance Internet Portal (NEPIP). For more recent updates or additional information concerning the artworks, please contact the Carnegie Museum of Art.
The CMOA collections dataset was published on Github by the Carnegie Museum of Art under a Creative Commons CC0 1.0 licence (no copyright).
It has been enhanced with a NEW URL field in order to link to the CMOA museum website.
Date data retrieved: August 2021
AOD Version: 1.0
Format: CSV Click to DOWNLOAD CSV
Aug 31, 2021
Dataset: Problematic provenances of artworks in Dutch museums 31 AUG 2021
RetrievalDate, Source Url, Artist, Title, Year, Technique, Inventorynumber, Category, Museum, Conclusion,Explanation, Provenance, Dimensions
DOWNLOAD CSV
Aug 12, 2021
Detector Tool Tutorial: ranking by number of Red Flag and Restitution Case Names
This post, in the educational series on the experimental digital tool for analysing provenance texts, demonstrates Ranking by Red Flag Names (photo: Albright-Knox).
Work in progress. Feedback welcome.
Jul 21, 2021
Tutorial for the Looted Art Detector: Using custom indicators
Looted Art Detector: Part 2 Using custom indicators
example with : ALIU Red Flag restorers
The user can analyse provenances for any names or words that seem interesting.
The list below contains the last names of art restorers who were investigated by the OSS Art Looting Investigation Unit for their role in the art market for Nazi-looted art.
Jul 18, 2021
Looted Art Detector Tool: Swiss GLAMHACK2021
Objective: Identify high priority artworks for provenance research
Description: Online Free Digital Tool
Approach: Automatic text analysis using frequency counts
Jun 5, 2020
DATASET: Text Analysis Challenge - Detect Looted Art - GLAMhack2020
Download Provenance Texts Dataset: CSV
Text Analysis Challenge: Detect Looted Art.
The Goal: Automatically Classify and Rank 60,000+ art provenance texts by probability that further research will turn up a deliberately concealed history of looting, forced sale, theft or forgery.
The Challenge: Analyse texts quickly for Red Flags, quantify, detect patterns, classify, rank, and learn. Whatever it takes to produce a reliable list of top suspects
For this challenge several datasets will be provided.
1) DATASET: 60,000+ art provenance texts for analysis
https://www.harvardartmuseums.org/collections/object/296887 | [Pierre Matisse Gallery, New York, New York], by 1932, to M. Gutmann, 1936. Maurice Wertheim, by 1937, bequest, to Fogg Art Museum, 1951.;NOTE: Provenance derived from "Degas to Matisse: The Maurice Wertheim Collection," John O'Brian, Harry N. Abrams, New York, 1988. | 1951.76 |
https://www.harvardartmuseums.org/collections/object/229045 | Private Collector, Paris, Said to have been bought directly from artist, 1918.;Maurice Wertheim, Purchased from the Valentine Gallery, 1937, Bequest to Fogg Art Museum, 1951. | 1951.52 |
https://www.harvardartmuseums.org/collections/object/229044 | Paul Guillaume, Paris, France, 1925, 1935. By 1930, per caption of photo, Paul Guillaume dining room dated c. 1930, Georgel 2006;Maurice Wertheim, 1937, Bequest to Fogg Art Museum, 1951. | 1951.51 |
https://www.harvardartmuseums.org/collections/object/229043 | Unidentified owner, Paris, sold, [through Hôtel Drouot, Paris, June 16, 1906, no 30.]. Dr. Alfred Wolff, Munich, (1912). Sir Michael Sadler, England, (1912). [De Hauke & Co., New York], sold, to A. Conger Goodyear, New York, (1929-1937) sold, [through Wildenstein && Co., New York];to Maurice Wertheim, New York (1937-1951) bequest, to Fogg Art Museum, 1951. | 1951.49 |
2) DATASET: 1000 Red Flag Names
(example)
Bignou, Etienne | Bignou | Etienne | Etienne Bignou |
Billiet, Director | Billiet | Director | Director Billiet |
Binder, Dr. Moritz Julius | Binder | Dr. Moritz Julius | Dr. Moritz Julius Binder |
Bing Collection | Bing Collection | Bing Collection | |
Birtschansky, Zacharie | Birtschansky | Zacharie | Zacharie Birtschansky |
Bisson, E. | Bisson | E. | E. Bisson |
Blanc, Pierre | Blanc | Pierre | Pierre Blanc |
Bleye, Willi | Bleye | Willi | Willi Bleye |
Bloch, Dr. Vitale | Bloch | Dr. Vitale | Dr. Vitale Bloch |
Bloch-Bauer Collection |
Bloch-Bauer Collection
| Bloch-Bauer Collection | |
Blot | Blot | Blot | |
Bode, Dr. | Bode | Dr. | Dr. Bode |
Bodenschatz, General Karl | Bodenschatz | General Karl | General Karl Bodenschatz |
Boedecker, Alfred | Boedecker | Alfred | Alfred Boedecker |
Boehler, Julius, Jr. | Boehler | Julius | Julius Boehler |
Boehler, Julius, Sr. | Boehler | Julius | Julius Boehler |
Boehm, Dr. Franz | Boehm | Dr. Franz | Dr. Franz Boehm |
Boehmer, Bernhard | Boehmer | Bernhard | Bernhard Boehmer |
3) DATESET: Red Flag Words or Phrases
flaguncertainty | flaganonymity | flagpuncutation | flagmove | flagreliability |
likely | private collector | ? | transfer | telephone |
probably | anonymous | [ | removed | to at least |
possibly | art market | until at least | ||
maybe | unidentified | by 19 | ||
? | unknown | before 19 | ||
property of a European collector | according to | |||
private collection | ||||
property of a lady | ||||
anon. |
- IDENTIFY Red Flag Names and Words in each Text?
- COUNT Red Flag Names and Words in each Text?
- CHARACTERIZE each Text (number of words? sentiment? completeness v gaps? other features to be identified that may be useful)?
- ANALYZE for patterns, links and networks?
- CALCULATE probability that the provenance conceals a Nazi-era history that will prove problematic if investigated in detail
- RANK according to urgency for further in-depth provenance research
What might a successful result look like?
- A list of 50 provenances from the DATASET ranked most likely to conceal looted art
- A color-coded evaluation of each provenance (RED, ORANGE, GREEN) by likelihood of concealing looted art
- Instructions how to analyze the provenances with the tools, functions or code to use (for example, how to use Voyant-Tools to count all the Red Flag Names and inject the result back into the spreadsheet)
- Ideas for going further....
Triage: "assignment of degrees of urgency to wounds or illnesses to decide the order of treatment of a large number of patients or casualties."
Link to Glamhack2020 project for participants
https://hack.glam.opendata.ch/project/7
Help us to test and improve and test and improve the code!
Link to Code on Githubhttps://github.com/parisdata/GLAMhack2020
Issues to resolve:
- While the word list counts and general name extraction seem to work pretty well, reconciliation with the list of 1000 Red Flag Names still needs work. To test: A tighter tolerance combined with a more complete listing of alias might help.
- The extraction of transaction years after 1900 gives interesting though incomplete indicators. The decision to exclude dates in parentheses (as they are sometimes biographical dates and not transaction dates) needs to be reviewed and refined.
(note: The texts are from multiple sources applying multiple formats and deliberately entered exactly as is)
Jun 3, 2020
DBpedia Kategorie:Kunsthistoriker
Below are the DBpedia URIs for all the people currently known as art dealers in the German Wikipedia.
Link to the Query for the German DBpedia Kategorie:Kunsthistoriker which produced the list above.
http://de.dbpedia.org/sparql?default-graph-uri=&query=%0D%0Aselect+*+where+%7B%3Chttp%3A%2F%2Fde.dbpedia.org%2Fresource%2FKategorie%3AKunsthistoriker%3E+%3Fp+%3Fo+.%7D%0D%0A&should-sponge=grab-all&format=text%2Fhtml&timeout=0&debug=on