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Instead of artists, the same could be done with artworks too:
Which artworks were exhibit at least once together at an event?
Which artworks were exhibit many times together?
Which artworks have never been exhibited together?
So. I noticed that the dataset does not include references to the proper artworks which were on display at the time. I was wondering: is it possible to compile a dataset relating artworks and exhibitions?
I expect this not to be a trivial exercise since data points are far more granular and it requires far more work to assert the presence of all the data points per exhibition. And the resulting dataset will probably be far larger then either yet available datasets.
Generating an adjacency matrix is an intensive task. As a dataset increases linear in size, the associated workload and required CPU resources increase at exponential rate. As such, even if the entire set was available, it would be hardly realistic to include everything. Small datasets (a few dozen artworks & exhibitions) yield optimum results. Maybe a small sample such as the curated highlights of the collection, or - better - a consistent timeframe (ie. artworks produced between 1950 to 1960) could be a viable alternative?
Thanks!
The text was updated successfully, but these errors were encountered:
Yes, it is possible to compile a dataset of the artworks on display in each exhibition; however, you are correct that it is not a trivial exercise. Compiling this dataset of artists and curators for each exhibition from 1929-1989 took a team of archivists 2.5 years. You are welcome to start compiling the data yourself using the checklists on our website at moma.org/history. Where we have one, a PDF (with OCR) of each checklist is available on each exhibition page (the URL of which is included in the dataset). These list all known works included in the exhibition.
In the meantime, if you are looking for artworks, have you seen our collection repository? There are ~128k artworks included in that dataset. It includes the date each artwork was created, so you can produce your own subsets, e.g., artworks in the collection produced between 1950 to 1960.
Hello,
This dataset relates artists and exhibitions. This allows you to answer these questions:
The answer can be visualised in a force-directed graph which is another rendition of an adjacency matrix.
Instead of artists, the same could be done with artworks too:
So. I noticed that the dataset does not include references to the proper artworks which were on display at the time. I was wondering: is it possible to compile a dataset relating artworks and exhibitions?
I expect this not to be a trivial exercise since data points are far more granular and it requires far more work to assert the presence of all the data points per exhibition. And the resulting dataset will probably be far larger then either yet available datasets.
Generating an adjacency matrix is an intensive task. As a dataset increases linear in size, the associated workload and required CPU resources increase at exponential rate. As such, even if the entire set was available, it would be hardly realistic to include everything. Small datasets (a few dozen artworks & exhibitions) yield optimum results. Maybe a small sample such as the curated highlights of the collection, or - better - a consistent timeframe (ie. artworks produced between 1950 to 1960) could be a viable alternative?
Thanks!
The text was updated successfully, but these errors were encountered: