Collection Data for Cooper Hewitt, Smithsonian Design Museum
Cooper Hewitt, Smithsonian Design Museum is committed to making its collection data available for public access. To date we have made public approximately 75% of the documented collection available online. Whilst we have a web interface for searching the collection, we are now also making the dataset available for free public download. By being able to see 'everything' at once, new connections and understandings may be able to be made. For more information please see our website.
Please follow the instructions on our wiki
Are there any restrictions?
In order to reduce any uncertainty about the 'legitimate uses' of this dataset, Cooper Hewitt has licensed this release under a Creative Commons Zero (CC0) license. This license is the most permissive available and allows for all types of reuse. It is explained in full in the accompanying license file.
Following the lead of Europeana, we have also released some guidelines for use which suggest that users:
Please be aware that images are not included. While we have provided a way to reference the images connected to the records, these images themselves are not part of the dataset being released and are not covered by the same license.
Please see our wiki for detailed usage guidelines.
This departments, exhibitions, objects, people, periods, roles and types folders contain Cooper Hewitt collection data exported as individual JSON files.
File names and parent directory structures are generated using the unique ID of the object itself. For example the full path for iRobot's Roomba vacuum cleaner (ID #18704235) is: objects/187/042/35/18704235.json
Paths are generated by chopping numeric identifiers in to groups of three (or less) starting front to back. A reference implementation can be found in the utils.py library.
It should be noted that the performance of Git (and GitHub) when dealing with very large repositories is still less than ideal. It appears to be a problem inherent to Git and its indexing processes.
Which is to say: Everything still works but it can be slow. In practice this has the side-effect of making some features of GitHub, like pull requests, nearly impossible because the web application is configured to time out before indexing (of a very large repository) has completed.
There is a good thread about the problem and some potential solutions over here:
If you notice a factual error in the data, please let us know using this form. Be sure to include the item's ID or accession number in your description of the error. As this repository represents a downstream export of our collections database, we cannot accept pull requests regarding factual errors.
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