This is a public repository of datasets made available for the Arts Datathon happening on April 22, 2017 at The Reef, the downtown Los Angeles campus of Claremont Graduate University and Sotheby's Institute of Art - Los Angeles. The Arts Datathon is jointly led by the City of Los Angeles Department of Cultural Affairs and the Los Angeles County Arts Commission.
The Arts Datathon will bring together local arts agencies with artists, arts administrators, educators, students, community advocates and researchers as well as other professionals in culture, museums and urban planning. Together we will explore the data to gain a greater understanding of the present and future of arts and culture programming, infrastructure, and policy across the Los Angeles region. We will also know a whole lot more about how we can put the data to work.
For more information, go to http://artsdatathon.org
When uploading files to the GitHub repository, please use the following file naming convention: [Author/Owner-SubjectMatter-YYMMDDpulled].[file format]
For example, if the uploaded dataset is Los Angeles County Arts Commission's civic art collections data, the uploaded file should be named: LACAC-CivicArtCollctn-170410.csv
Feel free to use conventional abbreviations so long as the abbreviation is explained in the Additional Documentation section below.
Artifacts going into and coming out of the datathon are licensed under a CC BY-NC 4.0 International license.
More information on the license available in the GitHub repo and the Creative Commons site: https://creativecommons.org/licenses/by-nc/4.0/legalcode
Do not mislead others or misrepresent the datasets or their sources. You must not use City of Los Angeles Department of Cultural Affairs or Los Angeles County Arts Commission logos or otherwise claim or imply that either agencies endorses you or your use of the datasets.
All datasets should be saved as a CSV file. Additionally, if other file formats are available, these should be uploaded to the GitHub repository, but is not required.
Upload the dataset in the folder that best describes the topic of the dataset. If you have questions, contact Yvonne Lee at [email protected]
In order to build trustworthiness and context for datasets, create a file containing additional documentation with each dataset uploaded to the GitHub repository. This may be narrative text that provides information about the conditions under which the dataset was created including tools used (software and hardware), periodicity, geography, topics.
Documentation on the author of the dataset (including organization if appropriate) is required. If available, please include data dictionaries and log books.