Please follow the link to the site to search, browse and view San Francisco data.
How to Submit Datasets to DataSF
If you are new to this site, the first step is to register. We suggest creating a username that indicates your department and division (e.g. DPW_BSM ). When considering what to share with the public, ensure that your data is raw, structured, machine-readable data. Some examples are: CSV file, Access Database, Excel spreadsheet. Data that is unstructured such as PDF files or websites that allow people to query the data but not have access to the underlying data are not appropriate for DataSF. The best datasets have high-value information which is information that can be used to increase agency accountability and responsiveness; improve public knowledge of the agency and its operations; further the core mission of the agency; create economic opportunity; or respond to need and demand as identified through public consultation.
2. Submit a Dataset
Before you submit a dataset it is your responsibility to contact your city attorney and verify that the dataset is approved for public consumption
To submit your dataset, you must be logged in to contribute to the DataSF website; if you are not, you will prompted to log in. When you submit a dataset, you will be asked for the dataset location in the first screen and several other pieces of information in the second screen. Once submitted, your dataset will be held for review to ensure accuracy and completeness. Your submisson can be edited at any time. If your department does not have a location to store datasets, you should coordinate with the administrators of DataSF.org.
3. Notify DataSF Admins
After submitting your dataset, contact the administrators of DataSF.org. Your dataset will be reviewed for accuracy and completeness and then published.
If you have any questions, you can contact the administrators of DataSF.org.
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(1) improve access to data
(2) help our community create innovative apps
(3) understand what datasets you'd like to see
(4) get feedback on the quality of our datasets.