San Diego’s Data & Analytics program relies on the worldwide community of open source developers. Below are projects that have been instrumental in the success of our program.
JKAN is a data portal project built on top of Jekyll. Multiple parts of this data portal are based on JKAN, a brainchiled of Tim Wisniewski, the CDO of Philadelphia. Thank you, Tim, for your contribution!
Serverless provides a backend for the dataset previews on this portal.
Polymer components display the dataset previews on this portal.
Most government publications are available in PDF, but Gitbook instead publishes the content as books in the browser that readers can navigate just like a web page. Gitbook is the publishing medium for the annual reports to council required by the City’s Open Data Policy.
Jupyter Notebooks allow the creation and sharing of documents that pull in data, perform equations and visualize results along with explanatory text. Jupyter Notebooks facilitated the prototyping of Airflow jobs. It is also used for data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more.
The R programming language and RStudio application can also be used for data cleaning, analysis, and transformation.
Airflow is a workflow automation solution that automatically updates the data on this portal. This platform is otherwise a key component of the Data & Analytics program because data delivered on a regular schedule improves City processes and makes data-driven decisions possible.
Docker maintains parity between local and production environments and is how we deploy applications.
An explorer for street paving and street conditions in San Diego
Docker orchestration for running Airflow on docker containers. Originally based on puckel’s version, our version accommodates our unique technology requirements.
Check out the City’s Github for all of our smaller projects, and follow the team to stay updated on our work!