Introducing Scout: Enhancing the Discoverability of NYC Open Datasets

A member of Data Clinic presents to an audience of people at NYC Open Data Week.
Scout helps surface lesser-known datasets on the NYC open data portal.

Data Clinic hosted a large gathering of open data aficionados to present our newest open source tool, scout. The presentation, which was held as part of NYC Open Data Week, showcased scouts unique ability to augment the NYC open data portal and enhance the discoverability of datasets on a stand-alone web app that enhances the discovery of datasets.

Kelly Jin, Chief Analytics Officer for the City of New York, and Chris Whong, Adjunct Assistant Professor of Urban Planning at the NYU Wagner Graduate School of Public Service, joined the Data Clinic team to describe  the motivation behind the project, the design challenges the team had overcome, and the broader use cases for the tool.

Two Sigma Data Clinic Scout Launch Screenshot

The presentation ended with a live demo to showcase scout’s functionality, which includes the ability to surface datasets that are thematically similar. Users can also join these datasets via common entries in specific columns and curate persistent and shareable collections of datasets.

We are actively collecting feedback on the beta version of scout. We are specifically interested in developing better ways to recommend datasets, and to identify and build new features with input from the community. Give it a test run, contribute on GitHub, and let us know what you think.

To learn more, watch a video of the event here.

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