CRED was launched in 2013 to facilitate community monitoring of the Red River and its tributaries during the spring runoff. CRED is a mobile crowdsourcing app - anyone in the Red River basin (or beyond) can use CRED to submit timely reports and photographs from their mobile devices for review by partners at local and federal agencies.
To promote two-way communication between data contributors and data users, CRED includes a number of "social" capabilities such as the ability to "star" and comment on reports. Agency staff also can log in and define targeted regions where more observations are needed.
The CRED report model uses the flexible EAV structure provided by the annotate pattern to make it possible to define multiple data collection campaigns with different targeted data attributes (e.g. the "Snow Pack" campaign includes an option to report depth, while the "Flooding / Conditions" campaign includes an option to report flooding severity). CRED uses uses the default wq.db REST API, with data stored in a PostgreSQL database.
Python Social Auth is used to provide Google, Twitter, and Facebook authentication options. Reports are republished to Twitter via the Twython library. If the user signed in via Twitter, the tweet is published under their account; otherwise, it is published via the @CREDreports account.
© 2013-2019 by S. Andrew Sheppard