I first heard about the crowdmapping platform Ushahidi a few years ago; it’s an open-source app/platform that can collect/collate geotagged data in real-time from mobile observers, or delayed reports over the web. The data can then be mapped, viewed on a timeline, and analyzed. One significant obstacle to using the platform was the need to install it on a webserver with PHP/MySQL support – easy for some, but a challenge for others. I’m a bit late (about a year), but I just found out that Ushahidi has created a free service called Crowdmap that hosts the platform for you, lowering the technical barrier significantly. Examples of Crowdmaps include one for the English papal visit, and a Crowdmap for the Australian floods earlier this year (screenshots below).
The map above shows all Crowdmap reports in all categories, plotted by location; clicking on a red dot brings up the option to show more detailed reports for that region.
You can set up report categories, and clicking on a category will show reports for only that category. You can also filter by time and other parameters.
Timelines can be displayed showing the number of reports in any/all categories, like the plot of electricity disruptions above.
Data can be submitted a number of ways:
- SMS text messages (geotagged)
- Twitter (geotagged)
- RSS feeds
- Web forms
- Mobile apps for both iOS and Android
As the Crowdmap site points out, while originally designed to provide real-time data tracking, there’s nothing to stop you from using this as a generic crowdmapping app.
There are still reasons why you might prefer to use the Ushahidi platform directly on your own webserver. Doing so gives you more control over the data, and how it will be used. Ushahidi is developing a complementary open-source platform called Swift River that can filter, verify and analyze real-time data to make more sense of it, and I don’t believe that’s currently available on Crowdmap (though Crowdmap does have some basic analytical tools). I suspect that at least some aspects of Swift River will be integrated into Crowdmap in the future. Even without these advanced Swift River data tools, though, the ease of Crowdmap’s implementation makes it a good choice for many.