Making Apps

Posted on 02/20/2012 by


Over the past few months, we’ve been exploring the world of data-driven applications, from Facebook to mobile services. Following on from our Christmas hacking, we’ve also been working with several developers to help them turn their ideas into applications. Helping developers do great things with data is part of our vision, and we’ve offered financial backing, technical support and the use of Kasabi’s features. Here, I’ll introduce you to three projects below, and we’ll be following them as their applications develop.

Exploring Botanical Gardens from a Smart Phone
StrongSteam: Ian Ozsvald and Kyran Dale

The StrongSteam team are working on an iPhone app that opens up new levels of exploration for visitors to botanical gardens. The app will let people access tons of information about the plants they find by taking a photo of the label. The app uses advanced character recognition to read the Latin name from descriptive labels, and pulls in data from a variety of sources to tell the user far more about the plant than could be available on signs.

They’re using the StrongSteam datamining API for matching plant labels and IDs, then using datasets in Kasabi (GeoSpecies, DBPedia and BBC Wildlife for example) to extract detailed information about plant species. The user will then be given facts, figures and other pieces of information, letting them learn far more about the plants they find interesting.

My Society: Paul Lenz

Through the popular app, FixMyStreet, My Society has been giving people the ability to report damaged infrastructure to their local authorities for a few years. Using smartphones, people have been highlighting things like potholes and broken streetlights across the UK since 2008. The app is now due a complete overhaul, upgrading to a more sophisticated, HTML5-based service. The new FixMyStreet will be a more powerful, responsively designed mobile-web version of the older native apps, and will use Kasabi to store a continuously-updated list of new problem reports. The new dataset will include information about councils, kinds of damage, timestamp and status of repairs along with detailed lat/long locations.

John Peel Time Machine
Storm: Dave Kelly, Mike Ellis, and Paul Leader

Developers from Storm are putting together a time machine travelling back through some of the greatest musical events of the 20th century under the watchful eyes of the legendary BBC radio DJ, the late John Peel. Building on the dataset of John Peel Sessions, the web app will guide users’ journeys on their search for artists who appeared on the live recordings of John Peel’s long-running show.

The Time Machine will work on a timeline, giving a high-level view of the Peel sessions by year, and highlight some of the relationships amongst musical artists. Where it can, it will link to recordings of the live sessions, and provide biographical information about the artists. The time machine will also provide information about the albums and tracks featured, and point users towards playlists of sessions, which they can purchase or listen to via the likes of iTunes or Spotify.

I shall be speaking with the teams of developers on these projects in the next couple weeks, and will share their progress and experiences here on the blog. I’m sure they’ll be happy to answer some questions you might have, and our own Kasabi team is more than happy to hear your ideas about data-driven apps too. Drop me a line or leave a comment below.

Datasets Mentioned

Posted in: Datasets, Funding, Ideas