The response to our first two data science challenges has been nothing short of inspiring. At the time of writing this article we’ve had more than 1500 entries, and the competition for our top leaderboard places is hotting up. If we were to run further challenges, what happens next?
One challenge, Safe Passage, centres around detecting and classifying vehicles in aerial imagery, while the second, Growing Instability, is all about classifying crisis reports contained in huge reams of newspaper data.
It’s easy to see how these might be applied to real defence and security scenarios. The ability to triage enormous amounts of incoming data will always provide a welcome edge.
Future challenges will all need to be built around perfecting new methodologies to provide that same kind of strategic advantage. To imagine what these advantages might look like, we thought we’d throw the floor open to our growing community.
Pitch in with ideas
The future for the platform is still under review but we are hopeful the benefits witnessed will warrant continuation in some form. How and with what technical focus is still to be agreed, but we see you, the Data Science community, as an important partner in shaping any future challenges.
As a data scientist, you know how different methodologies can be applied to performing different functions in the real world. How might your preferred data science discipline be applied to the UK’s defence and security?
By joining our growing data science community and pitching in ideas for future challenges, you’d be contributing to an ongoing, important mission to help keep people safe. Our forums are already buzzing with inquisitive people like yourself tugging at the various aspects that make up each challenge, and that’s exactly the kind of participation we want to encourage.
This community thrives on innovation. We’ve created a space where everyone, not just challenge participants, is encouraged to contribute whatever ideas they can. That might be the basis for an entire challenge, or just the smallest thread of an idea which the community can build on.
The only barriers are your data science expertise and your imagination. Of course, there’s a lot that goes into creating our challenges and getting them ready for entrants, but at this early ideas stage (arguably the most exciting part) we want you to let your creativity run wild and let us worry about the practicalities.
How the challenges go from this initial brainstorming to final completion will depend on a bunch of different factors. Our project team will review the most feasible ideas, and the best options will then be subject to research, determining whether we can get the right representative data to support the challenge.
After that, it’s all to play for. Do you want to help shape any future challenges? Join our community and start pitching in your ideas today.