The Defence Science and Technology Laboratory (DSTL) has launched a major competition aimed at developing new ways of analysing unstructured data.
The Data Science Challenge is part of the wider programme laid out in the Defence Innovation Initiative, which the Ministry of Defence (MoD) says will help build an open and innovative ecosystem bringing together academia, industry and individuals to "develop new approaches to complex problems".
The Data Science Challenge consists of two separate challenges. The first, dubbed "safe passage", requires participants to detect and classify vehicles, such as buses, cars and motorbikes from a set of aerial images. The second, "growing instability", asks those involved in the competition to analyse news reports to predict topic tags for classifying unseen reports so they can be used "to improve awareness and understanding" of potential crisis situations.
Each challenge has a total prize fund of 40,000, which will be divided into a 20,000 first place prize, 12,000 second place prize and 8,000 third place prize.
James Srinivasan, a principal data scientist at DSTL, said: "Around the world, governments are using the power of data to meet many of the huge challenges that they are facing. By analysing complex, evolving information, data science can provide invaluable insight that informs how we can best respond to event.
"There is real talent out there and we want to encourage the curious to experiment and learn. We are determined to push the boundaries of what can be done, and to keep striving to always be better. This is why we are launching the Data Science Challenge today."
Registration opens today and participants have until 17 May to develop and submit their solutions. For more information and to register visit www.datasciencechallenge.org.
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