At Bloomberg, we believe that equal access to information is a social good; it is a principle fundamentally linked to good business.
Our founder, Mike Bloomberg, applied this principle to democratize the opaque capital markets, using cutting edge data and technology to open access to information – such as bond prices – that not only propels financial markets, but enables capital investments to support growing cities, towns and school districts.
We still firmly apply this principle today, increasingly so within my field of software development where we have looked at the platforms and technology we have built over the years and open sourced a number of significant projects that are useful to the community.
Across the business world, data science has had an immense impact in allowing businesses to provide better service, more cheaply, and to more customers. These advances have come from decreasing costs of computation, the increasing access to data, and advanced statistical methods that can be brought to bear on problems.
But while the corporate sector has effectively engaged the academic community in this approach to problem-solving, the public and non-profit sectors have seen comparatively less application of data science methods. This is something we are committed to helping to change.
In 2014, over 900 scientists, thought leaders, and policy makers convened at our global headquarters in New York, for KDD at Bloomberg, which was a pre-conference held in partnership with SIGKDD. There, participants from industry and academia shared insights and progress on applying modern machine learning and data science methods to problems in the public and non-profit sector.
On September 28 this year, we will reconvene to further these aims at ‘Data For Good Exchange’ – a Bloomberg-hosted workshop in connection with Strata + Hadoop World New York. Speaking at today’s Strata + Hadoop World conference in London, I was delighted to announce the call for papers responding to our objective of sharing success stories, challenges, and visions for the future applications of data science to address problems around social policy. The call for papers and related details can be found at Bloomberglabs.com/data-science.
We hope to receive submissions on topics as diverse as empowering local governments with data science, engaging citizens in collecting the necessary data to transform public health, and using data science to mitigate or remediate environmental problems.
We welcome submissions that highlight successes, present relevant challenges or problems, describe especially relevant data sets or lay out a vision for the future direction of this growing and exciting field.
Above all, we hope to see examples of a shared belief in the power of data and information – and the enhanced transparency it brings – to create social impact as well as business impact.
— Christine Flounders is Head of London R&D at Bloomberg L.P.