What can Big data do for Chemistry?

If there was ever a conference with a title that reflects what we do as the Data Science Team at the Royal Society of Chemistry, the "What can Big data do for Chemistry?” meeting in London was it.

We were excited to hear about it, keen to attend and hear all of the other presentations through the day and even more delighted to present there. The day had a slant to make it even more interesting – we were asked to focus on the benefits to the end users, and to resist the temptation to dwell on the technical details of how it all works (as we technical specialists tend to do given the chance). As a Data Science team with customers who are all chemists, but some of which are internal and some external to the Royal Society of Chemistry this gave us wide variety of aims, projects and deliverables to talk about.

The result was a presentation "Advancing the chemical sciences through big data" which covered a breadth of projects including the molecule and article recommenders, term extraction from literature, trend analysis and category dashboard.

The day also revealed the big strides being made by Big data as applied to Chemistry in a range of companies (large and small) with a variety of applications (although many were pharmaceutical) and academia, in cheminformatics and machine learning related literature. Ed Griffen (MedChemica) drew the day to a close with an overview. He pointed out that making the complicated simple is desirable for internet search engines, but less so for rocket scientists piloting a space shuttle. Our customers (and decision-making managers) in Chemistry are highly skilled and time poor and our interface designs need to reflect that so that we can give them all the information that they need.

Our presentation "Advancing the chemical sciences through big data" is available for those who could not make it on the day.