SPRU - Science Policy Research Unit

Data Science for Innovation Workshop

Dr Daniele Rotolo and Dr Frederique Bone organised a workshop in June, on Data Science for Innovation, which brought together data practitioners, data providers, and academics to explore the use of new data sources, discuss analytical technologies and techniques (such as Machine Learning or text mining) and novel ways to visualise data. The workshop also provided the opportunity to connect academics with data practitioners and thus build a community around data science for innovation.

Data science workshop photograph 1Data are an important element of any decision-making process and scientific study, but it is not enough just to have data, it is equally important to know where they come from, how to analyse them, and how to interpret the results of the analyses.  And then, getting your point across is another issue - as how you visualise data can lead to important insights and enable clearer, more informed decision-making.

The workshop was divided into three sections, with a series of presentations around each topic:

  • Data, Data, Data …
  • Text mining for Science, Technology and Innovation
  • Mapping research

Contributions to these sessions were provided by a range of organisations: Web of Science (Clarivate Analytics), Digital Science, Researchfish, OECD, MIoIR (University of Manchester), NESTA, WZB Berlin Social Science Center, Amsterdam University, UNU-MERIT (Maastricht University), DELab (University of Warsaw), Aalborg University, and SPRU (University of Sussex). For full details, please see the agenda. Presentations were followed by plenty of discussion, with a final dialogue on transparency and bias in measurement and data selection and plans for further collaborations and workshops.

For full details, please see the agenda for the workshop.