Data Science at Elsevier: A Brief Overview
Over the last twenty-five years, Elsevier has transformed itself from a traditional print publisher into an information solutions provider. In the latest phase of this transformation, Elsevier is accelerating its efforts to combine the scientific and medical literature with a wide range of additional sources of data to create new ways of delivering value to customers in the research and healthcare markets we serve. The data science community at Elsevier, spread across our various businesses and embedded within our product development teams, is a key part of this effort. We will describe the organization and focus of our data science teams, the infrastructural and process-oriented challenges they face, and the principles they are applying to the creation of new data products. We will also provide a view into the range of data solutions being delivered to internal and external customers, and touch on a few examples of near-term and long-term data science projects, both of which exploit recent advances in automated knowledge base construction using neural approaches to natural language processing.
Bradley Allen is Chief Architect at Elsevier, where he leads the architectural governance of Elsevier, guides Elsevier Labs’ collaborative research into the future of scientific and medical publishing, and chairs Elsevier’s Data Science Leadership Group. Prior to Elsevier, Brad was founder and CTO at a series of enterprise software startups in the Los Angeles area, beginning his career as one of the first knowledge engineers of the expert systems era of artificial intelligence applications. He has a BS in Applied Mathematics from Carnegie Mellon University.
Daniel Kershaw is a Senior Data Scientist at Elsevier. Having completed his PhD in the Highlight DTC at Lancaster University in the Prediction of Information Diffusion in Online Social Networks, specifically the emergency and dynamics of new word formation e.g. fleek. Whilst at Elsevier he has worked on and delivered numerous Machine Learning for Personalised information discovery for Mendeley and Science Direct. Currently his focus is on automated text summarisation and knowledge graph construction for personalised information consumption and discovery.