Cancer, climate change, gender inequality – these are just a few of today’s big challenges. To tackle them, we’re using information analytics. Elsevier technologists and data scientists are using machine learning and natural language processing to reveal insights and make content “actionable.”
For former Vice President Joe Biden’s Cancer Moonshot initiative, Elsevier produced a roadmap and report – Future Research Priorities in the USA – which sets out 13 areas of focus for the National Cancer Institute as part of the 21st Century Cures Act. To support the United Nations’ Sustainable Development Goals, Elsevier teamed up with SciDev.net to examine the field of sustainability science and the dialogue between science and society.
In both these examples, we applied our expertise in data science and bibliometrics to vast quantities of high-quality data, including the peer-reviewed research published by Elsevier and others, to understand the state of the research in the field and identify the most impactful paths to pursue.
With gender representation in research, until recently, much of the discussion has been driven by experience and speculation. At Elsevier, we aimed to support the dialogue with data. We undertook an evidence-based examination of the state of gender representation in research, employing bibliometric analyses and methodologies for gender disambiguation of authors in the Scopus abstract and citation database. Our report, Gender in the Global Research Landscape, presents insights and guidance on gender research and gender equality policy for governments, funders and institutions worldwide.
When taking on grand challenges, it is crucial to determine what to focus on. Elsevier brings together the content, data, technology and collaborators to support that process. As Biden explained in reference to his Blue Ribbon Panel, “We were determined … to make sure that we had the best minds in the country and mined the best minds in the world” to answer the question: “Where are the most immediate, biggest payoffs possible?” The key was to turn the panel’s recommendations into “doable, bite-sized” components whose impact could be measured, he said:
I want to thank Elsevier for focusing on drilling down and making sure we had this blueprint. ... My dad was right – it matters what the priorities are. And so it came to full fruition tonight with what you guys did in taking this down to very usable information.
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