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Author: Una Farr

Demonstrating research impact and setting a comprehensive strategy are critical tasks for any research organization, but gathering trustworthy insights can be difficult and time-consuming. To support organizations in reaching their strategic goals, Nature has recently developed Research Intelligence - a new suite of solutions which summaries research trends to allow organizations to quickly measure their success, uncover hidden connections, and guide their strategy. To mark the launch, we spoke with Markus Kaindl, Group Product Manager for Research Intelligence, about why the portfolio was developed, and how it contributes to the wider landscape of AI in information science.

Having majored in Computational Linguistics, Markus has always been passionate about natural language processing bridging the gap between humans and machines. In his current role, he leverages almost a decade of experience in research publishing and AI to support research organizations in their strategic decision-making.

You’ve spoken before about AI helping to tackle the “information overload” faced by the research community. Is this what you had in mind while developing Nature Research Intelligence?

Exactly. This challenge has been growing more and more with the sheer volume of publications and preprints on a daily basis. Never has it been more important to stay on top of scientific discoveries, but who can you trust? How can you ensure your results are comprehensive? With Nature Research Intelligence we want to empower non-analyst decision-makers by breaking away from the dominating search paradigm on existing platforms, where you still need to know the right keywords to find what you’re looking for.

This is only one of the challenges we are addressing, though. While most data is retrospective, one of our customers’ key jobs is to set future research strategies in order to attract funding and enable impactful collaborations. We want to provide them with forward-looking insights which enable them to deliver cutting edge research by spotting upcoming trends right when - or even before - they start to surface.

Tell us a bit more about the data. Where does it come from and why is it unique?

As I mentioned, our goal is to create the most comprehensive data platform there is to enable a holistic research assessment our partners can trust - and this is not only for ���ϳԹ��� content, but an inclusive pan-publisher solution. To that end we’re working with publicly available data from sources such as Crossref or OpenAlex, which we blend with Dimensions from Digital Science. This unique combination allows us to investigate relationships that go way beyond traditional academic citation analysis, building connections from grants to datasets via publications and their online attention, linking all the way to patent applications, clinical trials and policy making.

Can you walk us through some of the use-cases of the products? Was there anything interesting that was discovered during the pilot?

For the most part, Nature Research Intelligence helps research organizations get the right data - whatever that may mean for them. Our three products work alongside each other, all using data to guide decision-making. Nature Index provides a holistic benchmark of an organization’s research output and leverages its selective high-quality data in special focus supplements, e.g. on nanoscience or AI & Robotics. Nature Strategy Reports offer a comprehensive deep-dive into a particular research area explaining recent developments and future trends along with recommendations on how to keep up. Nature Navigator complements this by providing a live window into emerging research trends with smart subtopic clustering, novel publication summaries and simple subject matter expert identification. So in terms of use-cases, the possibilities really are endless. We want to provide solutions that meet our customers where they are - be that geographically, by discipline or vertical, or current analytics capability - and to listen very carefully to find out what is truly important for them to succeed.

A common trend we did find remarkable, though, was the shift to societal impact when it comes to measuring a research organization’s reputation and access. While rankings are still highly valued, we uncovered that we were really able to support these communities in finding alternative ways to monitor and promote their performance.

It seems like with these solutions, the real value lies in a collaboration between technology and people, would you agree?

Absolutely. We’re on the verge of moving from AI-assisted humans to human-assisted AI in many parts of daily life already. Ultimately, there is too much research for a single human to digest, but AI has only recently learned to properly read and write! Research is the final frontier due to its challenging complexity and intriguing nuances per field of study. We’ll need technology to support people to make the interdisciplinary connections between fields and research areas if science is to make that difference when progressing towards the United Nations’ Sustainable Development Goals.

With AI technologies getting more sophisticated every year, what do you envision for the future of Nature Research Intelligence?

We’re already proud of how Nature Research Intelligence simplifies the process of measuring research success, and this can only become even simpler as technology advances. Ideally, we would like organizations to provide us with as little, unstructured information as possible, and for our suite of products to take care of the rest. This combined with AI-powered technologies such as smart chart descriptions which are dynamically generated as the data changes - or even a knowledgeable Nature Research Intelligence chat bot that knows the answers before you’ve asked the question!

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