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Pure Impact AI, a GenAI-powered storytelling module, transforms data from Elsevier’s research information management system Pure and other trusted sources into evidence-based impact narratives.
These narratives reveal new insights, helping academic communities connect and showcase their meaningful impact on the world.
Pure is home to a wealth of harvested and self-reported information about institutions and their researchers. Pure Impact AI blends this data with insights from sources like Scopus, Overton, PlumX metrics, and LexisNexis patent data, offering a holistic view of research impact in seconds.
Pure Impact AI generates narratives and visualizations that can be saved to Pure as impact statements, enhancing research storytelling.
Collaboration with universities, funders, and academic thought leaders worldwide was key to designing, testing, and refining Pure Impact AI. The community's valuable input shaped important decisions about the module’s functionality and features.
Ongoing collaboration with academic partners will remain central to developing and improving Pure Impact AI.
"It’s hard for a lot of researchers to talk about themselves and how their work has been impactful… having a tool which can provide something that’s a helpful starting point that the researcher can then take and tweak and polish… that’s a lot easier than starting from a blank page."
PD
Paul Daniels
Athabasca University, Athabasca, Canada
Pure Impact AI is developed in line with Elsevier's five Responsible AI Principles. For example:
Real-world impact
Academic community members have been closely involved since the earliest stages.
Robust data privacy
Any data that users enter is treated in line with our Privacy Policy. We also adhere to European privacy regulations.
Human oversight Our teams perform ongoing, robust quality assurance of the AI-generated narratives. We ensure the intended use is understood by users and encourage them to be the ultimate decision-makers.
Pure Impact AI generates impact narratives in seconds, saving hours of manual work.
Users select the relevant project, person, or set of research outputs in Pure. They can also manually enter publication IDs.
Pure Impact AI gets to work, drawing relevant data from its varying sources.
It generates a multi-dimensional view of the impact, including a visualization, a summary of the research and a list of all reference material used.
Users can edit the AI-generated view to ensure it reflects the full breadth of their research impact.
Pure Impact AI tracks impact across seven research characteristics, carefully selected to span all research domains and mirror the diverse ways we communicate as humans —through creativity, collaboration, influence and knowledge sharing.
The visualization it generates includes weightings for each characteristic, providing valuable insights for strategy planning, resource allocation and beyond. It not only helps users identify where their research already excels, it also highlights areas of potential focus.
"What I found with a tool like this – it’s a time-saving thing… I very much saw it as a supplement to our impact prep work and our thinking at the start of an impact journey, in particular. "I found this tool (Pure Impact AI) extremely useful in overcoming that first hurdle, as my grasp of the subject field is developed more quickly and, as a result, I’m prepared in a shorter timeframe. It perfectly supplements the information we are acquiring ourselves through reading project reports and outputs."
LN
Laura Noble
Research Impact Manager at Coventry University, UK
Pure Impact AI captures the full depth of research contributions; a great way to demonstrate impact beyond citation and publication counts.
Enrich your impact narratives:
Build relatable impact narratives, strengthened by the inclusion of your institution’s Pure data. The more data you enter in Pure, the stronger your impact story will be.
Enhance funding opportunities:
Use the narratives to comply with funder requests for evidence of impact.
Create impact highlights:
Showcase researchers’ work, research projects, or departmental impact.
Pure Impact AI helps to identify, understand, and describe the societal impact of your institution’s research, promoting accountability and transparency.
Automatically generated narratives can be leveraged in:
Annual reports
National assessments
Recruitment
Fundraising
Engagement with the public, donors, and alumni
About the 7 research characteristics
Pure Impact AI tracks impact across seven research characteristics, reflecting creativity, collaboration, influence, and knowledge sharing across all domains.
Academic significance: The extent to which the research advances knowledge within its academic field. Factors include the robust nature of the findings and their contributions to theory and methodology.
Collaboration: The degree to which the research involves cooperative efforts across different disciplines, institutions and sectors, leading to synergistic outcomes.
Engagement: The extent to which stakeholders, including researchers, practitioners, policymakers and the public, are involved in conducting and disseminating the research.
Novelty: The degree of originality and innovation in the research; for example, how new the ideas, methods or applications are.
Reach: The extent to which the research findings are disseminated and accessed by a wide audience, both within and outside academia.
Transferability: The extent to which the research findings can be applied to other contexts, settings or populations beyond the original study.
Applicability: The extent to which the research findings are used to address societal issues, including their influence on policy making, practical implementation and broader societal outcomes.
