Research performance collaborations
Researchers and research institutions are under increasing pressure to demonstrate both their academic and broader societal impact. Elsevier partners with the scientific community through programs such as Snowball Metrics to develop a basket of metrics that is comprehensive, relevant and usable at all stages of the research workflow.
Whether it’s via citations, teaching assessments, compliance scores or grant success rate, there is a growing mandate to measure every element of a researcher’s work across the entire research workflow. Universities, too, have to address national assessment exercises, rankings and the pressure to show return on investment for research programs.
Collaborative projects with teams at Elsevier are looking more deeply at ways to measure impact of research and ways to optimize performance at the institutional level.
Measuring research performance
Assessing research impact in SDG 2 (Zero Hunger) and 17 (Partnerships for the Goals)
A key sustainable development goal (SDG) of the United Nations is in Zero Hunger. In an ongoing collaboration at Wageningen University and Research the WUR-Elsevier team is looking at how data from Scopus, Scival, Newsflo, PlumX and LexisNexis NewsDesk can help demonstrate how Wageningen University’s SDG2 research and researchers are used and taken up by policymakers and the media. Not only will the holistic reporting show the institution’s contribution to Zero Hunger, it also supports SDG 17: Partnerships to address the SDG Goals.
Social metric modelling attribution
Research Associate Waqas Khawaja (left) in the Semantic Web group and PhD Student Mohan Timilsina in the Machine Learning & Statistics group at the Insight Center for Data Analytics, National University of Ireland, Galway.
Citations aren’t the only way to measure research impact. Researchers at the Insight Centre for Data Analytics at the National University of Ireland, Galway looked at how online news and social media could be attributed to published research, and how that could be weighted and modelled. Using data from Scopus and PlumX, the team developed a framework for Social Metrics modelling and attribution.
- Read more about our collaboration in social media networks at University of Galway in our article: Altmetrics reveal insights into the impact of scientific knowledge
Evidence-based planning for research rerformance
Queen's University Belfast (photo (C) istock.com/RobertMayne)
If a university knows where they stand, they can plan their future. Queen’s University Belfast worked with Elsevier’s Research Metrics team to undertake a deep dive analysis of the university’s published research across several schools. They looked at the citation impact and quantity of publications as well as the proportion of international collaborations. The results not only gave them insights into how the university compares to its peers; it provided the evidence that helped change the culture and conversations around research metrics that support their new publication strategy and research ambition.
- Read more about the collaboration in these articles: Elsevier and Queen’s University Belfast: a metrics-driven approach to research success (p49)
- How personalized metrics can change behaviour and improve research performance.
- A free webinar and case study are also available.
Elsevier-UC Davis Data Science Program
Left to Right: Duncan Temple Lang, Director of the Data Science Initiative; MacKenzie Smith, University Librarian; Brad Fenwick, Senior VP of Global Strategic Alliances at Elsevier; and Paul Dodd, Associate Vice Chancellor for Research. Photo credit: Kar
Universities benefit from assessing the competitive positioning of their programs. The joint Elsevier-UC Davis Data Science Program will utilize Elsevier’s support, data and tools to evaluate the effectiveness, competitiveness and impact of UC Davis’ research, teaching and other academic activities using a data-driven approach. Their goals include improving institutional effectiveness and building more effective models for interdisciplinary collaboration among researchers.
- Read more about this collaboration on the UC Davis site here
- And in our article: Partnering in the US for the advancement and promotion of research.
Improving the evaluation process
Can reviewers really predict the impact of an article? In collaboration with Cell Press, a team from the Crowd Innovation Lab at Harvard Business School is investigating whether there are detectable elements in a manuscript that can be used to predict the future impact of a research article. The research team will measure how key characteristics of submitted manuscripts (for example combinatorial novelty, multidisciplinary coverage, topic currency) correlate with editorial and reviewer evaluations, and published article metrics.
Detecting signals of societal-economic impact
Knowing the recipe for impactful research will help universities make the most of their research efforts. We’re working with Professor Michael Khor, Director of RSO and Bibliometric Analysis in Nanyang Technological University’s Research Support Office to profile the field of Biomaterials over time in order to assess whether we can identify and detect early signals of impact in the area of biomaterials.
- Research Intelligence reports
- Research Metrics
- Article level metrics
- Plum X metrics
- Snowball metrics
- Using research metrics responsibly and effectively as a researcher (2016)
- Research Intelligence Resource Library
- A “basket of metrics” the best support for understanding journal merit (European Science Editing, 2015)
- Pursuing a multidimensional path to research assessment – Elsevier’s approach to metrics (London School of Economics Blog, 2015)
- Impact of science: the need to measure
- Response to HEFCE’s call for evidence: independent review of the role of metrics in research assessment
How we support national assessment exercises and rankings