Bibliometric Leaders Unveil New Methods to Understand Biomedical Science

Our portfolio company ÜberResearch, a leading data and analytics solutions and services company serving scientific funders and research organizations, has announced a set of innovative methods from a collaboration undertaken with a group of international bibliometric experts which represent a progression for the field of bibliometrics as it relates to the analysis of the life sciences. These methods will help researchers more easily identify variation in topics, and novelty in biomedical fields.

In a paper published in the journal Scientometrics, the international group led by Dr. Loet Leydesdorff, including Aaron Sorensen, ÜberResearch’s Head of Bibliometric Engagement and Scientometrics editor at the Journal of Alzheimer’s Disease, disclosed a set of methods that will help to open up new insights into the variations in topics, and novelty from within biomedical fields. Domain-specific terms and citation data are integrated together to help researchers improve their understanding of biomedical and disease fields, and the different kinds of topics, and novelty within those fields. This is important as it helps researchers more easily compare different hypotheses in the same line of investigation.

The paper outlines methods that enable users to integrate MeSH (Medical Subject Headings) terms with citation data. The MeSH terms are provided by the National Library of Medicine. By integrating these “gold standard” terms for describing topics, with citation data, the group achieved an enhancement.

They were able to retain the core archival structure for the field provided by the journal titles, but also use the MeSH terms to highlight the variations in topics, and indeed novelty, within a given scientific field. The group used the mouse-model approach to exploring the amyloid cascade hypothesis as the test for the new methods. This is the most dominant line of investigation within Alzheimer’s Disease research in recent history.

Aaron Sorensen commented:

“The new methods were used to condense this subfield of Alzheimer’s disease research into a collection of forty interrelated, landmark papers for the disease known as a ‘main path.’ In order to assess quality of the main path, the author lists of the forty articles were compared to a list of the ten most-highly-cited, dual winners of the two most prestigious Alzheimer’s research awards – it was quite impressive to see that the work of every single top-ten investigator appeared in the main path.”

Fig. 1: Journal references in red represent the core structure of research around the line of investigation of the mouse-model approach to exploring the amyloid cascade hypothesis. The MeSH terms in green reveal the variation of topics and novelty

The group’s methods and results are published in this paper in the Springer Nature journal, Scientometrics.