ÜberResearch, a data and analytics solutions and services company serving scientific funders and research organisations, 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.
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