Investigation of Partition Cells as a Structural Basis Suitable for Assessments of Individual Scientists

Research output: Chapter in Book/Report/Conference proceedingConference paper


Individual, excellent scientists have become increasingly important in the research funding landscape. Accurate bibliometric measures of an individual's performance could help identify excellent scientists, but still present a challenge. One crucial aspect in this respect is an adequate delineation of the sets of publications that determine the reference values to which a scientist's publication record and its citation impact should be compared. The structure of partition cells formed by intersecting fixed subject categories in a database has been proposed to approximate a scientist's specialty more closely than can be done with the broader subject categories. This paper investigates this cell structure's suitability as an underlying basis for methodologies to assess individual scientists, from two perspectives:
(1) Proximity to the actual structure of publication records of individual scientists: The distribution and concentration of publications over the highly fragmented structure of partition cells are examined for a sample of ERC grantees;
(2) Proximity to customary levels of accuracy: Differences in commonly used reference values (mean expected number of citations per publication, and threshold number of citations for highly cited publications) between adjacent partition cells are compared to differences in two other dimensions: successive publication years and successive citation window lengths.
Findings from both perspectives are in support of partition cells rather than the larger subject categories as a journal based structure on which to construct and apply methodologies for the assessment of highly specialized publication records such as those of individual scientists.
Original languageEnglish
Title of host publicationProceedings of the science and technology indicators conference 2014 Leiden
Subtitle of host publicationContext Counts: Pathways to Master Big and Little Data
EditorsEd Noyons
PublisherUniversiteit Leiden, CWTS
Number of pages10
ISBN (Print)978-90-817527-2-5
Publication statusPublished - 2014
EventSTI 2014: the Science and Technology Indicators Conference - Leiden, Netherlands
Duration: 3 Sep 20145 Sep 2014


ConferenceSTI 2014: the Science and Technology Indicators Conference


  • Individual research performance
  • Domain delineation
  • Bibliometric reference values
  • Field partition
  • Research excellence


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