a month in the life of a university bibliometrician dr ian rowlands university of leicester, uk
Post on 12-Jan-2016
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University of LeicesterCollegesArts, Humanities & LawEngineering & ScienceMedicine & Life SciencesSocial Sciences
People21,800 students (7,700 distance)1,300 academic staff
Research incomeResearch grants and contracts£ 55 million (2013)REF-related QR income£ 24 million (2013)Famous forDNA fingerprintingSpace scienceRichard III
Library Research Services
Research analytics
Research data management
Researcher training and development
Institutional repository
Gold open access funds
Interface with University systems
Briefings on information issues
PhD training (library tools)
Project support
Bibliometrics support
Internal consultancy
Management reports
My diary March 2014
Staff training and development•Briefing on journal impact factors•Briefing on researcher identifiers•Live webinar on h-index•Develop `citation tips’ leaflet
Reports•Background report on QS World University Rankings for Vice-Chancellor• Analysis of collaboration between universities in the English Midlands• Internal review of Department of Chemistry
Major enquiries•Can we use citation data to help thin out the print journal collection?•How can citation data be used in a systematic health review?
Quick enquiries•Handling Spanish surnames•Finding someone’s h-index
Routine maintenance•Quarterly update of InCites address database
REF2014
REF2014 is a UK-wide framework for assessing research in all disciplines. Its purpose is:
• to inform research funding allocations (approximately £2 billion per year)
• provide accountability for public funding of research and demonstrate its benefits
• to provide benchmarks
Assessment criteria
The criteria for assessing the quality of outputs are originality, significance and rigour*
Four star Quality that is world-leading in terms of originality, significance and rigour
Three starQuality that is internationally excellent in terms of originality, significance and rigour but which falls short of the highest standards of excellence
Two star Quality that is recognised internationally in terms of originality, significance and rigour
One star Quality that is recognised nationally in terms of originality, significance and rigour
UnclassifiedQuality that falls below the standard of nationally recognised work. Or work which does not meet the published definition of research for the purposes of this assessment
Assessment criteria
The criteria for assessing the quality of outputs are originality, significance and rigour*
Four star Quality that is world-leading in terms of originality, significance and rigour
Three starQuality that is internationally excellent in terms of originality, significance and rigour but which falls short of the highest standards of excellence
Two star Quality that is recognised internationally in terms of originality, significance and rigour
One star Quality that is recognised nationally in terms of originality, significance and rigour
UnclassifiedQuality that falls below the standard of nationally recognised work. Or work which does not meet the published definition of research for the purposes of this assessment
NOT FUNDED
NOT FUNDED
NOT FUNDED
REF2014 and use of citation data
• The following subpanels will make use of citation data:
- Main Panel A: Subpanels 1-6 [life sciences]
- Main Panel B: Subpanels 7-11 [physical sciences]
- Main Panel C: Subpanel 18 [economics]
• REF2014 will use only use Scopus citation data
• None of the sub-panels will use journal impact factors, journal rankings, or other forms of bibliometric analysis
How we used citation data
• Each paper was graded by two assessors, at least one external to the University
• We counted Scopus citations and used published REF2014 calibration tables to locate papers in the top 1%, 5%, 10% or 25% of world impact
• We repeated the exercise using Web of Science InCites, where we have continuous citation percentiles and other metrics such as journal impact factors
How we used citation data
• Citation data showed a very good fit with human judgments, so were a helpful source of additional information
• The data were particularly useful in guiding decisions at the critical 3*/2* boundary
• The data helped us to model the whole submission and (hopefully) optimise the trade-off between grade and volume
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