Friday 5 May 2017

Introduction - Bibliometric Measures in Citation-Tracking Databases - Research Guides at University of Waterloo Library

Source: http://subjectguides.uwaterloo.ca/bibliometric_measures

Bibliometric Measures in Citation-Tracking Databases

Introduction

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This guide overviews bibliometric measures available in the citation-tracking databases Scopus, Web of Science, and Google Scholar. In particular, this guide explores:

This guide explores the bibliometric data available in these tools,
rather than their general searching functionality! To learn about
searching these or other databases, please contact your Liaison Librarian.

Mindful Use

Citation-tracking databases collect and report a range of
bibliometric measures, however their publication and citation data is
limited to works indexed in that database. For more information about
known limitations to citation-tracking tools, see Citation-Tracking.
Bibliometric data can support various levels of bibliometric
analysis. To understand possible objectives, and appropriate and
inappropriate uses of the data at different levels, see: Individual Data, Discipline Data, and Institutional Data.

Research productivity, impact, and output naturally differs across
disciplines, as does the relevance and usefulness of bibliometric
measures. The reality is that citation-tracking databases do not capture
these known differences well, both in the bibliometric data offered and
indexed content.

Publication behaviours across disciplines, with Neurosciences and Life Sciences having high frequency of publications, length of reference lists, and number of co-authors. Further, Mathematics, Computer Sciences, Arts and Humanities having low frequency of publications, length of reference lists, and number of co-authors.

Basket of Measures

Bibliometric
measures are one data point! A basket of measures approach can lead to a
more robust understanding of elements of research productivity and
impact. Beyond bibliometric and altmetric measures, other measures used
to capture elements of research productivity and impact include:

Peer review.
Type and amount of intellectual property, e.g., patents, licenses, and spin-offs.
Type and amount of research awards.
Highly qualified personnel developed by a researcher or group.
Publication acceptance rates.