  The launch of Google Scholar (GS) marked the beginning of a revolution in the
scientific information market. This search engine, unlike traditional
databases, automatically indexes information from the academic web. Its ease of
use, together with its wide coverage and fast indexing speed, have made it the
first tool most scientists currently turn to when they need to carry out a
literature search. Additionally, the fact that its search results were
accompanied from the beginning by citation counts, as well as the later
development of secondary products which leverage this citation data (such as
Google Scholar Metrics and Google Scholar Citations), made many scientists
wonder about its potential as a source of data for bibliometric analyses. The
goal of this chapter is to lay the foundations for the use of GS as a
supplementary source (and in some disciplines, arguably the best alternative)
for scientific evaluation. First, we present a general overview of how GS
works. Second, we present empirical evidences about its main characteristics
(size, coverage, and growth rate). Third, we carry out a systematic analysis of
the main limitations this search engine presents as a tool for the evaluation
of scientific performance. Lastly, we discuss the main differences between GS
and other more traditional bibliographic databases in light of the correlations
found between their citation data. We conclude that Google Scholar presents a
broader view of the academic world because it has brought to light a great
amount of sources that were not previously visible.
