SciVal Metric: Scholarly Output

Benchmark the scholarly output of entities that are similar in size and that fall within similar fields of research, such as Institutions with a similar number of research staff, or Researchers in the same field of research and with similar career lengths

Provide impressive figures to showcase the performance of entities that are large in comparison to a group of peers, when this metric is likely to give high numbers

Look at publishing activity in a way that is difficult to manipulate

Investigate activity during the early stages of a new strategy when publications are just starting to appear, or the scholarly output of early-career researchers

Benchmarking the productivity of entities of obviously different sizes, such as Countries and Institutions, large collaboration networks and individual Researchers, or stable, established Research Areas and small, emerging Research Areas:

• Differences in the value of this “Power Metric” for comparing such entities will probably reflect distinct entity sizes rather than differences in prolificacy.
• Users are advised to limit the use of this metric to similar entities, or to use size-normalized metrics such as Citations per Publication.

Benchmarking the collaboration of entities with distinct disciplinary profiles:

• Academics in distinct fields tend to publish with very different frequencies. For example, Institutions with a high proportion of academics in life sciences, who tend to publish with high frequency, are likely to have a higher Scholarly Output than similarly sized Institutions with a high proportion of academics in humanities, who tend to publish with low frequency.
• Differences in Scholarly Output, in these cases, are most likely to reflect distinct disciplinary characteristics rather than to provide reliable information about differences in productivity.
• It is not advisable to use this metric to compare entities in distinct disciplines without accounting for these differences.
• When comparing entities made up of a mixture of disciplines, such as an Institution or a Country, users are advised to apply the Research Area filter to focus on one field that is common between all the entities, or to use field-normalized metrics such as Publications in Top Journal Percentiles which will take this into account.

Understanding the productivity of small entities for which there may be gaps within the Scopus coverage:

• A single missing publication from a small data set may have a significant negative impact on apparent productivity.
• The only way to account for this is to be vigilant. Consider also limiting the use of Scholarly Output to comparing larger data sets in which the potential gaps in the database coverage likely have a similar effect on all entities and do not invalidate the comparison.

Citation Countopens in new tab/window, which sums, over all publications, the citations received by an entity, and is a complement to Scholarly Output that counts the publications of an entity

h-indicesopens in new tab/window, whose values depend on a combination of Scholarly Output together with Citation Count, and are logical partner metrics

The set of all other “Power Metrics” whose value tends to increase as the entity becomes bigger: Subject Area Count, Scopus Source Title Count, Citation Count, Cited Publications (“Total value”), Number of Citing Countries, Collaboration (“Total value”),  Academic-Corporate Collaboration (“Total value”), Outputs in Top Citation Percentiles (“Total value”), Publications in Top Journal Percentiles (“Total value”), and h-indices

The set of all other “time-independent metrics”, which provide useful, reliable information immediately upon publication and do not rely on the passing of time for useful data to accumulate: Subject Area Count, Scopus Source Title Count, Collaboration, Academic Corporate Collaboration, and Publications in Top Journal Percentiles