SciVal Strata FAQ

What is SciVal Strata?

SciVal® Strata is a tool that allows you to measure research performance using multiple metrics. It will let you understand and test how best to put your organization’s strategy in place, and how to demonstrate the value that you or your team represent to that strategy.

It does this by making it easy for the user to:

  • Take a look at performance of teams of researchers, and individual researchers
  • Judge performance in context, whether between teams and/or researchers, or against subject field averages
  • Look at performance of teams and/or researchers both within and outside your own organization (i.e. peers, competition, collaboration)
  • Look at different aspects of performance, that might be important in different fields, for different career stages, and for different questions
How is SciVal Strata different from SciVal Spotlight?

SciVal® Spotlight gives a view of distinctive and emerging research competencies from an institutional level. SciVal Strata on the other hand, provides a view of research performance that starts with the researcher and can be expanded to include groups and departments and is not limited by institution.

Where does the data come from? How often is it updated?

The data underlying the analyses in SciVal Strata comes from Scopus® and is updated weekly.

I’d like to compare my researchers and teams to peers from around the world. Can I import researchers from other institutions?

Yes. SciVal Strata allows you to import specific researchers regardless of their institution.

What types of analyses are available in SciVal Strata?
  • Citation Benchmark analysis - Average citations per document, of the set of documents published in any one year.
  • Citation Indices analysis - How the documents published by a researcher or cluster generate the h-index or g-index. Document rank (by citations to date) is shown together with citations to date (h-index) or cumulative citations to date (g-index).
  • Document Output analysis - Number of documents published by publication year.
  • Citations Received analysis - Total citations received to date for the set of documents published in any one year.
  • Cited / Uncited Documents analysis - The split of documents published in any one year that have been cited at least once to date, or not yet cited at all.
  • Geographical Collaboration Network - Shows the affiliation of each co-author (from the addresses in the relevant publications) of the researcher or researchers being examined. 
  • Author Network - Shows the h- or g-index rating over time for the researcher’s or cluster’s co-authors.
Can I benchmark against national averages?

Yes. The citation benchmark analysis function allows you to compare average citations per document compared to a national average in a given Reference Field.

What is a "Reference Field"?

A Reference Field is a group of sources, such as journals, that make up a subject field, against which it makes sense to compare the performance of particular researchers or clusters. There are default Reference Fields already in SciVal Strata, or the user can define their own Reference Fields by selecting specific sources.

What is a Cluster?

A cluster is a group of researchers. Think of it like a folder. It can contain one or more researchers and/or one or more clusters. For example a cluster can be a research group, i.e. International Antibody Team, and can contain any researcher found in Scopus. You can create as many clusters as you like, name them as you like and add any number of researchers or clusters to them as you like.

What are Ready-made Clusters (RMCs)?

As an additional service we will create clusters of researchers that you define, called Ready-made Clusters (RMCs). They have been quality assured using the same methodology applied in SciVal® Experts – a combination of computer matching and manual linking, gives the most precise profiles with the minimum effort on the customer's part. The resulting RMCs are uploaded to your implementation of SciVal Strata and are available to all of your users.

What are the benefits of RMCs?

Efficiency: Your users can get started with evaluation and benchmarking immediately without having to do preparation.

Quality: RMCs are quality assured using the same methodology applied in SciVal Experts. This means a quality check on all researcher profiles you would like to be populated. These quality checked profiles will also be transferred to Scopus.com.

Flexibility: All of your users will have access to the same ready-made clusters, and will receive the same updated information. Once imported, each user can modify the clusters, and create their own according to their needs.