Academic Identity

Some common metrics are the H-index, Journal Impact Factor, and the FWCI (called CNCI in Web of Science).

• H-Index is a measure of how many times a journals published articles are cited, an index of fifteen means an article has been cited 15 times.
• Journal Impact Factor (IF) – A measurement of how many times a journal’s published articles are cited by different researchers.
• FWCI – Publication Field weighted citation indices indicate how the number of citations received by researcher’s publications compared to the average number for similar publications.
• Category Normalized Citation Impact (CNCI) – Calculated using Web of Science, CNCI is “an indicator of impact normalized for subject focus, age and document type. A CNCI of 1 is at par with the world average, anything above 2 is twice the global average
• SJR - Scimago Journal Rank is a measure of the "prestige" of journals which makes use of both the number of citations a journal accrues and the perception of those journals in the wider academic community
• SNIP - Source Normalized Impact per Paper is a metric which accounts for the field specific differences between journals. The need for this is that some fields have different publishing practices, time frames, and constraints. This results in the need for a metric like SNIP which is calculated by comparing the citations per journal with the citation potential of the field as a whole, in other words it would measure of history journal against other history journals and vice versa for other academic disciplines     

Why are they important?

• Bibliometrics like the H-Index can tell you a lot about a researcher's impact, and it can be used as a measure of the reach of research.
• They are used by certain stakeholders such as journals, and universities to make decisions which can effect you and your career
• On top of this they are also useful to you as a researcher in that they allow for you to measure the impact of your research, and measure readership and use of your work.

The pros of bibliometrics are easy to pin down, they are...

1. Objective because they are quantitative, easily reproducible
2. Coverage going back decades
3. Coverage can be close to comprehensive, though not always
4. Easy to produce and maintain
5. Transparent

Limitations of Bibliometric Data

There are a number of limitations to biblio and alt-metrics, here are the most commonly agreed upon.

1. Quality: a high citation count doesn't directly equate with quality in a scientific paper, neither does it mean that a paper is the most cutting edge research in a given field. What these metrics tell us is how much attention is being paid to a specific article.
2. Academic Disciplines: different disciplines have different publishing standards, research can take longer etc. and thus there can be wide variance between say history and chemical engineering.
3. Data problems: all metrics are based on data sets. These datasets can be incomplete in certain cases and therefore cannot tell the whole story. Others may have other problems, this is why you must be a critical consumer of information when using bibliometric data.