There is no single way to measure and compare research outputs and their impact, value, and prestige. There is also no single way to measure and compare the value and impact of an individual scholar during different stages of their career. There are multiple competing metrics developed by many groups, and new metrics are being developed. This guide defines some commonly used categories of metrics, identifies specific metrics within these categories, identifies controversies, and offers assistance in finding metrics.
What are common categories used to measure 'impact'?
Article impact: These metrics state that the value of individual works, such as journal articles, conference proceedings, and books, can be measured by the number of times they are cited by other works. This can include citations within scholarly works or alternative metrics such as tweets, blog posts, likes, bookmarks, etc.
Journal impact: These metrics state that the importance of particular academic journals can be measured by the number of times their articles are cited, and where they are cited. Different metrics weigh the value of time differently: whether it is better for citations to appear soon after publication or throughout a longer time period.
Researcher impact: These metrics state that the impact of individual researchers can be measured by the number of works they publish, the length of their career, the number of collaborators, the number and quality of their collaborations with other researchers, the number of times their works are cited, and when these citations occur (soon after the publication or later in time).
Altmetrics: Altmetrics is a shortened version of the phrase "alternative metrics." This word refers to counting mentions in publications that are alternatives to the traditional journal article: social media posts, blog posts, newspaper articles, page views of a website, tweets, likes, bookmarks, favorites, or follows. Altmetrics can be used in two ways: first, to assess the impact of a specific scholarly article or book. They can also be used to assess the impact of scholarly publications in formats ignored by traditional article metrics, like data sets, videos, infographics, presentations, web sites, or code.
Data Impact: Data sets can be published in journals or made available through repositories for others to re-use. These metrics state that he impact of a data set can be measured by counting how many articles, dissertations, or other publications have used the data set, or how many times it has been viewed, downloaded, or manipulated by unique users.
Institutional impact: These metrics state that the prestige of a department or area of research within an institution can be measured by measuring the collective impact of its researchers' output. For example, a department might count the number of citations to all articles arising from the department, count the number of articles appearing in journals with high impact factors, or count the re-use of data sets published by the department.