...that the world’s favorite search engine wouldn't exist without bibliometrics?

The SCImago Journal Rank (SJR) metric and the related Eigenfactor trace their origins back to pioneering work by Gabriel Pinski and Francis Narin in the 1970s (1), and are, in this way, also related to Google’s PageRank algorithm, which powers the famous search engine. Using data on cross-citations between journals, they developed an iterative ranking method for measuring the influence of a journal based on who is citing it and how influential they are.

Although Pinski and Narin were able to apply this method to a small database of physics journals, technological limitations meant the method could not be easily used on larger sets of journals, and it was neglected by bibliometricians.

All this changed in the 1990s with the rapid growth of computing power and the internet. Users needed an effective way of navigating through the sea of online content to find the information they wanted. In developing the Google search engine to address this, Larry Page drew on Pinski and Narin’s research to design the PageRank algorithm that ranks the importance of a webpage based on how many links it receives and who these links come from (2).

The popularity of Google triggered a renewed interest in Pinski and Narin’s work in the bibliometrics field that led to the development of metrics such as SJR.

References:
(1) Pinski, G. and Narin, F. (1976) “Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics”, Information Processing and Management, 12:297-312.
(2) Brin, S. and Page L. (1998) “The anatomy of a large-scale hypertextual web search engine”.