Steve - would you be interested in participating in a panel discussion on how libraries store and use their COUNTER data for the COUNTER Conference?

Please reply directly to me.
Thanks!

Karen R. Harker
Collection Assessment Librarian
University of North Texas Libraries
Denton, Texas 75287
[log in to unmask]

-----Original Message-----
From: Code for Libraries <[log in to unmask]> On Behalf Of Steve Meyer
Sent: Monday, March 30, 2026 2:25 PM
To: [log in to unmask]
Subject: [EXT] Re: [CODE4LIB] counter reports

[Some people who received this message don't often get email from [log in to unmask] Learn why this is important at https://aka.ms/LearnAboutSenderIdentification ]

At the UW-Madison Libraries we have been collecting COUNTER reports for over two decades. Each year the department that is currently called Electronic Resources Management has gone to all of our e-resource vendors and downloaded Excel versions of spreadsheets for various COUNTER reports. We typically collect reports for journal, book, database and platform use.

We are a Ruby shop, so I have a little Ruby gem that knows how to parse COUNTER Excel reports (assuming they are well-formed). This gem is used in a few different projects. Two examples would include a) scripts that are run over a single fiscal year’s worth of COUNTER files to collect numbers that go into our ARL and ACRL annual report submissions, and b) locally developed analytics sites for our staff to use.

For the latter, see this example for Nature from our Journal Statistics website:

https://journalstats.library.wisc.edu/journals/991021974405202122

This site does a lightweight FRBR merge for print and electronic use data. For our staff who can login, we also attach some payment data when the Alma data model allows us to make that connection.

Because the data collection is a massive task, we are in the process of migrating that workflow to the Celus platform.

Cheers,
Steve

On Mar 13, 2026, at 5:51 PM, Eric Lease Morgan <[log in to unmask]> wrote:


How is your library collecting COUNTER reports and making decisions against them?

As you probably know, COUNTER is a standard for formatting the usage statistics from vendors and publishers. The reports come in two formats: delimited and JSON. There seem to be about two dozen standardized reports, and the easiest ones to get your brain around are the book and journal reports. These reports list things like what book was viewed (or downloaded) in a given time frame, and then lists the total number of views/downloads. I know. The reports are much more nuanced than that. Such is only an example.

For the gentlest introduction, see "Basics and Resources: COUNTER" [1] An example COUNTER report ought to be attached, and it addresses the question, "How many times was Access Engineering accessed in the given year?"

Given the myriad of COUNTER reports, there ought to be more than a myriad of ways to interpret them. This community -- being a set people who eat data for lunch -- probably have experience getting and interpreting COUNTER data. Thus, I'm curious. How do y'all get, interpret, and use COUNTER data?

[1] https://urldefense.com/v3/__https://libtechlaunchpad.com/basics-and-resources/counter/__;!!Mak6IKo!KJi5kHHeP8gLZMAt-HQD-W4pWJt4h6rlle8ox8lh0JGDliTNCpCFtmoKeXzdK7emQXOJhiAPX5t0yTlOTlkekmqi3aDbp7qJG-o$

--
Eric Morgan <[log in to unmask]>

<counter-report.csv>