Charleston 2017: COUNTER Release 5 — Consistency, Clarity, Simplification and Continuous Maintenance

Speakers: Lorraine Estelle (Project COUNTER), Anne Osterman (VIVA – The Virtual Library of Virginia), Oliver Pesch (EBSCO Information Services)

COUNTER has had very minimal updates over the years, and it wasn’t until release 4 that things really exploded with report types and additional useful data. Release 5 attempts to reduce complexity so that all publishers and content providers are able to achieve compliance.

They are seeking consistency in the report layout, between formats, and in vocabulary. Clarity in metric types and qualifying action, processing rules, and formatting expectations.

The standard reports will be fewer, but more flexible. The expanded reports will introduce more data, but with flexibility.

A transaction will have different attributes recorded depending on the item type. They are also trying to get at intent — items investigated (abstract) vs. items requested (full-text). Searches will now distinguish between whether it was on a selected platform, a federated search, a discovery service search, or a search across a single vendor platform. Unfortunately, the latter data point will only be reported on the platform report, and still does not address teasing that out at the database level.

The access type attribute will indicate when the usage is on various Open Access or free content as well as licensed content. There will be a year of publication (YOP) attribution, which was not in any of the book reports and only included in Journal Report 5.

Consistent, standard header for each report, with additional details about the data. Consistent columns for each report. There will be multiple rows per title to cover all the combinations, making it more machine-friendly, but you can create filters in Excel to make it more human-friendly.

They expect to have release 5 published by July 2017 with compliance required by January 2019.

Q: Will there eventually be a way to account for anomalies in data (abuse of access, etc.)?
A: They are looking at how to address use triggered by robot activity. Need to also be sensitive of privacy issues.

Q: Current book reports do not include zero use entitlements. Will that change?
A: Encouraged to provide KBART reports to get around that. The challenge is that DDA/PDA collections are huge and cumbersome to deliver reports. Will also be dropping the zero use reporting on journals, too.

Q: Using DOI as a unique identifier, but not consistently provided in reports. Any advocacy to include unique identifiers?
A: There is an initiative associated with KBART to make sure that data is shared so that knowledgbases are updated so that users find the content so that there are fewer zero use titles. Publisher have motivation to do this.

Q: How do you distinguish between unique uses?
A: Session based data. Assign a session ID to activity. If no session tracking, a combination of IP address and user agent. The user agent is helpful when multiple users are coming through one IP via the proxy server.


community site for usage statistics

Usus is an independent community website developed to help librarians, library consortium administrators, publishers, aggregators, etc. communicate around topics related to usage statistics. From problem-solving to workflow tips to calling out bad actors, this site hopes to be the hub of all things usage.

Do you have news to share or a problem you can’t figure out? Do you have really cool workflows you want to share? Drop us a note!

mapping ejournal use to subject areas

I had a thought last night as I was trying to fall asleep: what if I took our data on demand file that includes subjects and mashed it up with our consolidated JR1 use statistics? Could I get a better picture of the disciplines at my institution that are using ejournals? It’s definitely something worth looking at.

LibFest: Telling your Story with Usage Statistics — Making data work

presenter: Jamene Brooks-Kieffer

She won’t be talking about complex tools or telling you to hire more staff. Rather, she’ll be looking at ways we can use what we have to do it better.

Right now, we have too much data from too many sources, and we don’t have enough time or staff to deal with it. And, nobody cares about it anyway. Instead of feeling blue about this, change your attitude.

Start by looking at smaller chunks. Look at all of the data types and sources, then choose one to focus on. Don’t stress about the rest. How to pick which one? Select data that has been consistently collected over time. If it’s focused on a specific activity, it’ll be easier to create a story about it. And finally, the data should be both interesting and accessible to you.

By selecting only one source of data, you have reduced the stress on time. You also need to acknowledge your limits in order to move forward. You can’t work miracles, but you can show enough impact to get others on board. Tie the data to your organizational goals. Analyze the data using the tools you already have (i.e. Excel), and then publicize the results of your work.

Why use Excel? It’s pretty universal, and there are free alternatives for spreadsheets if you need them. Three useful Excel tools: import & manipulate files of various formats (CSV files), consolidate similar information (total annual data from monthly worksheets), and conditional formatting (identify cost/use over thresholds).

The spreadsheets are for you, not the stakeholders. Stop relying on them to communicate your data. The trouble with spreadsheets is that although they contain a lot of data, it’s challenging for those unfamiliar with the sources to understand the meaning of the data. Sending a summary/story will get your message across faster and more clearly.

Data has context, settings, complexities, and conflicts. One of the best ways of communicating it is through a story. Give stakeholders the context to hang the numbers on and a way to remember why they are important. Write what you know, focus on the important things, and keep it brief and meaningful. Here is an example: Data Stories: A dirty job.

Data stories are everywhere. It’s not strictly for usage or financial data. If you have a specific question you want answered through data, it makes it easier to compose the story.

Convince yourself to act; your actions will persuade others.

presenter: Katy Silberger

She will be showing three scenarios for observing user behavior through statistics: looking at the past with vendor supplied statistics, assessing current user behavior with Google Analytics, and anticipating user behavior with Google Analytics.

They started looking at usage patterns before and after implementing federated searching. It was hard to answer the question of how federated searching changed user behavior. They used vendor usage reports and website visits to calculate the number of articles retrieved per website visit and articles retrieved per search. They found that the federated search tool generated an increase in article/use. The ratios take into account the fluctuation in user populations.

Google Analytics could be used to identify use from students abroad. It’s also helpful for identifying trends in mobile web access.

NASIG 2010: What Counts? Assessing the Value of Non-Text Resources

Presenters: Stephanie Krueger, ARTstor and Tammy S. Sugarman, Georgia State University

Anyone who does anything with use statistics or assessment knows why use statistics are important and the value of standards like COUNTER. But, how do we count the use of non-text content that doesn’t fit in the categories of download, search, session, etc.? What does it mean to “use” these resources?

Of the libraries surveyed that collect use stats for non-text resources, they mainly use them to report to administrators and determine renewals. A few use it to evaluate the success of training or promote the resource to the user community. More than a third of the respondents indicated that the stats they have do not adequately meet the needs they have for the data.

ARTstor approached COUNTER and asked that the technical advisory group include representatives from vendors that provide non-text content such as images, video, etc. Currently, the COUNTER reports are either about Journals or Databases, and do not consider primary source materials. One might think that “search” and “sessions” would be easy to track, but there are complexities that are not apparent.

Consider the Database 1 report. With a primary source aggregator like ARTstor, who is the “publisher” of the content? For ARTstor, search is only 27% of the use of the resource. 47% comes from image requests (includes thumbnail, full-size, printing, download, etc.) and the rest is from software utilities within the resource (creation of course folders, passwords creation, organizing folders, annotations of images, emailing content/URLs, sending information to bibliographic management tools, etc.).

The missing metric is the non-text full content unit request (i.e. view, download, print, email, stream, etc.). There needs to be some way of measuring this that is equivalent to the full-text download of a journal article. Otherwise, cost per use analysis is skewed.

What is the equivalent of the ISSN? Non-text resources don’t even have DOIs assigned to them.

On top of all of that, how do you measure the use of these resources beyond the measurable environment? For example, once an image is downloaded, it can be included in slides and webpages for classroom use more than once, but those uses are not counted. ARTstor doesn’t use DRM, so they can’t track that way.

No one is really talking about how to assess this kind of usage, at least not in the professional library literature. However, the IT community is thinking about this as well, so we may be able to find some ideas/solutions there. They are being asked to justify software usage, and they have the same lack of data and limitations. So, instead of going with the traditional journal/database counting methods, they are attempting to measure the value of the services provided by the software. The IT folk identify services, determine the cost of those services, and identify benchmarks for those costs.

A potential report could have the following columns: collection (i.e. an art collection within ARTstor, or a university collection developed locally), content provider, platform, and then the use numbers. This is basic, and can increase in granularity over time.

There are still challenges, even with this report. Time-based objects need to have a defined value of use. Resources like data sets and software-like things are hard to define as well (i.e. SciFinder Scholar). And, it will be difficult to define a report that is one size fits all.