Day 1 - Data-Driven Dollar$: Analyzing E-Resource Usage in LibInsight

Springy_Will

Session information: https://buzz.springshare.com/springycamp/2022/data-driven-dollars

In April 2020, Creighton University Libraries subscribed to LibInsight with the intention of using data to support nearly all aspects of the libraries. In June 2021, with the addition of an Electronic Resources Librarian to the Libraries' staff, we were able to fully utilize LibInsight's ability to automatically calculate cost per use. In this presentation, we will highlight how we built the datasets for analysis, as well as how we maintain them and use them in our collection development process.

Have any questions for Brian Tuttle & Rachel Wallenbeck?

Post them here! 💬

Groomej

I think I need a deeper explanation of your different data sets - what is in them and why.

amartel

We currently aren't tracking non-SUSHI compliant vendors in LibInsight and are still manually creating spreadsheets to track them. Did you just create Custom datasets for that data? Are you standardizing it in any way?

rachelwallenbeck

Sure, @Groomej! We have three datasets:

1. Database Master dataset - We only pull Database Master reports (COUNTER 5) via SUSHI in this dataset. This is for all of our databases that offer COUNTER 5 reports via SUSHI. If the vendor does not offer SUSHI and COUNTER 5 reports, the database usage is entered manually in our custom dataset.
2. Title Master dataset - We only pull Title Master reports (COUNTER 5) via SUSHI in this dataset. This is for all platforms where we own title-level (journals or ebooks) subscription content. If the publisher does not offer SUSHI and COUNTER 5 reports, we manually enter the data in our custom dataset.
3. Custom eResource manual-entry dataset - Includes the usage for any content we subscribe to that do not fit into the above datasets. Some are databases, some are journals, some are packages! If vendors don't offer COUNTER reports (unique reports), or they do not have SUSHI-harvesting capabilities for their usage reports, they are entered in this dataset.

rachelwallenbeck

@amartel We use the E-Journals/Databases - r4 dataset template for our manual-entry dataset, which includes all of our resources for vendors that do not offer COUNTER reports or SUSHI. We don't break them down by Platform in that dataset though. We enter the resource name as the platform and use the manual entry form to enter the data for each resource each month. Then, we can enter the cost for that single resource and it calculates the CPU on that main screen of the dataset. We also use the internal notes for each platform to track how stats are gathered, where to go for stats, what stat to use (to be consistent if the stats are unique to that platform), etc.

Jozina_Cappello

Can you use this ( Cross-Dataset Analysis: Compare multiple Datasets with each other) with all the datasets to create one graph to show admin?

rachelwallenbeck

@Jozina_Cappello I think that depends on the type of information you want to analyze. For our purposes, the Cross-Dataset analysis doesn't work for our process. We take a look at the particular resources within our datasets and compile them into a report. We don't cross-analyze the datasets because there is no need for us to compare the usage across the datasets. We only look at particular data points individually for our FY collection development process we discussed in our presentation.

Now, if we were wanting to compare vendors or resources or some other scenario, then yes! This feature would be great for that!