Scan of Article Bento Boxes and Filtering Summon

At Penn State, we’re planning a discovery revamp which will include presenting our catalog with a Blacklight layer over the MARC records and creating a Bento landing page for the front-page search, which currently goes to Summon. We’ve been reviewing other institutions who’ve implemented such approaches, determining their choices, and assessing how they do or don’t meet our own needs.

The box causing the most conversation right now has been our Summon search. We don’t plan to serve it up in Blacklight yet, as some institutions do, although that’s on the table for the future. But, if our Summon currently contains 1,000,324,214 records¹ (whereas our library’s catalog contains almost 7 million…) what should we actually be searchingwhen we’re returning those results from Summon to the Bento page.

Of the institutions we reviewed, all had a box labeled something along the lines of Articles or Articles+ (or Articles & Ebooks). Most did not search the entire serials/databases/subscription interface but used some kind of faceting to filter result types toward a more scholarly result. Some excluded. Some included. Some did both. I found the scan of enough interest that I decided to share them on both our staff blog and my personal website.

I’m including two tables from the scan. The first is a table of information gathered about choices for the Articles/Articles+ Bento box. The second is a table which compares the total possible number of results from an institution with the total number of results when faceting is applied. The second table only includes institutions which provide at least fairly direct access to their Summon. I couldn’t do a null search of Summon over Blacklight.

This iteration of the scan was conducted between 16 and 17 January, 2018 and numbers, choices, and percentages may change.

Articles+ Scan

These results were all collected as an off-campus user who was not logged in. Institutions included in the scan were those whose Bento implementations we had chosen for review, not all institutions who may be using such functions. Ordering has no meaning.

Edit, 2018-01-25: Added Michigan State University

How Faceting Affects Search Results

These results were all collected as an off-campus user who was not logged in. Institutions included in the scan were those whose Bento implementations we had chosen for review which also had Summon and had not applied a Blacklight layer. Ordering has no meaning.²

Edit, 2018-01-25: Added Michigan State University

Our Own Numbers

We did our own experimentation on the subject and determined that faceting our Summon to include only Scholarly & Peer Review material returns 97 million results. Of those, 9.8 million are Book Reviews, which are a known issue in clouding our search results (although some Book Reviews are tagged as Journal Articles in Summon). So, cutting those out, we come down to almost 88 million records. We’ll be doing user testing, of course, so these decisions aren’t solid. But I think they’re a good starting place for us.

Notes