Up until now, to track and analyze reference questions, a library had to create a custom dataset. That’s still possible, of course, but if you’re a librarian who likes things in the right categories (and we know you are!), you can use a new option in the Reference Dataset to track those individual transactions.
How? When you create a Reference dataset in your LibInsight installation, you’ll see three options:
If you are tracking monthly statistics from another reference system, choose “For importing aggregate count of SMS, Chats, Tickets, & FAQs from my Reference system.” To have those numbers automatically harvested for you from LibAnswers, choose the second option. To enter details about each question answered at your desk, choose the third option, “To add individual Reference Questions.”
Bonus! You can integrate a READ scale field if you use that in your library. Analysis of the READ scale values is included in the dataset analysis.
Many folks use LibAnalytics to track their reference questions, and that’s great! LibInsight goes one further and gives you the power of all the field types in the Custom Dataset, applied to your Reference service! Add select fields for items like location or the method used to ask the question; add a multi-select field for items like “Resources Used.” Did you consult the catalog, a database, and a book from the ready reference shelf? No problem! Check all that apply. 🙂 Also available are Numeric, Monetary, Scale, and Date/Time fields. You can divide fields among three columns on the entry form and include text instructions, if you so wish.
Other New Features
We’ve also added a couple of new filters to analysis. For any select field, you can choose “is not” to see records that match all options except the one(s) you choose.
We’ve added a multi-select filter to the analysis page for Gate Count datasets so that you can analyze related libraries / entrances as a group:
Last but not least! You can now edit your Custom and Shared dataset Pre-Defined entries from the Manage Datasets > your dataset screen: