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Each session contains multiple presentations and will cost $25 per attendee. The $25 registration fee is per session per attendee for the live session and/or on demand recording. The registration and on-demand link are registered to each individual participant's email address.
Currently, there are no volume or bulk discounts for ELUNA Learns. ELUNA is committed to keeping the cost for our educational events affordable, especially in these budget-challenged times. In order to provide quality member-based programming, we ask that individuals register for each of the events that are relevant to their work. Sharing login information for group-viewing sessions undermines the ELUNA's ability to provide this programming. If you value this program and the community that provides this content, either via the face to face meeting or online, please register for each session you will attend with your email account
ELUNA learns 2022 – eResources
- 1:00 pm - 1:05 pm. Introduction
- 1:05 pm - 1:50 pm. E-Resources, NZ Analytics, Python/Pandas/Jupyter & Alma APIs
- 1:50 pm – 2:00 pm. 10-minute break
- 2:00 pm - 2:45 pm. Reaping Resources for Recommenders: Working with LibGuides, MarcEdit, and Other Simple Tool
- 2:45 pm – 2:55 pm. 10-minute break
- 2:45 pm – 3:30 pm. Streamline your Evidence-Based Acquisition with Rialto
Note, schedule times are approximate. Schedule may shift slightly during the event.
E-Resources, NZ Analytics, Python/Pandas/Jupyter & Alma APIs. Jill Holman, PALS.
Do you need to combine several Alma Analytics reports together?Do you need to do this for more than one institution and/or reproduce it periodically?If either of those are true, you might be considering using Python/Pandas/Jupyter or Alma APIs. Learn about our recent projects and what we discovered from them in this session. In spring 2022, we combined NZ and IZ data from both Alma and analytics into one report for each of our institutions using Python/Pandas/Jupyter. It helped our consortium members see duplication and also what data is missing. For June 2022, we automated this process further for our MnPALS consortium using the Alma APIs.
Reaping Resources for Recommenders: Working with LibGuides, MarcEdit, and Other Simple Tools. Nancy Babb, University at Buffalo, State University of New York.
Primo VE's Resource Recommender functionality allows libraries to present a variety of curated resources in response to selected keyword tags. Databases and Library Guides are two types of common Resource Recommenders. Resource Recommender entries can be manually created in Alma or imported via Excel spreadsheet -- but the task may seem daunting for libraries who wish to include large lists of resources. The maintenance of these resources may also seem daunting, since the Alma Resource Recommender files are static and not automatically updated. Libraries that use LibGuides or another structured platform to host their library guides and database A-Z lists can use MarcEdit to harvest and process the OAI from their guides and A-Z lists and export the revised data for uploading to Alma. Excel and Notepad++ can be used for additional data cleanup and ongoing maintenance. This session will describe and demonstrate our process at University at Buffalo Libraries.
Streamline your Evidence-Based Acquisition with Rialto. John Larson, ProQuest, Part of Clarivate(Platinum Sponsor)
Evidence Based Acquisition (EBA) is a popular model among academic libraries who want to build their collections based on data while sticking to a pre-defined budget. In this session, you will learn how Rialto can help your library efficiently manage an EBA program and collaborate on selections within your existing Rialto workflow. You’ll see a demonstration of how EBA works in Rialto—including how to monitor your EBA pool and budget spend, using the Smart Selection tool, and how Rialto creates transparency for all staff around EBA activity.