Log 4:Part 2 Cataloging Children's Books with Cynthia and meeting with Alyssa about library technology
Updated: Jul 21, 2024
May 31st UTEP Library
Media & Microfilm, Cataloging Department
TiJeat Berry; Supervisor Joy Urbina and Virginia Rassaei
Terms: AI = artificial intelligence; AR = accelerated reader; DDC = Dewey Decimial Classification; Para = paraprofessional or teaching assistant
Cynthia/Children’s
I had a one-hour meeting with Cynthia Navarro, the Metadata Specialist Supervisor, regarding cataloging the children’s collection. There are four different categories: EASY, FICTION, NON-FICTION, and BIOGRAPHY. Some of them use DDC.
What I learned:
Use title verso to obtain metadata
Catalogers must use a different Cutter table than the one online, below is an image of the book we used to get our Cutter number for the two books we cataloged; one was Holding Her Own: The Exceptional Life of Jackie Ormes by Traci N. Todd and Illustrated by Shannon Wright.
Book used to create Cutter #
The following 3 websites:
Teaching Books https://school.teachingbooks.net/
Accelerated Reader https://www.arbookfind.com/default.aspx
Are used to collect metadata for fields:
521 Target Audience Note
521 0 _ Grade Level
521 1 _ Age Range
521 8 _
526 Study Program Information Note
526 0 _ Accelerated Reader information
586 Awards Note
All the awards for a book must be listed in 586
The Non-Fiction Children’s Book collection is the only one that is classified using DDC.
During this process, I also learned that 526 0 _ subfields explain the specifics of the AR system for an item.
The example provided by Cynthia
Quiz Type | Interest Level | Reading Level | AR Points | Quiz # | ||
Accelerated Reader | AD | ‡b UG | ‡c 5.6 | ‡d 21.0 | ‡z 139117 |
This was a short sit-down with Cynthia, but it again helped me understand the fields and subfields in real time. I did not get a chance to catalog a book on my own but I did use C.A. Cutter's Three-FIgure Author Table to create a unique Call # for Cynthia. I assume that children's librarians use the 526 0_ and 586 in school libraries, and these fields would help teachers decide which books they want to keep in their classrooms and put on their reading lists. It provides them with the data without having to go to the website and obtain it themselves. As a substitute and para, I know that teachers do not have the time to research and review books even by reading summaries. This is another way modern librarians, regardless of the type of library they work in, need to operate in a similar fashion to knowledge managers in special librarians within a business or law firm.
During my time with Alyssa, I learned about ListServs, AI technology, cataloging professional groups, and how to sell myself during interviews and resume development. She keeps a list of articles she reads in a spreadsheet accompanied with links. I believe this would be a better method than the one I currently use. She specializes in emerging technologies including AI and provided some insight regarding BIBFRAME, the semantic web, and linked data; she argued that linked data across the whole web would be hard to achieve, but that it is possible on a smaller scale, such as bringing together all data on a specific topic structured in a distinct category. Her example is linking data on women + mayors + United States = data that can gather and represent the nuance in this particular relationship.
She also directed me to
And Wikidata
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