Reorienting Collection Analysis: Cost-Effective Item-Level Analysis and Machine Learning in Public Libraries.

In public libraries, especially those in rural settings, it is important that every dime of library funding is leveraged effectively into serving the community. As part of a year-long project beginning in January 2023, we are evaluating item-level cost-effectiveness for each circulating item housed...

Full description

Bibliographic Details
Published in:Information Technology & Libraries Vol. 42; no. 4; pp. 1 - 7
Main Author: Hanney, Ross
Format: tables/charts Journal Article
Published: American Library Association Dec2023
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=174633061&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 174633061
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        07309295
        ITL
      jtl: Information Technology & Libraries
      issn: 07309295
      maglogo: N
    pubinfo:
      dt: Dec2023
      vid: 42
      iid: 4
      pid: 55
      pub: American Library Association
      place: Chicago, Illinois
    artinfo:
      ui:
        174633061
        174633061
        174633061
        10.5860/ital.v42i4.16987
        174633061
      ppf: 1
      ppct: 6
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Reorienting Collection Analysis: Cost-Effective Item-Level Analysis and Machine Learning in Public Libraries.
      aug:
        au: Hanney, Ross
        affil: Staff Development Coordinator, St. Joe County (Indiana) Public Library
      sug:
        subj:
          Libraries, Public Economics
          Machine Learning
          Algorithms
          Rural Areas
          Information Technology
          Cost Effectiveness Analysis
          Item Analysis
          Indiana
          Data Analytics
          Integrated Library Systems
          Cost Savings
          Library Circulation Economics
          Artificial Intelligence
          Software Design
          Data Analysis
          Neural Networks (Computer)
      ab: In public libraries, especially those in rural settings, it is important that every dime of library funding is leveraged effectively into serving the community. As part of a year-long project beginning in January 2023, we are evaluating item-level cost-effectiveness for each circulating item housed at the public library in Lakeville, Indiana. Through the use of big(ish) data, some custom Python scripting, and machine learning algorithms we hope to answer: How much money is saved by library patrons through their use of the public library's physical collection? How much money is saved by the community through the operation of a public library based on the use of the circulating collection? And are there any non-obvious traits which make an item or title a more or less cost-effective circulating asset? In this column, I will describe the scripts, share initial findings, discuss challenges, and investigate next steps.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N