Volume 7, Issue 1, February 2018, Page: 5-8
Customer Focused Collection Services in the Age of Big Data
Ying Zhang, University of Central Florida Libraries, Orlando, USA
Received: Sep. 29, 2017;       Accepted: Oct. 19, 2017;       Published: Apr. 4, 2018
DOI: 10.11648/j.ijiis.20180701.12      View  1048      Downloads  51
Abstract
As part of library core functions, collection services had always focused on resources and processes in the print age. With the advent of big data with prevailing digital technologies in the recent decades, academic libraries in the U.S. have increasingly brought customer into the center of collection services. Big data empower these customer-focused services in various formats and scopes. What are some common practices? How effective are they in addressing the customer needs while fulfilling the conventional goals of collection services? This article starts with a historical overview on the evolutions of collection activities from the perspectives of academic libraries in the U.S. It then shares several key trends and common practices enabled by big data to build collection services centering on customers, including demand driven acquisitions models, digital collections development, collection access and discovery enhancements and systematic collection assessments. The article also discusses the multitudes of implications and impacts brought by these new customer-focused collection services on the library and information science (LIS) profession, in technologies, in philosophies, in personnel, in budgets and certainly in user experience.
Keywords
Collection Services, Big Data, Academic Libraries, Demand Driven Acquisitions, Assessment, Digital Collections, Discovery Services, Customer Focused, Library and Information Science
To cite this article
Ying Zhang, Customer Focused Collection Services in the Age of Big Data, International Journal of Intelligent Information Systems. Vol. 7, No. 1, 2018, pp. 5-8. doi: 10.11648/j.ijiis.20180701.12
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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