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.
Published in | International Journal of Intelligent Information Systems (Volume 7, Issue 1) |
DOI | 10.11648/j.ijiis.20180701.12 |
Page(s) | 5-8 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Collection Services, Big Data, Academic Libraries, Demand Driven Acquisitions, Assessment, Digital Collections, Discovery Services, Customer Focused, Library and Information Science
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[13] | Zhang, Y. (2014, December 9). Evidence Based Acquisitions: does the evidence support this hybrid model? Retrieved from Information Today: http://www.infotoday.eu/Articles/Editorial/Featured-Articles/Evidence-Based-Acquisitions-does-the-evidence-support-this-hybrid-model-101019.aspx |
APA Style
Ying Zhang. (2018). Customer Focused Collection Services in the Age of Big Data. International Journal of Intelligent Information Systems, 7(1), 5-8. https://doi.org/10.11648/j.ijiis.20180701.12
ACS Style
Ying Zhang. Customer Focused Collection Services in the Age of Big Data. Int. J. Intell. Inf. Syst. 2018, 7(1), 5-8. doi: 10.11648/j.ijiis.20180701.12
AMA Style
Ying Zhang. Customer Focused Collection Services in the Age of Big Data. Int J Intell Inf Syst. 2018;7(1):5-8. doi: 10.11648/j.ijiis.20180701.12
@article{10.11648/j.ijiis.20180701.12, author = {Ying Zhang}, title = {Customer Focused Collection Services in the Age of Big Data}, journal = {International Journal of Intelligent Information Systems}, volume = {7}, number = {1}, pages = {5-8}, doi = {10.11648/j.ijiis.20180701.12}, url = {https://doi.org/10.11648/j.ijiis.20180701.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20180701.12}, 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.}, year = {2018} }
TY - JOUR T1 - Customer Focused Collection Services in the Age of Big Data AU - Ying Zhang Y1 - 2018/04/04 PY - 2018 N1 - https://doi.org/10.11648/j.ijiis.20180701.12 DO - 10.11648/j.ijiis.20180701.12 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 5 EP - 8 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.20180701.12 AB - 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. VL - 7 IS - 1 ER -