Smart Data, Smart Library: Assessing Implied Value through Big Data
Jin Xiu Guo, Fei Xu · 2019
The growing expenditure on electronic resources has become a new norm for academic libraries.It is crucial for library administration to measure the impact of such investment consistently and persistently, and then develop collection strategies.Big data technology provides such an arena for management to gain insights through meaningful data and allow libraries to optimize collection operations in real time.The purpose of this study is to assess the implied value of a research library by analyzing Cost per Use with BigQuery a cloud-based data warehouse.The authors developed a systematic approach to process structured data including e-resource usage and interlibrary loan transactions, and then analyzed the data in BigQuery.Google Data Studio was employed to visualize the results.The findings of this study not only manifest the implied and exchange values of the research library but also offer an innovative approach to predict the future collection needs.The methodology employed in the study also provides a new opportunity for libraries to adopt big data technology and artificial intelligence to tackle intricate problems and make smart and informed decisions in this big data era.