Seeing the Forest by Counting the Trees: Using a Variety of Data Sources to See the Big Picture

Abstract

Libraries, particularly academic libraries, are swimming in a sea of data. Librarians often contribute to this by counting every possible patron interaction in an attempt to both define their current situation and to predict future staffing, budgetary, and collection needs. This investigation assessed the effectiveness of using various data sources in predicting future library activity and needs. The authors collected data on in-person and chat reference transactions, electronic journal downloads, database queries, and catalog searches from 2009–12. By analyzing these data points, the authors hypothesized they would find correlations that might be predictive of changes in related library services. Results indicated that the strongest correlations track activity over the course of the academic calendar. While none of the data points examined had predictive properties, the strong correlations between the data points over the period of time studied indicated that any one of them might serve as a stand-alone indicator of usage.

KEYWORDS:

• data
• library services
• leading indicators
• lagging indicators
• normalization of data
• reference
• chat reference
• e-journals
• database usage

Acknowledgments

This article is based on a presentation by Aaron Shrimplin, Andy Revelle, and Susan Hurst, “Seeing the Forest by Counting the Trees: Using a Variety of Data Sources to See the Big Picture,” at LITA, Columbus, Ohio, Oct. 6, 2012.

© Susan Hurst, Andy Revelle, and Aaron Shrimplin

Notes

1. Spring 2009 is not included because LibStats data collection was not implemented until July 2009.