Measuring library information services by sampling method (EAHIL2010 Poster)


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46 Justyna Seiffert, Wioletta Dyjas Measuring library information services by sampling method. Poland
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Measuring library information services by sampling method (EAHIL2010 Poster)

  1. 1. Measuring library information services by sampling method Justyna Seiffert, Wioletta Dyjas, Library of Medical University of Silesia in Katowice; Katowice; Poland Sampling method is allowed, time- and effort-saving way of gathering statistic data on information services in libraries. Introduction The Library of Medical University of Silesia in Katowice (MUS) has been taking part for seven years in a national project aimed at establishing Polish academic and research libraries performance indicators. Project Objectives requires detailed statistical data, many of The most difficult data to collect concerned which wasn't collected earlier. library information services. This data could not be collected by any automated system and manual compiling is laborious. It includes information requests, such as: - searching for specific documents (localization, correcting citations), Methods - Factographic questions (about facts, In 2008 performance indicators project dates, addresses), managers introduced a sampling method for - databases searching techniques information services data collection as consultations, allowed by international standard (ISO - databases searching performed by 2789:2006, point 4.2.2 and point 5.3). librarians for users. Standard defines: - types of information requests which should be counted; - necessity of counting requests delivered also by electronic media; - draft of the method: 'The sample should be taken in one or more normal weeks and Results grossed up' (ISO 2789:2006 page 29, point The MUS Library performed two samples: 6.3.8). the first on 20-25 April 2009 and the second on 23-28 November 2009. The date choice was done based on other libraries experience. Calculation The data was collected from all Library Data collected during the sample week was departments: the Main Library and three summed and the result divided by the faculty libraries. number of days in the week in which department was open. It has given the average for one day. Than the average was multiplied by the number of days in 2009 year in which department was open. It gave the estimates for all 2009 year. We calculated estimates for every of two samples separately and planned to gross them up together. Nevertheless, having compared results from spring and autumn samples, we drew the conclusion that November sample was not representative as regards time these results showed to be twice as big as in April sample. We found explanation by correlating sample results with other usage data. Monthly Library income from payable services showed that November was one of the most active months. Finally we counted estimates for 2009 only using the spring sample. Conclusions 1. Performed samples produced only estimates but nevertheless get us closer to real values. 2. Collected data showed how much of information services work and effort is passing unnoticed.