46 Justyna Seiffert, Wioletta Dyjas Measuring library information services by sampling method. Poland This upload is based on digital version of the poster It was send to eahil2010@gmail.com http://www.netvibes.com/eahil

1. Measuring library information
services by sampling method
Justyna Seiffert, Wioletta Dyjas
jseiffert@sum.edu.pl, wdyjas@sum.edu.pl
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.