This document discusses using EZProxy logs, the library's patron database, MySQL, and ColdFusion to analyze usage of library resources at William Paterson University. EZProxy logs patron access to databases, journals, and other resources and are loaded into a MySQL database monthly alongside patron data from the library catalog. Statistical reports are then generated to understand usage patterns of resources by variables like academic department, class level, and location. The analysis aims to inform collection development and service decisions.

1. Application of EZProxy logs, Voyager’s
Patron Database, MySQL, and
ColdFusion for Comparative Usage
Analysis of Library Resources
Ray Schwartz,
William Paterson University of NJ,
schwartzr2@wpunj.edu
ENUG Conference, University of Bridgeport, CT
Thursday, October 27, 2011

2. Our University
• 9000 undergraduates
• 1000 graduates (mostly education majors)
• 400 faculty
• 800 adjuncts
• 1000 staff
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3. Our Library
• 19 librarians and 26 library staff
• 350,000 volumes
• 18,000 audiovisual items
• 47,000 print and electronic periodicals
• 124 general and subject specific databases
• $1,100,000 Non-Salary Allocations
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4. EZProxy via LDAP authenticates
access to:
• Databases
• Electronic journals
• ILL/Doc Delivery forms

5. Example of EZProxy log entry
• Ip address nj.dhcp.embarqhsd.net
• (Not used) -
• user id theuser
• date/time 1/1/2008 4:25:15 AM
• Method GET
• page http://ezproxy.wpunj.edu:2048/connect?
retrieved session=sGHMbeSss121YxZa&url=http://www.wpunj.edu/scripts/webs
cript.exe?fs.scr
• Version
HTTP/1.1
• response
code 302
• no. of bytes
• Referring 537
URL http://ezproxy.wpunj.edu:2048/login?
• User agent url=http://www.wpunj.edu/scripts/webscript.exe?fs.scr
Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; .NET CLR 1.1.4322)
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6. MySQL operations
• EZProxy transactions would be stored in one
table with patron statistical categories, but
without the user ID.
• User ID s would be stored in another table
with counts for each service divided by
academic year.
• Logs are collected monthly and loaded and
deleted monthly.
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7. Perl Script for loading ezproxy log
use strict;
into MySQL
my
%month=(Jan=>'01',Feb=>'02',Mar=>'03',Apr=>'04',May=>'05',Jun=>'06',Jul=>'07',Aug=>'08'
,Sep=>'09',Oct=>'10',Nov=>'11',Dec=>'12');
while (<>){
my $pattern =
'^(S*) (S*) (S*) (S*) '.
'[(..)/(...)/(....):(..):(..):(..) .....]'.
' "(S*) (S*) (S*)" '.
'(d*) (-|d*) "([^"]*)" "([^"]*)"';
if (m/$pattern/){
my ($tgt,$ref,$agt) = (esc($12),esc($16),esc($17));
my $byt = $15 eq '_'?'NULL':$15;
print "INSERT INTO ezproxylogs VALUES ('$1','$2','$3',".
" TIMESTAMP '$7/$month{$6}/$5 $8:$9:$10','$11','$tgt',".
"'$13',$14,$byt,'$ref','$agt');r.";
}else{
print "--Skipped line $.n";
}
}
sub esc{
my ($p) = @_;
$p =~ s/'/''/g;
return $p; 7
}

8. Patron Statistical Categories
• Voyager Patron Database allows a maximum of 10
statistical categories per patron record.
• Weekly extract from SIS and HRS to load into
Voyager
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9. From Students
•College and Mercer Identifier
•Class Level (Freshman, Sophomore, Junior, Senior, Graduate)
•Total Hours Registered for Current Semester
•Major
•2nd Major
•Degree
•CA-Collection Agency
•SOILS
•Student Entrance Level (New Non-Traditional Freshman, New
First Time Transfer, etc.)
•Department

10. From Faculty / Staff / Adjuncts
•College
•Full or Part-Time
•Status (Faculty, Adjunct, Staff, Professional Staff, Tenured,
Tenure-Track)
•Division
•Departments

11. Extracting patron statistical categories back out
of Voyager and building them into MySQL
database.
Once completed, user ids are deleted.

13. Internal WPUNet IPv4 addressing scheme IP Network 149.151.
Block Description IP Block Start Range IP Block End Range
Admin (Services) 2.1 129.254
Labs (Users) 130.1 162.254
Admin (Users) 163.1 233.254
Resnet (Users) 234.1 250.254
Video 251.1 251.253

14. IP Address Location = 149.151.VlanID.*
Admin VLANs Labs VLANs
Vlan ID Vlan Name Vlan ID Vlan Name
2 Servers 3 Lab Servers
4 Admin 9 Imaging
5 Science 160 Lib Labs
6 Test Servers 174 STU VPN
7 NAS 175 Ben Shahn Lab
101 Energy Management 178 Hobart Lab
102 Diebold 179 SCI Lab
104 Xerox 187 CS Lab
150 Media Services 192 Atrium
161 Dorms Offices 209 Labs
162 RBI 212 Resnet Labs
163 Police 214 Raub Labs
164 Maintenance 228 VR Labs
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24. References
•Coombs, Karen A. (2005). Lessons learned from analyzing
library database usage data. Library Hi Tech, 23:4, 598.
• Diana, Birkin James. dashboard_beta.
http://library.brown.edu/dashboard/info/
• Metridoc. http://code.google.com/p/metridoc/
• Morton-Owens, Emily (2011) Trends at a glance. LITA 2011.
http://connect.ala.org/files/79651/trends_at_a_glance_dashb
oards_pdf_12068.pdf

25. Questions?
Ray Schwartz,
Systems Specialist Librarian
Cheng Library, William Paterson University,
Wayne, New Jersey, USA
schwartzr2 @ wpunj.edu
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