Through the Bytes Darkly Through the Bytes Darkly, Management Information and the Digital Library Joe Zucca Assessment, Planning and Publications Librarian University of Pennsylvania Library Information Technology Interest Group ACRL, New England Chapter
Through the Bytes Darkly,. Management Information and the Digital Library. Information Technology Interest Group ACRL, New England Chapter. Joe Zucca Assessment, Planning and Publications Librarian University of Pennsylvania Library. Four Sections of This Presentation:. - PowerPoint PPT Presentation
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Through the Bytes Darkly
Through the Bytes Darkly,
Management Information and the Digital Library
Joe ZuccaAssessment, Planning and Publications LibrarianUniversity of Pennsylvania Library
Information Technology Interest GroupACRL, New England Chapter
Through the Bytes Darkly
1. Environmental Audit: Key Factors That Influence Our Ability to Measure Digital Information Use
2. From Low Resolution to High Resolution Data: Mining the Server Logs
3. The Data Farm Experiment: Tools That Serve Access Can Also Serve Measurement
4. Why the Data Are Important
Four Sections of This Presentation:
Through the Bytes Darkly
Strategic Focus
Base planning, goal setting/assessment on empirical evidence. From 1996- an element of Penn’s Strategic Plan
Operational Imperatives
1) Make evaluation and measurement a component of each program and project
2) Construct relays that feed data to people who need quantitative information to strategize and manage
Experimental Attitude
Leverage the data you have; usually they’re “good enough” to validate organizational experience and knowledge
1. Organization and Culture
Measuring Electronic Use at Penn: Environmental Influences
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3 9 86
1394
2438
4932
6875
0
1000
2000
3000
4000
5000
6000
7000
1991 1993 1996 1999 2000 2001 2002
Num
ber
of T
itles
2. Proliferation of Electronic Resources
Article indexes, e-journals and other full-text resources
Measuring Electronic Use at Penn: Environmental Influences
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2.1. Growth of Expenditures for Electronic Resources
Measuring Electronic Use at Penn: Environmental Influences
Database & E-Journal Log-ins by Subject (based on log samples from FY2001)
Use of Licensed Resources
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On-Campus Depts50%
In-Library25%
Off-Campus15%
Campus Residences10%
Use of Licensed Resources
Where Do Our Clients Access Information?
Database Log-ins by Domain, FY2001
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Database Log-ins from Off Campus as a Percent of Total Log-ins, FY2001
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
SSWGSE
WHRT
NURSSAS
DENTL
GSFA
SEASASC
MED
LAW
ADM†
VET
On Campus
Off-Campus
School or Center
Use of Licensed Resources
Where Do Communities of Clients Work?
Pct
. of L
og-in
s
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When Are They Working?Use of Licensed Resources
Database Use by Time of Day, FY2001
0
5000
10000
15000
20000
25000
12
-1A
M
1-2
AM
2-3
AM
3-4
AM
4-5
AM
5-6
AM
6-7
AM
7-8
AM
8-9
AM
9-1
0 A
M
10
-11
AM
11
-12
AM
12
-1 P
M
1-2
PM
2-3
PM
3-4
PM
4-5
PM
5-6
PM
6-7
PM
7-8
PM
8-9
PM
9-1
0 P
M
10
-11
PM
11
-12
PM
Att
empt
ed L
ogon
s
In-Library Student Houses Schools Campus Modem Pool
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0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
12-1
AM
1-2
AM
2-3
AM
3-4
AM
4-5
AM
5-6
AM
6-7
AM
7-8
AM
8-9
AM
9-10
AM
10-1
1 A
M
11-1
2 A
M
12-1
PM
1-2
PM
2-3
PM
3-4
PM
4-5
PM
5-6
PM
6-7
PM
7-8
PM
8-9
PM
9-10
PM
10-1
1 P
M
11-1
2 P
M
Per
cen
t o
f T
ota
l Lo
go
ns
for
Eac
h H
ou
r
In-L ibrary Student Houses Schools Campus Modem Pool All Other (non-Penn domains)
The points on this line total 100% of logons for the hour 5-6 AM . In this example, "All Other Domains" accounted for 46.6% of attempted log-ons during the given hour.
Network Domains:
Use of Licensed Resources
How Does Audience Composition Change Through the Day?
Database Use by hour, FY2001
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The Data Farm Experiment: Tools That Serve Information Access Can Also Serve Measurement
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Schematic of the Data FarmAs of May 2002
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VoyagerDLXS
Server array
logs
Data Farm Processes
Scripts Server
Staff Client
Oracle
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Normalize the Data
Regularize the Migration of Logs from Production Machines
Manage the Storage
Maintain the Scripts
Standardize Processes: program modules, plug-in scripts
Optimize Usability
Perils of the MIS Prototype: Lessons Learned
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To Demonstrate Accountability:
Is the library spending the Schools’ money effectively? (Pressures of Penn’s responsibility center budget environment)
To Understand and Describe the Transfer of Technology:
Is the academic information universe a digital universe (as some at Penn believe)?
Is the digital universe more cost efficient than the paper one (as some at Penn believe)?
To Guide the Improvement of Existing and the Development of New Services
To Ensure the Successful Fulfillment of Our Mission
Why Are the Data Important?
“If you don’t know where you’re going, you’ll probably end up somewhere else” - Casey Stengel
Just a second quick note begging you, please, keep trying to look at those three databases!
Data farm usage logs indicate that one-quarter of all database logins from Annenberg IP addresses in 2001 were pointing to Academic Index (followed by Lexis-Nexis and PsycInfo, both with about 10-percent of all Annenberg database logins).
Also, 15-percent of all Academic Index school-based logins last year came from Annenberg IP addresses, more than from all schools except Arts and Sciences (at 30-percent).
Considering how much Annenberg people use the general database -- and you must know best how they can raise Holy Ned over the least change, I hope that you can find the time to check out the three candidate databases. I'm happy to come over and walk you through the log-in.
Through the Bytes Darkly
R2 = 0.2211
0
20
40
60
80
100
120
140
160
0 50 100 150 200 250 300
Lo
g-
ins
Reshelves
Journal of the American Chemical SocietyJournal of Organic ChemistryTetrahedron Letters
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Basic Search (262952) Guided Keyword Search (111710)Parameter Search Count Parameter FrequencyTitle 69498 Title 41389Author 51080 Keyword General 37256Journal Title 49437 Author 21725Subject 44592 ISSN [xxxx-xxxx] 17378Keyword 40727 Subject 11580Call Number 4905 ISBN 2422Prolific Author 776 Series Title 389Relevance Ranked 743 Publisher Name 334