shared print analysis - scelc board meeting
TRANSCRIPT
SCELC Board of Directors
OCLC Data
AnalysisJohn McDonald
CIO, Claremont University Consortium
February 8, 2013
SCELC’s Need for DATA• Nascent resource sharing program (CAMINO)
What can I get out of this if I join?
• Interest in shared print preservation program
What will I be obligated to keep if I join?
• Some have interest in closer collaborative collection
development
What can I stop buying or what else can I buy?
OCLC Data Analysis
• SCELC officially requested provision of print book
holdings from OCLC for a portion of its members
• 56 SCELC schools requested (50% of membership)
• Simple Data provided:
By OCLC Number
Holding Libraries by Symbol
OCLC Data Analysis
• 2.2 Million Books (or 2,190,464 to be exact)
• 5.5 Million Holdings (or 5,558,921 to be exact)
Data looks a little like this…
0
100,000
200,000
300,000
400,000
500,000
600,000C
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ter
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All
ian
t -
Irv
ine
Total Books Held, by Library
So what? What will the data tell us…
Who makes a good resource sharing partner?
Who makes a good shared print partner?
What traits can influence a Library to join a
program or start a partnership?
Who do is best to collaborate with on
collections in the future?
0%
5%
10%
15%
20%
25%
30%
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%
To
tal P
ort
ion o
f C
olle
ction
Unique across all Libraries
Fuller Theological Seminary, 100K
Caltech, 75K
Claremont, 180K
LMU, USF, Santa
Clara, 70-80K each
American Jewish
University, 50K
Occidental, 50K
Shared Print: Find Unique Holdings to Maximize Preservation
Shared Print: Find Overlap Holdings to Maximize Deselection
Bo
ok
s a
lso
held
by
Cla
rem
on
t
Shared Print: Find Overlap as a % of Collection
% o
f C
oll
ec
tio
n h
eld
by
Cla
rem
on
t
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
40% 50% 60% 70% 80% 90% 100%
LMU, USF, Santa
Clara, 200-250K each
To
tal P
ort
ion o
f C
olle
ction
Unique from Claremont
Fuller Theological
Seminary, 230K
Loma Linda, 120K
Biola, 135K
Caltech, 150K
Resource Sharing: Find Libraries Most Unlike Us
• Data has proven to be valuable in modeling collections
sharing, preserving, and collaboration potential
• Additional areas of analysis:
▫ Overlap and uniqueness by publication year and subject area (LC
Call Number)
▫ Paired and multiple modeled scenarios
• OCLC Data is just a snapshot in time (and already outdated)
• OCLC is hard to work with and can be expensive
Potential for this data
• Need data from members directly
▫ Simple data extraction should be easy and can be supplemented
by OCLC API
• Find appropriate permanent home for database
• Develop self-service tool with (close to) real time data
• Determine if new OCLC Collection Analysis tool will provide
the same or similar information
Next Steps