Zack Lane ReCAP Coordinator January 24, 2012 ReCAP Columbia University.

What’s Up With ReCAP?

Updates and Data Analysis

Zack LaneReCAP Coordinator

January 24, 2012

ReCAPColumbia University


Zack’s Ulterior Motives

Excuse to share

Find forum to share, examine, discuss and publish

Share what I do and how I do it

Review of ReCAP operations◦ Physical plant and new modules◦ Mellon Project◦ Websites

Data◦ Part 1: Why (bother) and how◦ Part 2: Boring data everybody’s seen followed by

amazing breakthrough◦ Part 3: New leads from Department presentations◦ Part 4: Trailblazing

Feedback!

Outline


9.4 million books CUL 3.9, NYPL 3.5, PUL

2.0 5 Modules complete 2 planned for

construction: Modules 8 & 9

CUL manages transfers with quotas

Tours conducted once or twice every year

ReCAP: Physical Plant


https://www1.columbia.edu/sec/cu/libraries/bts/recap/quotas.html

Columbia will occupy 5 aisles of new modules

NYPL plans to transfer 5.3 million books

Quotas will expand to 250,000 accessions per year (FY15)

ReCAP: Physical Plant


2 new modules 12 aisles each,

same length as aisle 5

Ground breaking in spring 2012, completed summer 2013

Wow

Mellon Project


Mellon Foundation grant to run for 12 months, April 2012 start

“From Discovery to Delivery”

Making all general collections at ReCAP available to partners

Impetus: NYPL’s 5.3 million transfers

Issues:◦ Collection

management◦ Collection

development◦ Technological

change◦ Governance◦ Policy◦ Cost-Sharing◦ Discover/Delivery

Mellon Project


Lizanne Payne, Planning Consultant

“Library Storage Facilities and the Future of Print Collections in North America,” 2007

Process:◦ Strategic planning◦ Holdings analysis◦ Policy changes◦ Cost analysis◦ Cost-sharing◦ Workflow and tech

requirements◦ Recommendations

http://csul.fcla.edu/sites/csul.fcla.edu/uploads/ss-oclc-storage-rept-11-02-07.pdf




New ReCAP Website!!


New ReCAP Website!


All data sets are publicly accessible

All ReCAP sites are publicly accessible

Squeaky wheels get the grease

New ReCAP Website



Data…always data What have we been looking at?

What else is there to look at?

What can it tell us?

What do we think it tells us?

How do we manipulate it?


Circulation Data Publicly available, all charges in Voyager

both on campus and offsite

Summer 2010 Internship: “Understanding the Effects of Policy Changes by Evaluating Circulation Activity Data at Columbia University Libraries” Serials Librarian, v.64:no.1, 2012.

Policy changes and user behavior

https://library.columbia.edu/bts/recap/data.html#circulation


13,326 14,951 17,615 21,383 25,083 28,029 27,524 28,73514,228

557,501 552,788

509,556

483,905

449,135 441,188 437,064415,987

207,069

0

100000

200000

300000

400000

500000

600000

FY03/04 FY04/05 FY05/06 FY06/07 FY07/08 FY08/09 FY09/10 FY10/11 FY11/12

CHARGES: Offsite vs. On Campus by Fiscal Year

Offsite On Campus


Zack’s Crystal Ball (extrapolation) Drop in total on campus charges: 399,208 Rise in total offsite charges: 29,282

◦ July-Dec = 51.87% of on campus, 48.59% of offsite)

User behavior: Faculty request offsite collections more and renew in greater proportion

Adaptation to technology takes time

Caveat: Causation is hard to prove


0

100000

200000

300000

400000

500000

600000


Circulation of ON CAMPUS Collections: Charges vs Renewals

On Campus - - - Sum of CHARGES On Campus - - - Sum of RENEWALS


0

5000

10000

15000

20000

25000

30000

35000

40000

45000


Circulation of OFFSITE Collections: Charges vs Renewals

Offsite - - - Sum of CHARGES Offsite - - - Sum of RENEWALS


0

2000

4000

6000

8000

10000

12000

FY03/04 FY04/05 FY05/06 FY06/07 FY07/08 FY08/09 FY09/10 FY10/11

RECALLS: OPAC vs Everywhere Else

OPAC Everywhere Else


To Analyze Data is to Suffer

Translating and defining

Quantity of data

Software/hardware limitations

Automation

Time


File types:◦ .txt◦ .xlsx◦ .accdb◦ .ppt and .pptx

Dynamic links Changeable

data sets Delicate

balance

Data Management


Circulation

Request Timing

TIME_SUM Calculation in Access


Critical F(x)s PivotTable/PivotChart

vlookup


Data: The Usual Suspects General categories Illustrate history of facility Lacks detail and nuance Provides big metrics we like Low hanging knowables

How can the data be mined?◦ Key: Accurate calculation of request rate


0

100000

200000

300000

400000

500000

600000

700000

800000

FY01/02 FY02/03 FY03/04 FY04/05 FY05/06 FY06/07 FY07/08 FY08/09 FY09/10 FY10/11 FY11/12

455,734

712,183

542,056

302,364

267,327

315,345

256,629

308,145

209,630183,324

83,479

System-wide Accessions by Fiscal Year

Load In Middle Phase Restrained


2,147

14,520

26,564

35,757

42,866

50,009

59,755

69,06071,119 71,582

34,536

0

10000

20000

30000

40000

50000

60000

70000

80000


System-wide Requests by Fiscal Year

Continuous Increase Level


0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

System-wide Requests by Hour

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

January February March April May June July August September October November December

System-wide Requests by Month



0

200

400

600

800

1000

1200

1400

1600

1800

200001

.01

01.0

901

.17

01.2

502

.02

02.1

002

.18

02.2

603

.05

03.1

303

.21

03.2

904

.06

04.1

404

.22

04.3

005

.08

05.1

605

.24

06.0

106

.09

06.1

706

.25

07.0

307

.11

07.1

907

.27

08.0

408

.12

08.2

008

.28

09.0

509

.13

09.2

109

.29

10.0

710

.15

10.2

310

.31

11.0

811

.16

11.2

412

.02

12.1

012

.18

12.2

6

System-wide Request by Calendar Day


Yawn Boring

“Zack, we know we know. Show us something new.”

Ok

Request rate calculated by “TIME_SUM” Item-by-Item analysis Allows focus on facets of bibliographic data Begin by looking again at what we’ve seen

before…

TIME_SUM Calculation in Access

Request Rate


Primary metric of collection use

Percent of collection requested per year

Target : 2.00% Target set to

estimate staffing and costs

2.06% as of January 2012

Does not include some staff, Google Book Project, Law, and other small outliers

Grotesque distinction between request and retrieval

Google Project is the Woodstock of ReCAP

What is the CUL Request Rate?



0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

16.00%

18.00%

20.00%

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Request Rate of Monographs by Publication Date:1991-2011


Request Rate by Publication Date Calculated for monographs with known

publication dates between 1850 and 2010 Volume of pre-1850 holdings is small in

comparison and considered outliers

1850-1990 : 1.74%1991-2011 : 6.73%

Increased overall rate attributed new acquisitions sent directly to ReCAP


0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

4.50%

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Request Rate of Serials by Publication Date: 1991-2011


0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

4.50%

1850

1854

1858

1862

1866

1870

1874

1878

1882

1886

1890

1894

1898

1902

1906

1910

1914

1918

1922

1926

1930

1934

1938

1942

1946

1950

1954

1958

1962

1966

1970

1974

1978

1982

1986

1990

1994

1998

2002

2006

2010

Request Rate of Serials by Publication Date: 1850-2011


Breakthrough Analyze any point in time, not just summary Calculate changing rates over time Faceted, item-by-item analysis

Combination of TIME_SUM and new formula

“Can the data get more specific?” Yes

Refined version of old news…


1.65%1.71%

1.79%1.84%

1.89%1.93%

1.99%2.06% 2.08% 2.08% 2.06%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%


Request Rate by Fiscal Year


0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%


Request Rate by Format

Monograph Serial Everything Else


Breakthrough Remember chart of request rate by

publication date?

It will always look the same - high rate for most recent publications

Conceptually, there is something else going on

Track the request rate of each publication date by fiscal year


0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

16.00%

18.00%

20.00%

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Request Rate of Monographs by Publication Date:1991-2011


0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

10.00%


Request Rates of 1991-2011 Imprints by Fiscal Year

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011


…lead to innovation

Examples:◦ Sciences: roll-out of subject analysis◦ Area Studies: focus on language, place of

publication and high use serials

Opportunities: ◦ Institutional knowledge◦ Variety of interest◦ Refining data

Department Presentations…


Request Rate by LC Class at Sciences Iterative process of refining reports and data

◦ Call number added July 2009

◦ Parsed call numbers added Nov. 2010

◦ LC/Non-LC (852 i1) added Jan. 2012

For Avery it was a mess Hard to analyze departments with non-LC

alphanumeric call numbers


B BF E G GC GF H HC HE HM HQ HV JK L LD P QA QC QE QK QM QR RA RC RM S SD SH T TC TE TJ TL TP TS V Z

Request Rate by LC Subject Heading

What is Area Studies? ◦ Oops, I didn’t exactly know (it’s not “Lehman”)

Language/subject based selection Focus on two CLIO locations:

◦ “Area Studies Collection” = off,glx and off,leh Pamela helped focus topic: language, high-

use titles and request rate New challenge: language codes

Area Studies and ReCAP



0

50000

100000

150000

200000

250000

300000

350000


Accession of Area Studies Collections


Avery6.4% Burke

4.7%Business

6.1%

Butler36.1%

East Asian13.1%

Engineering4.8%

Geology/Geoscience1.4%

Health Science

4.5%

Journalism0.0%

Lehman7.2%

Mathematics0.0%

Music2.6%

RBML4.3%

Sciences off,bio1.6%

Sciences off,che1.4%

Sciences off,phy

1.3% Sciences off,psy

0.8%

Sciences off,sci1.6%

Social Work1.1%

(blank) (blank)1.0%

System-wide Accession by Department

TOTAL : 1,482,420 / 181,195 (Request Rate 1.90%)

off,glx : 1,267,596 / 155,674 (1.81%) off,leh : 214,824 / 25,521 (2.74%)

Accessions / Requests by CLIO Location


“Libraries” consist of multiple CLIO locations (collections)

For several years there has been a steady decline for EDD requests

Likely due to e-access to current titles and purchase of backfiles

Individual patrons can have large effect on data (e.g. early 2009)

Pagination now required (August 2009) Patrons must have active borrowing

privileges to request EDD (August 2011)

EDD (Electronic Document Delivery)



0

100

200

300

400

500

600

700

800

3/1/

2002

6/1/

2002

9/1/

2002

12/1

/200

2

3/1/

2003

6/1/

2003

9/1/

2003

12/1

/200

3

3/1/

2004

6/1/

2004

9/1/

2004

12/1

/200

4

3/1/

2005

6/1/

2005

9/1/

2005

12/1

/200

5

3/1/

2006

6/1/

2006

9/1/

2006

12/1

/200

6

3/1/

2007

6/1/

2007

9/1/

2007

12/1

/200

7

3/1/

2008

6/1/

2008

9/1/

2008

12/1

/200

8

3/1/

2009

6/1/

2009

9/1/

2009

12/1

/200

9

3/1/

2010

6/1/

2010

9/1/

2010

12/1

/201

0

3/1/

2011

6/1/

2011

9/1/

2011

12/1

/201

1

Monthly EDD Requests:Health Sciences vs All Other Departments

All Other Departments HSL

A high-use title is any title that has been requested 5 or more times since accession

Includes both physical delivery and EDD Desire by staff to study high-use titles Initial purpose of ReCAP was to shelve low-

use collections Due to space need, selector decision and

patron trends, some titles may be considered higher- or high-use

Excludes: eng, fre, ger and ita

High-Use Titles at ReCAP


High(est) Use Titles: Area Studies


Monographs Serials


Analysis of HU Spanish Serials

0

20

40

60

80

100

120

140

160

180

200

High Use Spanish Language Serials in Area Studies by Month


Butler80.39%

Lehman8.96%

ILL8.28%

EDD1.25%

Everywhere Else1.13%

High Use Spanish Language Serials in Area Studies by Delivery Location

VIS2.27%

OFF10.54%

GRD33.22%

REG53.97%

High Use Spanish Language Serials in Area Studies by Patron Group

0

10

20

30

40

50

60

19

00

19

03

19

06

19

09

19

12

19

15

19

18

19

21

19

24

19

27

19

30

19

33

19

36

19

39

19

42

19

45

19

48

19

51

19

54

19

57

19

60

19

63

19

66

19

69

19

72

19

75

19

78

19

81

19

84

19

87

19

90

19

93

19

96

19

99

20

02

20

05

20

08

20

11

Distribution of HU spa Serials Requests by Publication Date


Compare to e-HLDGs

0

10

20

30

40

50

60

1900

1903

1906

1909

1912

1915

1918

1921

1924

1927

1930

1933

1936

1939

1942

1945

1948

1951

1954

1957

1960

1963

1966

1969

1972

1975

1978

1981

1984

1987

1990

1993

1996

1999

2002

2005

2008

2011

Distribution of HU spa Serials Requests by Publication Date


English78.3%

Spanish7.4%

French3.8%

Everything Else2.5%

Russian2.2%

German1.8%

Arabic1.3%

Italian1.0%

Portugese0.9%

Persian0.8%

Breakdown of Area Studies Requests by Language


More Data Needed

Language is good and can be tailored…but not the whole story

Place of publication important


Place of publication added Jan. 2012

Metadata must often be created to analyze

Will provide better data for decisions to Area Studies

But also creates new possibilities…

Place of Publication


Trailblazing This whole thing was actually leading

somewhere…

Impact of Mass Digitization Elements:

◦ Request rate over time◦ Faceted analysis◦ New facet: place of publication

New data and methods allow posing question: How has request rate of pre-1923 USA imprints changed over past 10 years?


0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%


Request Rate of Pre-1923 USA Imprints


0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

4.50%


Request Rate of USA Imprints by Era

Pre-1923 1923-1963 Post-1963


0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%

1.80%

2.00%


Request Rate of Foreign Imprints by Era

Pre-1923 1923-1963 Post-1963


Plato’s Cave

Every chart is a shadow on the cave wall – none the full picture and often difficult to discern

How can we pursue useful analysis?

How can results be shared?

More information about data sets can be found on the ReCAP Data Center

Primary data categories include: accession, retrieval, delivery and circulation

Tailored data sets and analysis will be provided to staff via the ReCAP Coordinator

Please see the main ReCAP website for general information about CUL procedures and systems

More Data Available


https://library.columbia.edu/bts/recap/data.html

https://library.columbia.edu/bts/recap/data.html

https://library.columbia.edu/bts/recap.html

https://library.columbia.edu/bts/recap.html

Zack Lane ReCAP Coordinator January 24, 2012 ReCAP Columbia University.

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