Satisfaction with Data Reuse: Survey Results from Users of a Social Science Data Archive

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Satisfaction with Data Reuse: Survey Results from Users of a Social Science Data Archive

Society of American Archivists 2013 Research Forum

August 13, 2013

New Orleans, LA

Adam KriesbergPhD Candidate, University of Michigan School of Information

akriesbe [at] umich [dot] edu

Twitter: @DIPIR_Project


• An Institute for Museum and Library Services (IMLS) funded project led by Dr. Ixchel Faniel and Dr. Elizabeth Yakel.

• Studying data reuse in three academic disciplines to identify how contextual information about the data that supports reuse can best be created and preserved.

• Focuses on research data produced and used by quantitative social scientists, archaeologists, and zoologists.

• The intended audiences of this project are researchers who use secondary data and the digital curators, digital repository managers, data center staff, and others who collect, manage, and store digital information. For more information, please visit http://www.dipir.org

http://www.dipir.org/


DIPIR Project

Nancy McGovernICPSR/MIT

Ixchel FanielOCLC

Research (PI)

Eric Kansa Open

Context

William Fink UM

Museum of Zoology

Elizabeth Yakel

University of Michigan (Co-PI)

The Research Team


Methods Overview

ICSPR Open Context UMMZ

Phase 1: Project Start up

Interviews Staff

10 Winter 2011

4 Winter 2011

10 Spring 2011

Phase 2: Collecting and analyzing user data

Interviews data consumers

43 Winter 2012

22 Winter 2012

27 Fall 2012

Survey data consumers

2000 Summer 2012

Web analyticsdata consumers

Server logsOngoing

Observations data consumers

10Ongoing

Phase 3: Mapping significant properties as representation information


ICPSR Survey Objective and Structure

Research Question:

What contributes to data reuse satisfaction and intention to continue using ICPSR data among users of the repository?

Survey Structure: 3 Sections

1. Critical (Data Reuse) Incident Section• Asked about perceptions of data quality• Dependent variable: Satisfaction with data reuse experience

2. Repository Section• Asked about experiences using ICPSR• Dependent variable: Intention to continue using ICPSR

3. Demographics


ICPSR Survey Development and Administration

• Instrument Development• Adapted items from management and management

information systems literature (e.g. Flavian et al., 2006; Lee et al., 2002; Wang and Strong, 1996)

• Created new items

• Survey Sample• 1,632 first authors of journal articles from the ICPSR

Bibliography of Data-Related Literature 2008-2012

• Survey Administration (May – June 2012)• Approximate response rate 16% (usable surveys)


The Data Reusers

have contributed data to ICPSR12%

feel there is sufficient data available for reuse in their field62%

mean length of time respondents have been reusing data in research13 years

of research conducted by respondents relies on data collected by others

66%


Demographics: Data Sources Used During Research


Demographics: Data Integrators


Demographics: Job Titles

198 t

enure

track

facu

lty


Respondents: Academic Disciplines

SociologyMedicine/Public Health

EconomicsCriminology/Criminal Justice


A Closer Look: Satisfaction by Field


Differences in Satisfaction with the Data Reuse Experience

Pairs of FieldsMean

DifferenceStd. Error Sig.

Criminology/Criminal Justice (5.81)

& Sociology (6.47)-0.66087* 0.18556 0.013

Criminology/Criminal Justice (5.81)

& Medicine/Public Health (6.39)-0.57118* 0.18174 0.048

ANOVA Pairwise Comparisons

(* = significant at p < 0.05)


Scopus: Average Journal Ranking by Discipline

Academic Field Mean Ranking (SJR) nPsychology 1.52 16Education 1.46 3Political Science 1.56 5Economics 2.10 21Sociology 1.26 65Medicine/ Public Health (and allied fields) 1.48 71Criminology/ Criminal Justice 1.69 31Social Work 0.74 12Other 1.00 8Total 1.45 232


Discussion

These results represent a small part a larger survey, but what can they tell us?

• Different research communities report differing levels of data reuse satisfaction

• 41% combined data from multiple datasets during research• Consistency is key to facilitate this type of work

• 66% collect their own data, but only 12% contribute to ICPSR• Where are these data? How can repositories identify these

datasets?

Next Steps:• Conduct regression analysis to assess main predictors driving

satisfaction with data reuse


Acknowledgements

• Institute of Museum and Library Services • LG-06-10-0140-10

• PI: Ixchel Faniel, Ph.D., OCLC Research• Co-PI: Elizabeth Yakel, Ph.D., UMSI• Partners: Nancy McGovern, Ph.D. (MIT), Eric Kansa, Ph.D.

(Open Context), William Fink, Ph.D. (University of Michigan Museum of Zoology)

• Julianna Barrera-Gomez, OCLC Diversity Fellow• Students: Morgan Daniels, Rebecca Frank, Jessica

Schaengold, Gavin Strassel, Michele DeLia, Kathleen Fear, Mallory Hood, Molly Haig, Annelise Doll, Monique Lowe


Questions?

Adam Kriesberg

akriesbe [at] umich [dot] edu

@adamkriesberg

@DIPIR_Project


----- Additional Slides -----


Demographics: Data Source for the Critical Incident

Source Frequency Percent

ICPSR only 80 31.9%

Other source(s) 52 20.7%

ICPSR and other source(s) 110 43.8%

Do not remember 9 3.6%

n=251


A Closer Look: Satisfaction by Field

Field N Mean (Satisfaction)

Psychology 18 6.3611

Education 5 6.5000

Political Science 5 5.9000

Economics 22 6.3636

Sociology 66 6.4697

Medicine/Public Health (and allied fields)

75 6.3800

Criminology/Criminal Justice

34 5.8088

Social Work 13 6.3462

Other 8 5.8750

Total 246 6.2967

Satisfaction with Data Reuse: Survey Results from Users of a Social Science Data Archive

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