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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>An Applied Approach to Data Curation Training at the Inter-university Consortium for Political and Social Research (ICPSR)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Jared Lyle</string-name>
          <email>lyle@umich.edu</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Mary Vardigan</string-name>
          <email>vardigan@umich.edu</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Jacob Carlson</string-name>
          <email>jakecarlson@purdue.edu</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Ron Nakao</string-name>
          <email>ronbo@stanford.edu</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>ICPSR, University of Michigan Ann Arbor</institution>
          ,
          <addr-line>MI</addr-line>
          ,
          <country country="US">U.S.A</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Purdue University West Lafayette</institution>
          ,
          <addr-line>IN</addr-line>
          ,
          <country country="US">U.S.A</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Stanford University Stanford</institution>
          ,
          <addr-line>CA</addr-line>
          ,
          <country country="US">U.S.A</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>-ICPSR recently developed two new training initiatives in digital curation: a week-long applied data curation workshop where participants learn the theories and methods of data curation using the ICPSR “processing pipeline” as framework, and an ongoing virtual working group of data librarians that discusses similar core data curation topics while giving participants independent access to curate their own data using ICPSR's processing environment and tools. This paper discusses the background, structure, and lessons learned from these new training initiatives.</p>
      </abstract>
      <kwd-group>
        <kwd>Digital curation</kwd>
        <kwd>data curation</kwd>
        <kwd>training</kwd>
        <kwd>curriculum</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>I. OVERVIEW</title>
      <p>The Inter-university Consortium for Political and Social
Research (ICPSR), a research center in the Institute for Social
Research at the University of Michigan and the world’s largest
archive of social science data, recently developed two new
training initiatives in digital curation. The first initiative is a
week-long applied data curation workshop offered as part of the
ICPSR Summer Program in Quantitative Methods, where
participants learn the theories and methods of data curation using
the ICPSR “processing pipeline” as framework. The second
initiative is an ongoing virtual working group of data librarians
that discusses similar core data curation topics while giving
participants independent access to curate their own data using
ICPSR’s processing environment and tools. This paper discusses
the background, structure, and lessons learned from these new
training initiatives.</p>
    </sec>
    <sec id="sec-2">
      <title>II. DATA CURATION WORKSHOP</title>
      <p>As data multiply in sheer quantity and become increasingly
important in the research process, the demand for data curation
knowledge rises. What are the best practices for curating research
data? How does one apply them to daily practice? What tools
can assist in curation efforts? In 2011, ICPSR began planning a
data curation workshop to address these questions.</p>
      <p>The workshop was intended for individuals interested or
actively engaged in the management and curation of research
data, particularly data scientists, data managers and analysts,
librarians, archivists, and data stewards and curators. The initial
goal of the workshop was to “raise awareness about the benefits
of life cycle principles for data management, including how to
create, comply with, and evaluate required data management
plans, how to encourage and trace re-use, and how to manage
data from its inception through archiving and beyond.”</p>
      <p>We believed, and continue to feel, that ICPSR is uniquely
positioned to offer a course on data curation. First, ICPSR plays a
central role in many social science data curation standards and
activities, including serving as the home office for the Data
Documentation Initiative (DDI) and as a founding member of the
Data Preservation Alliance for the Social Sciences (Data-PASS).
DDI has become an international standard for metadata in the
social sciences. ICPSR and many other data archives use the DDI
XML to document information about the data in our repositories;
the ICPSR online catalog is also built on DDI metadata, allowing
structured searching across the entire repository at the
variableand even the value-level. Data-PASS is a voluntary partnership
of organizations created to archive, catalog, and preserve data
used for social science research. The Data-PASS partners
collaborate on best practices for data archiving and have a shared
digital preservation strategy.</p>
      <p>Second, ICPSR has established workflows for curating,
preserving, and providing access to data. These workflows,
described as the “ICPSR Pipeline Process” (Fig. 1), have been
developed and refined over 50 years of archiving more than
8,000 research collections from across all social science
disciplines, and are informed by the Reference Model for an
Open Archival Information System (OAIS) for the preservation
of digital objects as well as other community-based best
practices. The workflow segments, which are broken into
digestible portions, make it easier for students to follow and learn
curation processes.</p>
      <p>Third, ICPSR has an established Summer Program in
Quantitative Methods that offers more than 70 courses every
summer. The program provides an instructional infrastructure
readily accessible for curation instruction. For the past several
years, for instance, we have offered a course for data librarians
called “Providing Social Science Data Services: Strategies for
Design and Operation.” More recently, a course on confidential
data, “Assessment and Mitigation of Disclosure Risk in Data:
Essentials for Social Science,” was offered.</p>
      <p>Finally, ICPSR is committed to global leadership in the area
of digital curation, especially through instruction. Direction 1 of
the ICPSR Strategic Plan reads: “Through global leadership and
strong partnerships, set standards for excellence in data curation
and in the ethics of data access and protection for the social
sciences and related disciplines.” The ICPSR Council, which is
elected by the Consortium membership and provides overall
guidance, strongly encourages our participation in initiatives to
promote digital curation. We are eager to share our experience
and knowledge. We also recognize and appreciate the benefits
from the course: increased connection with front-line curators,
improved understanding of the needs and workflows of the
community, and new opportunities to influence the curation of
data further upstream in the data lifecycle (i.e., closer to the
original production of the data).</p>
      <p>The workshop, titled “Applied Data Science: Managing
Research Data for Re-Use,” was held July 23-27, 2012 in Ann
Arbor, Michigan. ICPSR teamed with the University of
Michigan School of Information to host the workshop. The core
instructors were Mary Vardigan and Jared Lyle from ICPSR,
Kathleen Fear from the UM School of Information, and Jake
Carlson from Purdue University.</p>
      <p>Twenty-five participants attended, representing diverse
institutions from the United States and Canada, as well as a range
of disciplines, including engineering, chemistry, physics, the
physical sciences, and the social sciences. Participants came to
the workshop with a wide variety of interests. Many participants
were interested in broad-based training. Others were establishing
or expanding their own repositories and needed “shovel ready”
plans for curating data. Still others came with very specific
questions in mind, such as how to manage confidential data or
how to address copyright questions.</p>
      <p>
        The workshop was grouped into five themed days that
followed an ICPSR dataset across the data life cycle through
creation, deposit, data processing, dissemination, preservation,
and reuse [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. Day 1 provided an overview of the research life
cycle stages and data curation. Day 2 covered data management
planning and acquisitions. Day 3 highlighted metadata. Day 4
covered data processing, confidential data management, and
repository requirements. Day 5 addressed dissemination,
preservation, and tracking reuse.
      </p>
      <p>Throughout the workshop, guest speakers provided insight on
a wide variety of curation topics, such as managing video data,
geospatial data, provenance, and repository assessment. Case
studies and hands-on curation activities designed to help
participants apply the material presented were woven throughout
the workshop. Examples of hands-on activities included creating
study- and variable-level metadata, reviewing unprocessed data
within Google Refine, and checking a dataset for confidentiality
issues.</p>
      <sec id="sec-2-1">
        <title>C. Lessons Learned</title>
        <p>Overall, the participants had very positive comments about
the workshop. Most rated it as “exceptional” or “above average”
when compared to other graduate level courses they have taken.</p>
        <p>Expertise, breadth of subject material, and applicability were
main strong points mentioned in the course evaluations. “This
workshop provided an insider’s view of the data curation
process,” wrote one participant, adding that “having presenters
that specialize in key parts of the process was very
valuable.” Another participant noted, “The ‘pipeline’ served as
an excellent framework.” Yet another appreciated “the hands-on
aspects of the course and the various print-based handouts.”</p>
        <p>As this was the first time this workshop was offered, we were
particularly active in gathering feedback. We surveyed the
participants at the end of each day of the course and applied the
feedback we received to adjust the course pace and content for
the subsequent days. At the end of the course, the Summer
Program also conducted an official, proctored evaluation. This
feedback now informs our future development. Some of the
shortcomings of the workshop that were identified, along with
plans to address them, include:</p>
        <p>1) Covering Too Much Content: While many participants
enjoyed the broad range of curation topics discussed, we also
heard comments like “Almost too much material...difficult to
digest in short space of time” and “Too many briefings that tried
to cover too much material in a short presentation.” We intend
to remedy this by discussing fewer topics but diving more
deeply. Instead of discussing, for instance, the many possible
data types in detail, leaving small chunks of time to each, we
intend to provide a quick but broad overview of the subject and
then spend quite a bit of time discussing the specifics of one or
two examples with hands-on activities.</p>
        <p>2) More Discussion and Collaboration: A few of our days
were especially long on lectures and short on discussion. We
wanted to impart as much of our knowledge as possible, along
with that of our invited experts. What the participants really
wanted was a mixture of learning from experts and discussion
among their peers. “Would have liked more opportunity to share
challenges/solutions with participants,” wrote one attendee.
Another said, “A forum for discussing individual situations,
problem-solving suggestions for next steps, etc. would be
helpful.” As a solution, we are building more discussion time
into the schedule, including structured thirty-minute blocks each
morning and afternoon and a longer lunch break. We are
exploring building peer-to-peer collaboration into the exercises
as well. We intend to better capitalize on the expertise and
knowledge that many workshop participants bring with them.</p>
        <p>3) Applied, Applied, Applied: Though we tried to pair applied
examples and exercises with each lecture, workshop participants
wanted more. Many participants mentioned there are quite a few
opportunities to learn about curation, but few chances for
handson active learning and interaction. While we feel applied
interaction is one of the strengths of our workshop, we are
looking to fine-tune the exercises that worked well and add
others.</p>
        <p>4) More Science in the Curriculum: As a social science data
archive, the curation material that we discussed naturally
emphasized methods and content from just one slice of the
research data spectrum. Our participants recognized the
applicability of social science data curation to all types and
formats of data, and we did include some examples from the
‘hard sciences.’ That said, the participants wanted to “cover a
wider array of data types and the unique management issues for
each.” While we will continue to highlight our own data and
methods from the social sciences, we can attempt to better
diversify the types of data covered in the exercises and
discussions. One option, for example, would be to offer
participants a choice of the types of data to work with during
exercises.</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>III.DATA CURATION WORKING GROUP</title>
      <p>Shortly before the start of the summer data curation
workshop, ICPSR discussed with Ron Nakao, Stanford
University, some possible mechanisms to provide more
handson, localized data curation training to librarians, especially the
Official Representatives at member institutions who assist
faculty, staff, and students with ICPSR resources. Many
librarians have limited experience with data management and
curation. In addition, as budgets are increasingly tightening,
librarians may not have the chance to travel for week-long
training. Even the more experienced data librarians do not have
the tools or resources that ICPSR can provide. Although multiple
venues exist to meet and discuss data curation topics -- from
listservs to conferences -- few opportunities arise for data
curators to engage in personalized but collaborative hands-on
work using the tools of an established domain repository.</p>
      <sec id="sec-3-1">
        <title>A. Background</title>
        <p>We proposed a virtual data curation working group where
participants would apply curation theories to practice through
actual data processing, interact with and ask questions of other
data specialists within a working environment, and gain
firsthand experience using ICPSR’s internal tools and procedures for
curation. The course would last approximately four months, with
one virtual meeting of 1 ½ hours approximately every other
week.</p>
        <p>ICPSR would benefit from the group as well. By opening our
processing environment and tools to outsiders, we would learn
more about the tools and services data librarians want and need,
and the suitability of expanding the use of ICPSR’s own curation
tools to a broader community. This interest coincides with our
work in an IMLS National Leadership Grant
(LG-05-09-008409) to investigate tools and services to assist librarians with
specialized tasks in the archiving and dissemination of social
science data. Another benefit of the working group would be that
more data would be curated and archived, benefiting the ICPSR
membership and the entire social science community.</p>
      </sec>
      <sec id="sec-3-2">
        <title>B. Structure</title>
        <p>The working group first met -- virtually -- in September 2012.
Participants hailed from Emory, Duke, UCLA, and UC Berkeley,
along with Jared Lyle from ICPSR as facilitator and Ron Nakao
as the chair. Participants received access to the ICPSR secure
processing environment and brought their own data to curate.
Biweekly discussions focused on topics similar to those found in
the summer data curation workshop: acquisition (gathering
information from the data producer, legal agreements, and
appraisal), review (quality and disclosure review), processing
(data cleaning, insuring data integrity, and quality checking),
metadata (standards, and variable- and study-level metadata),
dissemination (final packaging, delivery mechanisms), and
preservation (policies and actions).</p>
        <p>At this time, the working group is still active. Participants
have access to the ICPSR secure data processing environment
through September 2013.</p>
      </sec>
      <sec id="sec-3-3">
        <title>C. Lessons Learned</title>
        <p>As in the workshop, participants were generally excited to be
learning about and practicing data curation. “This was a fantastic
opportunity,” wrote one participant. “The most
useful/informative aspect has been applying the ICPSR’s
workflows and practices to an actual data collection and seeing
what’s involved in getting the data in sync with those workflows
and practices.”</p>
        <p>Since the group is ongoing, and since group members are still
processing and curating their data, we anticipate learning more
about the successes and challenges of this training format. In the
meantime, we offer a few in-progress lessons learned.</p>
        <p>5) Bring Your Own Data: All working group participants
brought their own data to process and curate. As a result, the
participants were highly invested and motivated; the questions
and discussions raised were timely and relevant rather than
purely theoretical.</p>
        <p>6) Hands-on Activities Were Key: Similar to bringing their
own data, hands-on activities using ICPSR’s processing
environment and tools helped the group members understand
and experience the core work of curation instead of just talking
through what can seem like generalized concepts. As one
participant mentioned, “...The real work was with going through
the data and documentation and seeing things like discrepancies
in variable names and the need to flesh out citations to make
them more informative. That was both interesting in its own
right and illuminating to provide a sense of what data curation
actually consists of in practice."</p>
        <p>7) Scheduling Issues: Virtual meetings have distinct benefits,
including saving time and money, and allowing participants to
practice methods and tools in between group discussions.
However, many in our group experienced one big drawback:
scheduling conflicts. As on member lamented, “I guess the only
real ‘problem’ with the group was that scheduling/timing issues
were such that we had to do a lot of the work during the
semester, when other demands on my time made it hard to focus
on the project in a sustained manner.” Another member
expressed similar frustration. “Unfortunately, my schedule
shifted pretty dramatically this semester, and it was often
difficult to fit in the call and prep work needed to make the call
most useful.” By not leaving their physical job work
environments, it was increasingly challenging for participants to
carve curation time away from the everyday job demands and
expectations.</p>
        <p>As part of ICPSR’s commitment to global leadership in the
area of digital curation, especially through instruction, we will
offer the data curation summer workshop again in July 2013.
Likewise, the data curation working group is running through
September 2013.</p>
        <p>We see continued demand by professionals to learn about
curation, especially through applied learning, and feel we can
play a role in helping educate the research and digital curation
community through teaching and discussing the curation
experiences and processes that have shaped our 50 years as a data
archive. As we do this, we recognize and appreciate the benefits:
increased connection with front-line curators, improved
understanding of the needs and workflows of the community, and
new opportunities to influence the curation of data further
upstream in the data lifecycle.</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>ACKNOWLEDGMENT</title>
      <p>We wish to acknowledge Nancy McGovern, ICPSR Digital
Preservation Officer from 2007-2012, who played a leading role
in developing the initial draft and goals of the workshop. We
thank the workshop and working group participants for their
feedback and participation. We also thank Dan Meisler for his
edits. IMLS National Leadership Grant (LG-05-09-0084-09)
supported data curation working group activities that identified
services to assist with archiving and disseminating social science
data.</p>
    </sec>
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</article>