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Data Librarians Represent!

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Title: Data Librarians Represent!


1
Data Librarians Represent!
Integrating Data Services into the Social Science
Research Process
Lynda Kellam Data Services Government
Information Librarian University of North
Carolina at Greensboro lmkellam_at_uncg.edu
Katharin Peter Social Sciences Data
Librarian University of Southern
California kpeter_at_usc.edu
2
Data Librarians Represent!
Integrating Data Services into the Social Science
Research Process
  • The aim of this workshop is to begin an ongoing
    dialogue about incorporating data services and
    numeric resources into the social science
    research process.

L. Kellam, K. Peter May 2009
3
Workshop overview
  • Warm-up scenarios
  • What does integrating data services mean?
  • Who are your users?
  • Teaching
  • Data Users
  • Non-data users
  • Other librarians
  • Collaborations across campus

L. Kellam, K. Peter May 2009
4
Scenario 1
  • You have been invited as a guest speaker to a
    freshman seminar on national politics and current
    events. The professor casually requests that you
    just talk about polling data for 10-15 minutes.
    How would work within these limitations and what
    would you cover?

L. Kellam, K. Peter May 2009
5
Scenario 2
  • You are providing a 50-minute library research
    workshop for lower-level comparative politics
    students. The students assignment is to write a
    paper comparing two countries and you have been
    asked to instruct them on locating scholarly
    articles and primary sources. How might you also
    incorporate numeric sources into the larger
    workshop?

L. Kellam, K. Peter May 2009
6
Scenario 3
  • You have been asked to give a 30-minute
    presentation on available data sources at the
    all-day, new PhD student orientation for the
    Sociology Department. Students are wide-ranging
    in knowledge, ability and research interests.
    How would you outline your presentation so it
    would be appropriate for this audience?

L. Kellam, K. Peter May 2009
7
Scenario 4
  • Tired of last-minute grant proposal questions,
    you decide to offer a Data Resources and Tips
    for Faculty Writing Grant Proposals brown bag
    workshop. What might you include in this 45
    minute workshop/discussion? What specifically do
    you want the faculty to walk away knowing?

L. Kellam, K. Peter May 2009
8
Scenario 5
  • It is your turn to provide the monthly 1-hour
    lecture for reference providers at your library
    (including social science and non-social science
    librarians as well as paraprofessionals that
    staff the reference desk). Given the diverse
    computer and mathematical skill levels of your
    colleagues, what sources/concepts would you cover
    so that they could confidently field (or refer)
    statistical reference questions?

L. Kellam, K. Peter May 2009
9
Integrating Data Services
  • What is does this even mean?
  • Why is it important?

L. Kellam, K. Peter May 2009
10
Who are your users?
  • Who are the users on your campus?
  • What the problems/challenges do you have in
    working with those users?
  • How do you fit into their social science research
    process?

L. Kellam, K. Peter May 2009
11
Teaching Data users
  • Incorporating data search into larger literature
    review
  • http//www.hawaii.edu/edper/pdf/Vol37Iss2/Reflecti
    ons.pdf
  • Putting data in context

L. Kellam, K. Peter May 2009
12
Teaching Non-data users
  • Finding the story in the data
  • Stepping stones and gateway resources
  • Example Polling data and active-learning

L. Kellam, K. Peter May 2009
13
Finding the story in the data
Source World Development Indicators
L. Kellam, K. Peter May 2009
14
Stepping stones and gateway resources
Source EIU Country Reports
15
Source http//data.un.org
16
Source http//data.un.org
17
Polling data and active-learning
  • Example
  • What is a public opinion poll?
  • Can results be trusted?
  • How do you vet a polling statistic?
  • How are the results displayed?
  • For more information

L. Kellam, K. Peter May 2009
18
Polling data and active-learning (cont.)
Source Roper Center iPoll
19
Polling data and active-learning (cont.)
L. Kellam, K. Peter May 2009
20
Teaching Non-data users (cont.)
  • Try and get students to think about the topic
    beforehand.
  • Differentiate between walk away (knowledge) vs.
    take away (directions/tutorials).
  • How can data literacy and statistical literacy
    fit into small assignments or limited class time?

L. Kellam, K. Peter May 2009
21
Teaching Other librarians
  • Preparing non-social science librarians and staff
    for the reference desk.
  • Teaching advanced topics to interns.

L. Kellam, K. Peter May 2009
22
Source http//www.census.gov
23
Source http//www.census.gov
24
Teaching about the American Community Survey
Lets Play with Fact Sheets!
  1. Find a partner and work on the questions below
    together!
  2. Navigate to http//www.census.gov/
  3. On the left navigation click on American
    FactFinder
  4. Look up Winston-Salem, NC in the Fact Sheets and
    look through the data categories. Under which
    category would school enrollment appear?
  5. What is the estimate for total school enrollment
    for Winston-Salem, NC in the 2005-2007 ACS? What
    was it during the 2000 Census?

25
Source http//www.census.gov
26
Teaching about the American Community Survey
What are critical concepts?
  • Estimates
  • Sample is small and requires aggregation of data
    over time for smaller locations
  • Point in time versus period data
  • Counting on April 1 of census year versus
    counting continuously throughout year
  • Margins of error and confidence intervals
  • Figures are an estimate with a confidence
    interval of 90

L. Kellam, K. Peter May 2009
27
Teaching about the American Community Survey
Town B has 30,000 Three sets of 3 year estimates
(05-07, 06-08, 07-09) one 5 year estimate are
available
City C has 80,000 or more Five sets of 1 year
estimates, three sets of 3 year estimates and one
5 year estimate are available
Village A has 15,000 Only 5 year estimates
available (2005-2009)
28
Collaborations across campus
  • Course specific outreach.
  • Students collecting their own data for thesis.
  • Starting out with PhD cohorts.
  • How have you collaborated?

L. Kellam, K. Peter May 2009
29
What have we missed?
  • Undergraduate versus graduate students
  • Incorporating statistical literacy and data
    literacy
  • Active learning
  • Assessment
  • Other outreach ideas?

L. Kellam, K. Peter May 2009
30
Selected Bibliography
  • Jacobs, Jim. 1991. Providing data services for
    machine-readable information in an academic
    library Some Levels of Service. Public-Access
    Computer Systems Review 2(1) 144-160.
  • Mahoe, Rochelle. 2004. Reflections on the
    Dissertation Process and the Use of Secondary
    Data. Educational Perspectives, 37(2) 34-37.
  • Reed, Eleanor J. 2007. Data services in academic
    libraries Assessing needs and promoting
    services. Reference and User Services Quarterly,
    46(3) 61-73.
  • Stephenson, Elisabeth and Caravello, Patti
    Schifter. 2007.  Incorporating data literacy into
    undergraduate information literacy programs in
    the social sciences A pilot project. Reference
    Services Review, 35(4) 525-540.
  • See also
  • The 2004 special issue of IASSIST Quarterly
    28(2/3) devoted to Developing Statistical
    Literacy.

L. Kellam, K. Peter May 2009
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