1. GIS Data Curation in
Libraries
A panel will explore the future of GIS data curation in libraries.
Speakers will address traditional ways libraries incorporate GIS
services, how researchers use GIS data through the life cycle & finally
the potential/challenge of GIS data curation.

2. Michael Elliot
Assistant Professor of Biostatistics at SLU
Karen Hogenboom
Numeric and Spatial Data Librarian at UIUC
Cynthia Hudson
Digital Data Outreach Librarian at WUSTL
Jennifer Moore
GIS / Anthropology Librarian at WUSTL
Chris Freeland
Associate University Librarian at WUSTL

3. Case Study
Data Digital
in the
Curation in Assets
Research
Libraries Management
Lifecycle
(Michael)
(Cynthia) Systems
(Chris)
GIS in Curating Discussion
Libraries GIS Data and
(Karen) (Jennifer) Questions

4. My Experience as a Public Health Faculty Member Using
GIS Data
Michael B. Elliott, Ph.D.
Assistant Professor

5. Public Health has a long history with spatial
data: 19th century London John Snow

6. Obesity Trends* Among U.S. Adults
BRFSS, 1985 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%

7. Obesity Trends* Among U.S. Adults
BRFSS, 1986 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%

8. Obesity Trends* Among U.S. Adults
BRFSS, 1987 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4”
person)
No Data <10% 10%–14%

9. Obesity Trends* Among U.S. Adults
BRFSS, 1988 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%

10. Obesity Trends* Among U.S. Adults
BRFSS, 1989 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%

11. Obesity Trends* Among U.S. Adults
BRFSS, 1990 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%

12. Obesity Trends* Among U.S. Adults
BRFSS, 1991 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%

13. Obesity Trends* Among U.S. Adults
BRFSS, 1992 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%

14. Obesity Trends* Among U.S. Adults
BRFSS, 1993 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%

15. Obesity Trends* Among U.S. Adults
BRFSS, 1994 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%

16. Obesity Trends* Among U.S. Adults
BRFSS, 1995 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%

17. Obesity Trends* Among U.S. Adults
BRFSS, 1996 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19%

18. Obesity Trends* Among U.S. Adults
BRFSS, 1997 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%

19. Obesity Trends* Among U.S. Adults
BRFSS, 1998 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%

20. Obesity Trends* Among U.S. Adults
BRFSS, 1999 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%

21. Obesity Trends* Among U.S. Adults
BRFSS, 2000 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% ≥20%

22. Obesity Trends* Among U.S. Adults
BRFSS, 2001 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

23. Obesity Trends* Among U.S. Adults
BRFSS, 2002
(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

24. Obesity Trends* Among U.S. Adults
BRFSS, 2003 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

25. Obesity Trends* Among U.S. Adults
BRFSS, 2004 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

26. Obesity Trends* Among U.S. Adults
BRFSS, 2005 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

27. Obesity Trends* Among U.S. Adults
BRFSS, 2006 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

28. Obesity Trends* Among U.S. Adults
BRFSS, 2007 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

29. Obesity Trends* Among U.S. Adults
BRFSS, 2008 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

30. Obesity Trends* Among U.S. Adults
BRFSS, 2009 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

31. Obesity Trends* Among U.S. Adults
BRFSS, 2010 (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

33. How I’ve used GIS data in my
research
 Associate aspects of the neighborhood (built environment)
with behaviors and chronic disease (diabetes)

34. Start with diabetes mortality rate

35. Look at poverty status

36. Look at location of parks

37. Look at location of fast food chains

38. Look at location of convenience stores

39. Look at location of grocery stores

40. When You Put it all together

41. What takes the most time?
 Finding data
 Modifying / Limiting shape files
 Re-finding data

42. Where do I try to find my data?
 Census Bureau
 MSDIS (Missouri Spatial Data Information Service)
 City/County Departments of Planning
 CDC
 Various pay sources

43. Where to store all this data?

44. What a mess!

45. Problems
 Trying to locate where I stored files for different projects
 Trying to remember what I named the files (especially when I accepted
ArcMap’s default names)
 Trying to remember how I changed the files
 Concerns about quality of the files
 Lack of access to colleagues files across
department, college, university, (city? Etc.)
 Lack of normalization of shape file projections
 Lack of metadata
 Disrupted linkages if switching computers or changing file structure or
updating software
 Using Dropbox as a collaborative temporary solution does not fix
problem

46. Possibilities for the future…

47. Possibilities for the future…

48. GIS
Services in
Academic
Libraries
Karen Hogenboom
Numeric and Spatial Data
Librarian
University of Illinois at
Urbana-Champaign
hogenboo@illinois.edu

49. Consultations with GIS Users
 Finding data
 Help with choosing or using software
 Data management (and curation)
 Metadata
 Database design
 Etc…

50. Providing Access to Data
 Compilations of trusted sources
http://www.library.illinois.edu/sc/datagis
 Geo-portals: http://geodata.tufts.edu
 Subscriptions to data sources
 SimplyMap
 Social Explorer
 Geolytics
 Small topical data sets
(countrydata.com, UNIDO Industrial Statistics)

51. http://www.library.illinois.edu/sc/datagis

52. http://www.library.illinois.edu/sc/datagis

53. Providing Access to Data
 Compilations of trusted sources
http://www.library.illinois.edu/sc/datagis
 Geo-portals: http://geodata.tufts.edu
 Subscriptions to data sources
 SimplyMap
 Social Explorer
 Geolytics
 Small topical data sets
(countrydata.com, UNIDO Industrial Statistics)

54. geodata.tufts.edu

55. geodata.tufts.edu

56. geodata.tufts.edu

57. Providing Access to Data
 Compilations of trusted sources
http://www.library.illinois.edu/sc/datagis
 Geo-portals: http://geodata.tufts.edu
 Subscriptions to data sources
 SimplyMap
 Social Explorer
 Geolytics
 Small topical data sets
(countrydata.com, UNIDO Industrial Statistics)

58. (Geo)Data Literacy
 Data literate students must “be able to
access, assess, manipulate, summarize, and
present data.”1
 Workshops (geographic concepts and software, finding
data)
 Sessions with classes/groups
 Online guides: http://libguides.com
1 MiloSchield, “Information Literacy, Statistical Literacy, and Data
Literacy,” IASSIST Quarterly (Summer/Fall 2004): 7-11.

59. http://www.libguides.com

60. http://www.libguides.com

61. Accessing Academic Library
GIS Services

62. Data Curation in Libraries
 The model and existing tools to get you there...
Cynthia Hudson
Digital Data Outreach Librarian
Washington University in St. Louis
Adapted from: Dorothea Salo “Librarians love data”

63. DCC Curation Lifecycle Model
http://www.dcc.ac.uk/resour
ces/curation-lifecycle-model

64. CONCEPTUALIZE

65. CREATE OR RECEIVE

66. APPRAISE & SELECT

67. INGEST

68. PRESERVATION ACTION

69. STORE

70. ACCESS, USE & REUSE

71. TRANSFORM

72. GIS Data Curation:
Challenges & Potential
Jennifer Moore
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

73. Curation Lifecycle Model as a Guide for GIS Data
http://www.dcc.ac.uk/resources/curation-lifecycle-model
Curation Lifecycle from the DCC
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

74. Provenance
Photo by Silver Stack http://www.flickr.com/photos/silverstack/7163871656/
Two issues:
Who/when/how/where Collection?
was it originally
collected Licensed?
Where/when/how did Purchased?
the researcher get it?
Public Domain?
CREATE/RECIEVE
PRESERVE
STORE
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

75. Authoritative?
What does
authoritative mean
Photo from woodlywonder works http://www.flickr.com/photos/wwworks/2222523486/
for GIS data?
Original, raw data?
Confirmed by local
Sources?
Quality?
Centuries long
problem for
cartographers
Now there are
many collectors of
GIS data; some
argue this makes
the question of
CREATE/RECEIVE
quality harder to
answer
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

76. Derivatives
Derivatives
Derivatives
Derivatives Derivatives
http://www.flickr.com/photos/luzbonita/2353227140/
Photo by Luz
Authority
Accuracy
Currency
APPRAISE/SELECT
PRESERVE
TRANSFORM Versioning
ACCESS/REUSE
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

77. Data Complexity
Photos by Doug88888 http://www.flickr.com/photos/doug88888/3220357081/
Diverse
Structured
Layered
Needs
Attribution
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

78. Data management
File size
Robust
Photo by Artform Canado http://www.flickr.com/photos/artform/3266013003/
Formats
Obsolete
Proprietary
Versatile
Best practices
Naming conventions
metadata
CONCEPTUALIZE
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

79. Data that informs us about the data.
Necessary for data
management, preservation and
discovery.
Data curators
say it is often a
challenge that But, researchers don’t want
researchers do to learn a metadata standard
not accurately to make the data useful; they
document their just want to fill in a form.
data.
metadata
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

80. FGDC metadata.
I mean, really.
FGDC is RIDICULOUSLY
complex, and tool support for it is
therefore nonexistent. Who thought
this would work, and have they been
fired yet?
metadata
- Dorothea Salo
ISO 19115? Geographic Markup Language (GML)?
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

81. Photo by Davewing68 http://www.flickr.com/photos/davewing68/2834143854/
CONCEPUTALIZATION
Data Access and Support
ACCESS/REUSE
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

82. Good Examples
http://cugir.mannlib.cornell.edu/
http://inside.uidaho.edu/
http://www.geomapp.net/
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

83. Steps Forward
Create a Geospatial
Data Collection
Policy (model NGDA)
Develop
relationship with
other institutions
Establish GeoPortal with
OAIS standard guidelines
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

84. Bibliography
Bethune, Alec, Butch Lazorchak, and Zsolt Nagy. 2009. “GeoMAPP: A Geospatial Multistate Archive and Preservation
Partnership.” Journal of Map & Geography Libraries 6 (1): 45–56. doi:10.1080/15420350903432630.
Bose, Rajendra, and Femke Reitsma. 2006. “Advancing Geospatial Data Curation.”
http://www.era.lib.ed.ac.uk/handle/1842/1074.
Downs, Robert R., and Robert S. Chen. "Organizational needs for managing and preserving geospatial data and related
electronic records." Data Science Journal 4, no. 0 (2005): 255-271.
Erwin, Tracey, and Julie Sweetkind-Singer. 2009. “The National Geospatial Digital Archive: A Collaborative Project to Archive
Geospatial Data.” Journal of Map & Geography Libraries 6 (1): 6–25. doi:10.1080/15420350903432440.
Gold, Anna K. "Cyberinfrastructure, data, and libraries, part 2: Libraries and the data challenge: Roles and actions for libraries."
Office of the Dean (Library) (2007): 17.
Jenkins, Keith. 2013. “Expert Feedback on Geospatial Data Curation.” http://guides.library.cornell.edu/profile.php?uid=1097
Kenyon, Jeremy. 2012. “Geospatial Data Curation at the University of Idaho.”Journal of Web Librarianship 6 (4): 251–262.
Salo, Dorothea. 2013. “Expert Feedback on Geospatial Data Curation.” http://dsalo.info/
Shaon, Arif, and Andrew Woolf. 2011. “Long-term Preservation for Spatial Data Infrastructures: a Metadata Framework and
Geo-portal Implementation.” D-Lib Magazine 17 (9): 1–.
Steinhart, Gail. 2006. “Libraries as Distributors of Geospatial Data: Data Management Policies as Tools for Managing
Partnerships.” Edited by Gail Steinhart. Library Trends 55 (2): 264–284.
Stonltenberg, Jaime. 2013. “Expert Feedback on Geospatial Data Curation.” http://www.library.wisc.edu/directory/staff/Jaime-
Stoltenberg
Sweetkind, Julie, Mary Lynette Larsgaard, and Tracey Erwin. 2006. “Digital Preservation of Geospatial Data.” Library Trends
55 (2): 304–314.
Xia, Jingfeng. 2012. “Metrics to Measure Open Geospatial Data Quality.” Issues in Science & Technology Librarianship (68): 7.
Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

85. GIS & Digital Asset
Management Systems
(DAMS)
Chris Freeland
Associate University Librarian
Twitter: @chrisfreeland

86. What is a Digital Asset
Management System?
 Combination of hardware & software used to store and
access digital objects
 Documents
 Images / Photos
 Video
 Audio
 Datasets

87. UIs / APIs:
DAMS • Add/Edit/Delete
• Access control
Metadata Files
DB SAN

88. Kinds of DAMS
Enterprise
Institutional
Personal

89. Connecting GIS & DAMS
…little to no native support, requires custom programming

90. Putting it all together
Tropicos: http://www.tropicos.org
Missouri Botanical Garden’s
botanical information system
 4 million+ specimen records
 1.2 million plant names
 98,000 collectors / authors
 140,000 images
Maps via ESRI tools & other technologies…
 ArcIMS in 2000, only recently taken offline
 ArcGIS Server 9.3 & JavaScript API in 2010
Digital Asset Management via Fedora Commons

98. UI / API
ASP.NET (C#)
ArcGIS API for JavaScript
App
ArcGIS Server Fedora Commons
djatoka
DB
Spatial Data MySQL Image Metadata
SQL Server
File System
Images
GIS DAMS

99. GIS & DAMS: Conclusions
 Libraries have invested in DAMS for media storage &
delivery
 Opportunities for use with custom GIS apps, but requires
customization / tradeoffs
 It DOES work
 It IS NOT simple
 Move towards community-supported research data portals
will probably win

100. Case Study
Data Digital
in the
Curation in Assets
Research
Libraries Management
Lifecycle
(Michael)
(Cynthia) Systems
(Chris)
GIS in Curating Discussion
Libraries GIS Data and
(Karen) (Jennifer) Questions
Thank you!