GIS Data Curation in Libraries

Preview:

DESCRIPTION

 

Citation preview

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.

Michael ElliotAssistant Professor of Biostatistics at SLU

Karen HogenboomNumeric and Spatial Data Librarian at UIUC

Cynthia HudsonDigital Data Outreach Librarian at WUSTL

Jennifer Moore GIS / Anthropology Librarian at WUSTL

Chris FreelandAssociate University Librarian at WUSTL

GIS in Libraries

(Karen)

Digital AssetsManagementSystems

(Chris)

Data Curation in Libraries(Cynthia)

Case Study in the

Research Lifecycle(Michael)

Curating GIS Data(Jennifer)

Discussion and

Questions

My Experience as a Public Health Faculty Member Using GIS DataMichael B. Elliott, Ph.D.

Assistant Professor

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

Obesity Trends* Among U.S. AdultsBRFSS, 1985

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14%

Obesity Trends* Among U.S. AdultsBRFSS, 1986

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14%

Obesity Trends* Among U.S. AdultsBRFSS, 1987

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14%

Obesity Trends* Among U.S. AdultsBRFSS, 1988

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14%

Obesity Trends* Among U.S. AdultsBRFSS, 1989

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14%

Obesity Trends* Among U.S. AdultsBRFSS, 1990

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14%

Obesity Trends* Among U.S. AdultsBRFSS, 1991

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19%

Obesity Trends* Among U.S. AdultsBRFSS, 1992

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19%

Obesity Trends* Among U.S. AdultsBRFSS, 1993

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19%

Obesity Trends* Among U.S. AdultsBRFSS, 1994

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19%

Obesity Trends* Among U.S. AdultsBRFSS, 1995

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19%

Obesity Trends* Among U.S. AdultsBRFSS, 1996

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19%

Obesity Trends* Among U.S. AdultsBRFSS, 1997

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% ≥20%

Obesity Trends* Among U.S. AdultsBRFSS, 1998

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% ≥20%

Obesity Trends* Among U.S. AdultsBRFSS, 1999

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% ≥20%

Obesity Trends* Among U.S. AdultsBRFSS, 2000

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% ≥20%

Obesity Trends* Among U.S. AdultsBRFSS, 2001

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

Obesity Trends* Among U.S. AdultsBRFSS, 2002

No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

Obesity Trends* Among U.S. AdultsBRFSS, 2003

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

Obesity Trends* Among U.S. AdultsBRFSS, 2004

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

Obesity Trends* Among U.S. AdultsBRFSS, 2005

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

Obesity Trends* Among U.S. AdultsBRFSS, 2006

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

Obesity Trends* Among U.S. AdultsBRFSS, 2007

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

Obesity Trends* Among U.S. AdultsBRFSS, 2008

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

Obesity Trends* Among U.S. AdultsBRFSS, 2009

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

Obesity Trends* Among U.S. AdultsBRFSS, 2010

(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

Prevalence* of Self-Reported Obesity Among U.S. AdultsBRFSS, 2011

*Prevalence reflects BRFSS methodological changes in 2011, and these estimates should not be compared to previous years.

15%–<20% 20%–<25% 25%–<30% 30%–<35% ≥35%

How I’ve used GIS data in my research Associate aspects of the neighborhood (built environment)

with behaviors and chronic disease (diabetes)

Start with diabetes mortality rate

Look at poverty status

Look at location of parks

Look at location of fast food chains

Look at location of convenience stores

Look at location of grocery stores

When You Put it all together

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

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

Where to store all this data?

What a mess!

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

Possibilities for the future…

Possibilities for the future…

GIS Services in Academic Libraries

Karen Hogenboom

Numeric and Spatial Data Librarian

University of Illinois at Urbana-Champaign

hogenboo@illinois.edu

Consultations with GIS Users

Finding data

Help with choosing or using software

Data management (and curation) Metadata Database design

Etc…

Providing Access to Data

Compilations of trusted sources http://www.library.illinois.edu/sc/datagis

Geo-portals: http://geodata.tufts.edu

Subscriptions to data sourcesSimplyMapSocial ExplorerGeolyticsSmall topical data sets (countrydata.com,

UNIDO Industrial Statistics)

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

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

Providing Access to Data

Compilations of trusted sources http://www.library.illinois.edu/sc/datagis

Geo-portals: http://geodata.tufts.edu

Subscriptions to data sourcesSimplyMapSocial ExplorerGeolyticsSmall topical data sets (countrydata.com,

UNIDO Industrial Statistics)

Providing Access to Data

Compilations of trusted sources http://www.library.illinois.edu/sc/datagis

Geo-portals: http://geodata.tufts.edu

Subscriptions to data sourcesSimplyMapSocial ExplorerGeolyticsSmall topical data sets (countrydata.com,

UNIDO Industrial Statistics)

(Geo)Data LiteracyData 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 Milo Schield, “Information Literacy, Statistical Literacy, and Data Literacy,” IASSIST Quarterly (Summer/Fall 2004): 7-11.

http://www.libguides.com

http://www.libguides.com

Accessing Academic Library GIS Services

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”

DCC Curation Lifecycle Model

http://www.dcc.ac.uk/resources/curation-lifecycle-model

CONCEPTUALIZE

CREATE OR RECEIVE

APPRAISE & SELECT

INGEST

PRESERVATION ACTION

STORE

ACCESS, USE & REUSE

TRANSFORM

GIS Data Curation: Challenges & PotentialJennifer Moore

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Cura

tion

Life

cycle fro

m th

e D

CC

http://

ww

w.d

cc.ac.u

k/reso

urces/cura

tion-life

cycle-mod

el

Curation Lifecycle Model as a Guide for GIS Data

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Provenance

Pho

to b

y S

ilve

r S

tack

htt

p://

ww

w.f

lickr

.co

m/p

ho

tos/

silv

ers

tack

/71

63

871

65

6/

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Collection?

Licensed?

Purchased?

Public Domain?

Two issues:

Who/when/how/where was it originally collected

Where/when/how did the researcher get it?

CREATE/RECIEVE

PRESERVE

STORE

Authoritative?

Quality?

Photo from

woodlyw

onder works http://w

ww

.flickr.com/photos/w

ww

orks/2222523486/

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

What does authoritative mean for GIS data?

Original, raw data?

Confirmed by localSources?

Centuries long problem for cartographers

Now there are many collectors of GIS data; some argue this makes the question of quality harder to answer

CREATE/RECEIVE

Derivatives

Versioning

Pho

to b

y Lu

z h

ttp://ww

w.flickr.co

m/p

ho

tos/luzb

onita

/235

32

271

40

/

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Derivatives

DerivativesDerivatives

Derivatives

AuthorityAccuracyCurrency

TRANSFORM

APPRAISE/SELECT

PRESERVE

ACCESS/REUSE

DiverseStructured Layered

NeedsAttribution

Pho

tos b

y Do

ug8

88

88 h

ttp://ww

w.flickr.co

m/p

ho

tos/do

ug8

88

88/3

22

035

70

81/

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Data Complexity

Pho

to b

y A

rtfo

rm C

an

ad

o h

ttp:

//w

ww

.flic

kr.c

om

/pho

tos/

art

form

/32

660

13

003

/

File sizeRobust

FormatsObsoleteProprietary Versatile

Best practicesNaming conventionsmetadata

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Data management

CONCEPTUALIZE

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarianmetadata

Data that informs us about the data. Necessary for data management, preservation and discovery.

Data curators say it is often a challenge that researchers do not accurately document their data.

But, researchers don’t want to learn a metadata standard to make the data useful; they just want to fill in a form.

metadata

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? - Dorothea Salo

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

ISO 19115? Geographic Markup Language (GML)?

Pho

to b

y D

avew

ing6

8 ht

tp:/

/ww

w.f

lickr

.com

/pho

tos/

dave

win

g68/

2834

1438

54/

Data Access and Support

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

ACCESS/REUSE

CONCEPUTALIZATION

Good Examples

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

http://cugir.mannlib.cornell.edu/ http://inside.uidaho.edu/

http://www.geomapp.net/

Steps Forward

Jennifer Moore | GIS Outreach & Anthropology Librarian | Washington University Libraries | j.moore@wustl.edu | @anthrolibrarian

Create a Geospatial Data Collection Policy (model

NGDA)

Anticipate the difficulties of geospatial data curation

Foster culture of data best practices

Develop relationship with other institutions

Establish GeoPortal with OAIS standard guidelines

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

GIS & Digital Asset Management Systems (DAMS)Chris Freeland

Associate University Librarian

Twitter: @chrisfreeland

What is a Digital Asset Management System? Combination of hardware & software used to store and

access digital objects Documents Images / Photos Video Audio Datasets

SANDB

DAMS

Metadata Files

UIs / APIs:• Add/Edit/Delete• Access control

Kinds of DAMS

Enterprise

Institutional

Personal

Connecting GIS & DAMS

…little to no native support, requires custom programming

Putting it all togetherTropicos: http://www.tropicos.orgMissouri 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

ArcGIS API for JavaScript

SQL Server

djatoka

ArcGIS Server Fedora Commons

Images

ASP.NET (C#)

File System

DB

App

UI / API

MySQLSpatial Data Image Metadata

GIS DAMS

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

GIS in Libraries

(Karen)

Digital AssetsManagementSystems

(Chris)

Data Curation in Libraries(Cynthia)

Case Study in the

Research Lifecycle(Michael)

Curating GIS Data(Jennifer)

Discussion and

Questions

Thank you!

Recommended