sotm us 2010 (nama r. budhathoki)
TRANSCRIPT
Who map in OpenStreetMap
and Why?
Nama Budhathoki, McGill University
Muki Haklay, University College London
Zorica Nedovic-Budic, University College Dublin
State of the Map 2010– Atlanta, USA, 14-15 August, 2010
Looked from the traditional mode of
production, it is a puzzle (Benkler
2005, 2006)
Understanding this question lies at the
heart of the science of volunteered
geographic information (Goodchild 2007)
Research questions
•Who are those mappers?
•Why do they map?
•What contributory pattern do mappers
demonstrate?
Theoretical framework for VGI
motivational study
• Unique ethos
• Learning
• Fun
• Instrumentality
• Recreation
• Meeting self need
• Altruism
• Recognition
• Career
• Reciprocity
• Community
• Monetary
• Socio-political
• More………...
Clary et al. (1998), Clary and Synder (1999); Stebbins (1982), Gould et al. (2008);
Wasko and Faraj (2005), Lee et al. (2008), Hertel et al. (2003), Shah (2006), Hippel
and Krogh (2003), Nov (2007),
Methodology
• Analysis of Planet.OSM to identify
patterns of contribution
• Qualitative analysis of talk-pages
• Survey of globally distributed contributors
Who are the mappers?
Male(96%)
Female(3%)
N=426
Below 20 years(4%)
20-30 years(32%)
31-40 years(32%)
41-50 years(22%)
Above 50 years
(10%)
High School or
lower(5%)
Some College(17%)
College/ University
degree(49%)
Post-graduate degree(21%)
Doctoral degree(8%)
<1 year(26%)
1-5 years(15%)
6-10 years(7%)
>10 years(3%)
None(49%)
Gender Age
Education GIS Experience
Student(17%)
Employed
(63%)
Retired (2%)
Self
employed
(15%)
Other(3%)
Commercial(71%)Academia
(11%)
Federal govt.(7%)
Local govt.(6%)
Non-profit(2%)
Other(3%)
Place In percent (%)
Home 96
Office 18
Mobile 13
Public libraries 0
Internet cafes 0.3
Others 0.6
Occupation Employment
Being an author of books which are using maps, I am not
able to pay royalty fees to map companies like google or
teleatlas.
It's a lot of fun, and it's nice to see your work appear 1-2
hours after it's done available to the whole world :)
I love to see the area around where I live accurately mapped
(and updated in a timely manner). I get enormous
satisfaction out of this entire process as well as know that
I'm contributing towards a valuable resource that others
can use. I also enjoying exploring on my bike new areas
that I'm mapping - I've discovered some cool suburban
places that I never new existed - often within meters of
roads that I drive down regularly.
Motivations
Perceived Motivations
Motivational construct Mean SD
Project goal 6.14 .77
Altruism 5.73 .83
Instrumentality of local knowledge 5.58 .81
Learning 5.29 .95
Self need 5.2 1.19
Social/Show off 4.04 1.00
Monetary 2.14 1.06
Difference in perceived motivations between
serious & casual mappers
Hypothesis Development
Motivational Factors
H3: Local knowledge
H2: Altruism
H1: Project goal
H4: Learning
H5: Self need
H6: Show-off
H7: Monetary
H8: Mapping party
Node
Longevity
Frequency
Contribution
Contributory Pattern (Europe)
0
100000
200000
300000
400000
500000
600000
0 100 200 300 400 500 600
No.
of
Nod
es
No. of Days
Contributory Pattern (Africa)
0
5000
10000
15000
20000
25000
0 20 40 60 80 100
No.
of N
odes
No. of Days
Contributory Pattern (Asia)
0
50000
100000
150000
200000
250000
0 100 200 300 400
No.
of
Nod
es
No. of Days
Contributory Pattern (North America)
0
50000
100000
150000
200000
250000
300000
350000
400000
0 50 100 150 200 250 300
No.
of
Nod
es
No. of Days
Contributory Pattern (South America)
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
0 20 40 60 80 100 120
No.
of
Nod
es
No. of Days
Contributory pattern in OSM
Registered users
117,000
Mappers
33,452 (29%)
Non-mappers
83,548 (71%)
34
• 44% are one-timers
• 5% have contributed more than 10,000 nodes
• 0.6% have contributed more than 100,000 nodes
Source: www.openstreetmap.org , downloaded from http://downloads.cloudmade.com/(Accessed on April, 2009)
Continent level
0
10
20
30
40
50
60
70
80
Africa Asia Europe North America
South America
Map
pers
(i
n %
)
One-time contributors >100 Node>1000 Node >10000 Node>100000 Node
Main hypotheses Sig value (Pillai’s
trace)
Sub-hypotheses Unstandardized
parameter estimates
Sig-value
H1: Project goal 0.030* Node (H1a) -0.615 0.012*
Longevity (H1b) -0.328 0.093
Frequency(H1c) -0.362 0.005*
H2: Altruism 0.080 Node (H2a) -0.440 0.049*
Longevity(H2b) -0.072 0.689
Frequency(H2c) -0.206 0.080
H3: Instrumentality
of local knowledge
0.000* Node(H3a) 2.011 0.000*
Longevity(H3b) 1.275 0.000*
Frequency(H3c) 1.038 0.000*
H4: Learning 0.877 Node(H4a) 0.054 0.794
Longevity(H4b) -0.064 0.697
Frequency(H4c) 0.001 0.995
H5: Self need 0.977 Node(H5a) 0.022 0.868
Longevity(H5b) -0.009 0.936
Frequency(H5c) 0.015 0.837
H6: Show off 0.454 Node(H6a) -0.263 0.180
Longevity(H6b) -0.215 0.171
Frequency(H6c) -0.105 0.311
H7: Monetary 0.724 Node(H7a) 0.097 0.593
Longevity(H7b) -0.033 0.822
Frequency(H7c) 0.046 0.633
H8: Mapping party 0.486 Node(H8a) 0.710 0.242
Longevity(H8b) 0.029 0.953
Frequency(H8c) 0.239 0.454
Hypothesis Testing
Motivations Sig. Value
Monetary 0.035*
Learning 0.922
Instrumentality of local knowledge 0.008*
Project Goal 0.574
Altruism 0.200
Show-off 0.110
Self need 0.625
Community importance 0.622
Identity 0.595
Self view 0.012*
Socio-political agenda 0.794
Serious mappers
7.3% 12.1%
75.6%
5%0
10
20
30
40
50
60
70
80
It will increase my
contribution
I will decrease my
contribution
It will not affect my
contribution
I will stop
contributing
How will the involvement of commercial companies affect your contribution to the
project?
Summary and implications
• Instrumentality of Local knowledge as a
key motivator of contribution
• Representation of local area
• Accuracy of map
• Self efficacy
• Fun
• Those who have higher monetary
motivation, local knowledge, and self view are
likely to be serious mappers.
• Why cann’t those with other motivations can’t
make good contribution?
• Learning materials
• Ease of use of the system
• Social network
Summary and implications
Feel free to contact me for more information:
http://budhathoki.wordpress.com
Thanks for listening!