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14 crowdsourcinggi
- 2. AGENDA
CROWDSOURCING AND SPATIAL DATA INFRASTRUCTURES
Background
Crowdsourcing Principles
Examples
Conclusions
© Manuel Ramos
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 2
- 3. BACKGROUND
THE ROLE OF GI
Geographic information (GI) was for generations produced and
consumed by professionals
Societal processes
land transfer,
planning and development,
risk management
…
that affect organisations and individuals.
Trend to develop mechanisms to bring GI closer to non-professional
users
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 3
- 4. BACKGROUND
MODERN TOOLS
Web 2.0
high interactivity,
sharing and collaboration,
Interoperability, and
real-time user-generated content
Web 2.0 apps
social networking,
blogging,
wikis,
video sharing, and
Mashups
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 4
- 5. BACKGROUND
WEB 2.0
The users’ role has changed
from looking for and retrieving content to active participation
© www.techscreens.com
everyone contributes to the common knowledge
of the group they interact with
Wikipedia, YouTube, Flickr, Wikimedia
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 5
- 6. CROWDSOURCING
WHY?
Organisations today have to operate in information-rich environments
They can no longer afford to rely entirely on their own ideas
They cannot bet their success to a single product to the market
Traditional development which largely focused on
intra-organisational skills,
closed off from outside ideas and technologies
is becoming obsolete
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 6
- 7. CROWD-WHAT?
Crowdsourcing
is the act of taking a job traditionally performed by a designated
agent (usually an employee) and outsourcing it to an undefined,
generally large group of people in the form of an open call.
Jeff Howe
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 7
- 8. CROW-WHAT?
The crowdsourcing approach
a recognised entity posts a problem online
a large number of individuals reacts
they provide a small part of the solution to the problem
solutions offered are exhaustive and not disjoint
This approach is popular because
web-based social technology makes it feasible & affordable to collect
data using groups of individuals
such data is often more accurate indicator of current conditions in the
real world than what can be obtained from data stored in databases
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 8
- 9. CROWDSOURCING PRINCIPLES
1. Formulate the problem properly
Scope & purpose
2. State deliverables concretely (quality)
let the crowd know exactly what is expected from them
leave space for their creativity
3. Connect with the right crowd
diversity (the question is answered from multiple points of view)
scientists or specialists and a significant number of hobbyists
with knowledge in the problem domain
4. Deploy the appropriate crowd management scheme
moderate discussion boards
post provocative challenges & publish milestones
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 9
- 10. EXAMPLES
Ushahidi
GeoNames
Geonode
Google MapMaker
OpenStreetMaps
Aim at providing open data through the
Creative Commons Attribution – ShareAlike license
data can be used freely and if you alter or build upon it,
you need to share those alterations back to the community
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 10
- 11. OPEN DATA
Data is considered to be open if
it is and publish online,
updated as often as possible,
provided in a way that allows for its legal use for any purpose, and
that allows easy processing with any arbitrary software program
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 11
- 12. OPENSTREETMAP
The OpenStreetMap project is a crowdsourced geospatial data
repository, with a global cast of volunteers.
With the mission to create a free editable dataset of the world
It has been very successful especially
In producing data fro places where it was very scarce
(rural & peri-urban areas)
In keeping up-to-date datasets of rapidly evolving urban areas
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 12
- 15. OPENSTREETMAP
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 15
- 19. SPATIAL DATASETS
CROWDSOURCING IMPACT
Lahore, Pakistan in Lahore, Pakistan in
Google Maps Google Maps
(before MapMaker) (after MapMaker)
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 19
- 21. USHAHIDI
HISTORY
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 21
- 24. USHAHIDI
EXPLOITATION
Disaster Response
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 24
- 25. USHAHIDI
EXAMPLES http://ushahidi.internewskenya.org/
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 25
- 26. USHAHIDI
EXAMPLES http://haiti.ushahidi.com/
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 26
- 27. CONCLUSIONS
CROWDS & SDI
Work on something relevant
(or at least has the promise of being useful relatively soon)
Put the users at the center
View users as important contributors
Give them responsibility
Enable ratings
Derive metadata from usage
Make customization as easy as possible
Enable mashups
Unlock the visualizations
Index your data and become searchable
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 27
- 28. CHALLENGES
RESEARCH ISSUES
Automatic validation an filtering of data inputs
Indirect geo-tagging (mining of social networks)
Automatic aggregation & summarizing of similar data entries
© Community FixIt
© Department of Geo-information Processing (GIP) – 27-Oct-2011 – 28