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UrbanGames
Irene Celino, Dario Cerizza, Simone Contessa, Marta Corubolo, Daniele Dell'Aglio,
Emanuele Della Valle, Stefano Fumeo, Federico Piccinini
December 12th, 2012, Luxembourg
Slide 2 of 25
UrbanGames - Motivation
Urban Computing and Location-based Services
Linked Data and Semantic Web
Games with a Purpose and
Crowdsourcing
Urban Games
citizens as sensors, check-in logging, mobile apps
collecting data, cleaning data, engaging the user, supporting the user while entertaining him/her
open/gov data, structured data, social networks,
tourism data and recommendations
UrbanGames in PlanetData - 12/12/12
Slide 3 of 25
UrbanGames - Approach
• Urban Games: • to consume, create and assess the quality of
Smart Cities-related Linked Data
• via a Human Computation approach
• for users in mobility with smart phone devices
• Traditional Human Computation approaches are based on users' domain knowledge…
…while Urban Games are based on and aim at exploiting "on site" users' experience knowledge
UrbanGames in PlanetData - 12/12/12
Slide 4 of 25
• State-of-the-art analysis
• Concept generation and selection
• Urbanopoly prototype implementation
• Evaluation results and outlook
UrbanGames in PlanetData - 12/12/12
UrbanGames - Execution
Slide 5 of x
UrbanGames work plan (WP9 – WP10 – WP11)
16 18 20 22 12 14
Task 9.1 Concept
and Design
Task 9.2
Implementation
and Evaluation
CEFRIEL
24
D9.1 UrbanGames Concept and design
D9.2 UrbanGames Prototype and evaluation
Deliverable number and title
CEFRIEL
CEFRIEL Task 10 UrbanGames
dissemination and
exploitation analysis
Task 11 UrbanGames
activity management CEFRIEL
D10.1 UrbanGames Dissemination, exploitation and management report
UrbanGames in PlanetData - 12/12/12
Slide 6 of 25 UrbanGames in PlanetData - 12/12/12
Purpose outside the game:
helping image search engines with manual tagging
Purpose
within
the game:
Human Computation Game with a Purpose
Slide 7 of 25
Urbanopoly as a Game with a Purpose
Collect and verify information about your city
by playing with the neighborhood around you
UrbanGames in PlanetData - 12/12/12
Purpose within
the game:
Purpose outside
the game:
Create your venues' portfolio and become
the greatest landlord ever!
http://bit.ly/urbanopoly
Slide 8 of 25
Urbanopoly – high-level view
LinkedGeoData +
Lombardia Open Data
bootstrap of
"venues" data
players
game to buy / sell
venues with missions
data about
venues as
missions
GWAP approach to
consolidate data verified / improved data
+ new data
Game purpose: check and correct geo-spatial data
from pre-existing sources + collect missing data
1
2
3
4
UrbanGames in PlanetData - 12/12/12
Slide 9 of 25
Urbanopoly Input Data
OpenStreetMap (OSM) http://www.openstreetmap.org/ via LinkedGeoData (LGD) http://linkedgeodata.org/ data as linked data, described by an ontology
Lombardia Open Data https://dati.lombardia.it data about "agriturismo" places as CSV converted to RDF
Urbanopoly data bootstrap: venues are "instances" of selected LGD "classes" with their OSM tags as features, thus Urbanopoly data are RDF statements of the form:
<venue> <feature> <value>
UrbanGames in PlanetData - 12/12/12
Slide 10 of 25
Urbanopoly gameplay (1/2)
UrbanGames in PlanetData - 12/12/12
http://bit.ly/u-video
Slide 11 of 25
Urbanopoly gameplay (2/2)
the map with the
close-by venues
to be visited
the player’s venue
portfolio
the “wheel of
fortune” when
visiting an
occupied venue
the leaderboard
with the best
players
UrbanGames in PlanetData - 12/12/12
Slide 12 of 25
Urbanopoly mini-games for Data Collection
data acquisition challenges as
contributions to an advertising campaign
– left: inserting a value,
right: taking a picture
data validation challenges to check
pre-existing data or other players’
contribution – left: answering a quiz,
right: rating a poster
UrbanGames in PlanetData - 12/12/12
Slide 13 of 25
Urbanopoly Data Consolidation (1/2)
Each statement has a confidence score:
{ <venue> <feature> <value> . } <confidence>
which indicates the probability of the statement to be true
Each player action is taken as an evidence of the associated knowledge and alters the confidence score
A weighted majority voting algorithm aggregates the evidences:
◦ Difficulty to acquire the contribution (e.g., typing vs. check box)
◦ Player’s reputation (e.g., number of errors)
◦ Player’s distance to the venue at contribution time (as sensed by the device geo-positioning)
UrbanGames in PlanetData - 12/12/12
Slide 14 of 25
Urbanopoly Data Consolidation (2/2)
When the confidence score overcomes a threshold, the triple <venue> <feature> <value> gets consolidated
There are two thresholds:
◦ An upper threshold: if the confidence score becomes greater than this threshold, the triple can be considered true
◦ A lower threshold: if the confidence score becomes smaller than this threshold, the triple can be considered false
◦ The values of thresholds are set with an initial evaluation of the collected data in order to maximize the trade-off between the correctness of the consolidated information (accuracy) and the system ability to collect contributions (throughput)
UrbanGames in PlanetData - 12/12/12
Slide 15 of 25
Urbanopoly Data Publication (1/2)
True statements are published as linked open data
◦ If a statement's confidence overcomes the threshold, the statement is asserted: <venue> <feature> <value>
(as in LinkedGeoData/OpenStreetMap)
But there's more interesting information to publish!
◦ False statements, statements' confidence, provenance information (who said what, when and where), etc.
◦ We created a Human Computation ontology extending the W3C PROV-O ontology (cf. http://swa.cefriel.it/ontologies/hc)
◦ We published this further knowledge as annotations to the player's evidences (technically speaking, the reification of the <venue> <feature> <value> statements)
UrbanGames in PlanetData - 12/12/12
Slide 16 of 25
Urbanopoly Data Publication (2/2)
Human Computation ontology and its relation with the W3C PROV-O ontology
Cf. http://swa.cefriel.it/linkeddata/
UrbanGames in PlanetData - 12/12/12
aggregatedFrom
Contributor
Contribution
Human Computation
Task
provo:Agent
provo:Entity
provo:Activity
Consolidated Information
solvedBy
enabledBy
contributionFrom
so
lutio
nT
o
aggre
ga
ted
By
Human Computation
Algorithm
Slide 17 of 25
Urbanopoly Evaluation (1/2)
"Enjoyability" of the game (engagement potential):
◦ Average life play: ALP = Played Time / Active Players
◦ ~ 100 minutes very good result
"Effectiveness" of the GWAP mechanism:
◦ Throughput = Solved Problems / Played Time
◦ ~ 287 collected evidences / hour very good
◦ ~ 5 consolidated statements / hour improvable
"Precision" of the results (measured on results' subset)
◦ Accuracy = ( (P – FP) + (N – FN) ) / (P + N)
◦ ~ 92 % very good result
UrbanGames in PlanetData - 12/12/12
Slide 18 of 25
Urbanopoly Evaluation (2/2)
"Playability" of the game
◦ Evaluation survey at http://bit.ly/u-survey, with questions about usability, social aspects, physical presence, motivation, etc.
◦ Feedbacks very encouraging
"Sociability" through Facebook channel
◦ With Facebook Insights (http://www.facebook.com/insights/), tracking of installs, demographics, log-ins, content sharing, etc.
◦ Example of published "story" on Facebook Timeline:
◦ Statistics about "stories" and "impressions":
◦ Interesting results, but channel to be further exploited
UrbanGames in PlanetData - 12/12/12
Slide 19 of 25
Creating Awareness
Spreading the word: ◦ Institutional sites: CEFRIEL website, PoliMI website
◦ Interview and dedicated post on semanticweb.com Urbanopoly: Gamers’ Way To Smarten Up Cities
Letting Urbanopoly "compete" with other apps: ◦ Participation to the 10th "Semantic Web Challenge"
selected among finalists
◦ Participation to the "OpenApp Lombardia" contest
Setting up various communication channels: ◦ Social networks: YouTube, Facebook, Twitter
◦ App stores and dedicated websites: Google Play, Urbanopoly website, iTunes, UrbanMatch website
UrbanGames in PlanetData - 12/12/12
Slide 20 of 25
Scientific Dissemination
I. Celino, S. Contessa, M. Corubolo, D. Dell'Aglio, E. Della Valle, S. Fumeo and T. Krüger: "Linking Smart Cities Datasets with Human Computation – the case of UrbanMatch", Proceeding of the 11th International Semantic Web Conference, ISWC 2012, Part II, Springer LNCS 7650, pp. 34–49, 2012.
I. Celino, D. Cerizza, S. Contessa, M. Corubolo, D. Dell'Aglio, E. Della Valle and S. Fumeo: "Urbanopoly – a Social and Location-based Game with a Purpose to Crowdsource your Urban Data", Proceedings of the the 4th IEEE International Conference on Social Computing, Workshop on Social Media for Human Computation (SoHuman2012), pp. 910-913, DOI: 10.1109/SocialCom-PASSAT.2012.138, 2012.
I. Celino, S. Contessa, M. Corubolo, D. Dell'Aglio, E. Della Valle, S. Fumeo, T. Krüger: "UrbanMatch – linking and improving Smart Cities Data", In Proceedings of the Linked Data on the Web Workshop (LDOW2012), CEUR Volume 937, co-located with the World Wide Web Conference (WWW2012), April 16th, Lyon, France, 2012.
I. Celino, D. Cerizza, S. Contessa, M. Corubolo, D. Dell'Aglio, E. Della Valle, S. Fumeo and F. Piccinini: "Urbanopoly: Collection and Quality Assessment of Geo-spatial Linked Data via a Human Computation Game", Proceedings of the 10th Semantic Web Challenge 2012, November 2012.
I. Celino: "Volunteered Geographic Information Provenance: Semantic Web-based Representation and Publishing", accepted with revision, IEEE Transactions on Geoscience and Remote Sensing (TGRS) for the Special Issue on "Geoscience Data Provenance"
I. Celino, D. Dell'Aglio, E. Della Valle: "Citizen Computation: effective Community Participation to Smart Cities", under review, IEEE Communications Magazine for the Special Issue on "Smart Cities"
UrbanGames in PlanetData - 12/12/12
Slide 21 of 25
Lessons learned
Urbanopoly achieves the purpose for which it was designed
◦ Designing a GWAP means "tuning" the right mix of gaming elements and purpose-related features
◦ Improvements and extensions are of course possible, e.g. by adding further mini-games in the global game narration
◦ Physical presence is often (but not always) a good replacement for location-specific knowledge
Urbanopoly players are not OpenStreetMap editors
◦ Different motivations can exist for the same purpose
◦ The purpose of a GWAP should definitely be hidden
◦ Different users can be complementary
UrbanGames are not the universal solution for any task
UrbanGames in PlanetData - 12/12/12
Slide 22 of 25
Citizen Science
UrbanGames in PlanetData - 12/12/12
Mount Rainier NPS
http://www.flickr.com/photos/mountrainiernps/6997851139/
Glacier NPS http://www.flickr.com/photos/glaciernps/4427412443/
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Slide 23 of 25
What about those citizens?
UrbanGames in PlanetData - 12/12/12
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Slide 24 of 25
Citizen Computation
UrbanGames in PlanetData - 12/12/12
Human Computation
exploiting human capabilities
to solve computational tasks
difficult for machines
Citizen Science
exploiting volunteers
to collect scientific data or
to conduct experiments
"in the world"
Citizen Computation
exploiting human capabilities
to contribute to a mixed
computational system
by living "in the world"
Thanks for your attention!
Irene Celino
CEFRIEL – ICT Institute,
Politecnico di Milano