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

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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)

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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

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http://www.flickr.com/photos/mountrainiernps/6997851139/

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Slide 23 of 25

What about those citizens?

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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

irene.celino@cefriel.it