Urbanopoly – a Social and Location-based Game with a Purpose

to Crowdsource your Urban Data

Irene Celino, Dario Cerizza, Simone Contessa,

Marta Corubolo, Daniele Dell’Aglio,

Emanuele Della Valle and Stefano Fumeo

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

Agenda

� Context

� Gamification

� Human Computation & Games with a Purpose

� Smart Cities & Mobile Users

� Citizen Computation Games

� Motivation

� Approach

� Urbanopoly

� Purpose & high-level view

� Storyboard and gameplay

� Data Collection, Data Consolidation & Data Publishing

� Evaluation

� Conclusions

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly2

Context: Gamification

� Definition:

“The integration of the mechanics that make games

fun and absorbing into non-game platforms and experiences

in order to improve engagement and participation”

TNS Global

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

“50% of companies will embrace gamification by 2015”

Gartner Research

“Over 70% of Global 2000 organizations will have at least one

gamified application by 2015” Gartner Research

“Gamification projects will grow from $100 million in 2011 to

$1.6 billion by 2015” M2 Research

“Gamification Market to Reach $2.8 Billion in US by 2016”

M2 Research

Urbanopoly3

Context: is Gamification a fad?

� In some ways it is a fad – adding points and badges in tacky ways, looking at "gamification" as an easy way to make boring things seem interesting – that is a fad. However, the idea of designing business processes so that those who engage in them find them more intrinsically rewarding – that is a long term trend.

Schell Games

� In three years, we will talk about what is at the core of it – design for motivation – not about the one strategy to get there: getting inspiration from games.

Coding Conduct

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly4

Context: Human Computation

� Definition:

"A paradigm for utilizing human processing power

to solve problems that computers cannot yet solve

(e.g. image recognition that is trivial for humans, but

challenges the most sophisticated computer programs)"

Luis von Ahn (CMU)

� Famous examples:

� CAPTCHA

� Google Image Labeller (and all "Games with a Purpose")

� Freebase data cleansing campaign

� Amazon Mechanical Turk

� CrowdDB

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly5

Context: Smart Cities and Mobile Users

� Success of Smart Phones and portable devices

� Success of location-based services (e.g. Siri)

� Popularity of "light-weight" social networks (e.g. foursquare)

� Large availability of data about the physical world (e.g. VGI)

� Users in Mobility are a natural target of (casual) games

� Urban Spaces of Smart Cities (and thus urban data) are interesting for a large number of "Citizens"

� Inhabitants

� Commuters

� Tourists

� ...

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly6

Motivation: Citizen Computation Games

Urban Computing and Location-based Services

Linked Data and Semantic Web

Games with a Purpose and

Crowdsourcing

Citizen Computation

Games

Citizen Computation

Games

citizens as sensors, check-in logging, mobile apps

collecting data, cleaning data, engaging the user, supporting the user with entertainment

open/gov data, structured data, social networks,

tourism data and recommendations

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Citizen Computation approach

� Citizen Computation 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/background knowledge…

…while Citizen Computation is also based on and aims at exploiting "on site" users' experience knowledge

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly8

Urbanopoly purpose

� Casual Mobile Location-based Game with a Purpose in urban environments aimed to:

� consume “clean” urban Linked Data

� assess and improve “doubtful” urban Linked Data

� contribute “new” urban Linked Data

� Why Casual? To involve the largest possible user base (i.e. no entry barrier)

� Why Mobile? To address users in mobility and exploit mobile devices capabilities (e.g. GPS location)

� Why GWAP? To engage the user base with entertainment

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Urbanopoly – high-level view

LinkedGeoData(OpenStreetMap)

bootstrap of "venues" data

players

game to buy / sell venues with missions

data about venues as missions

GWAP approach to consolidate dataverified / improved data

+ new data

Game purpose: check and correct pre-existing data from LinkedGeoData (OpenStreetMap) + collect missing data

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

1

2

3

4

Urbanopoly10

Urbanopoly Input Data

� OpenStreetMap (OSM)http://www.openstreetmap.org/data as key-value pairs + pre-defined tags

� LinkedGeoData (LGD)http://linkedgeodata.org/data as RDF triples (linked data), described by an ontology

� Urbanopoly data bootstrap: venues are "instances" of selected LGD "classes" with their OSM tags as features

� Urbanopoly data are RDF statements of the form:

<venue> <feature> <value>

� E.g.: <Rijksmuseum> rdf:type uo:Museum .

<Rijksmuseum> uo:museum_type "art museum" .

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly11

Urbanopoly "game mood"

Collect information about your city by playing with the neighborhood around you.

Create your venues' portfolio and become the greatest landlord ever!

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly12

http://bit.ly/urbanopoly

Urbanopoly gameplay

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

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

Urbanopoly13

Urbanopoly mini-games for Data Collection

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

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

Urbanopoly14

Urbanopoly Data Consolidation

� Each statement has a confidence score:

{ <venue> <feature> <value> . } <confidence>

which indicates the probability of the statement to be true

� Each player action (inserting a value, choosing an option, verifying a piece of data) is taken as an evidence of the associated knowledge

� Each evidence alters the confidence score of the related statement(s) by an incrementor a decrement

� When a statement's confidence scoreovercomes a threshold, after the evaluation of 2+ distinct players' actions, the statement becomes either true or false

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

truewhen > upperthreshold

falsewhen < lower threshold

evidences from players alter confidence score

Urbanopoly15

Urbanopoly Data Publication

� True statements published as linked data

� If a statement's confidence becomes greater that the upper threshold, the statement is asserted: <venue> <feature> <value>

� This is the approach adopted by OpenStreetMap/LinkedGeoData

� But there's more interesting information to publish!

� False statements, statements' confidence, provenance info, etc.

� We decided to publish this further knowledge as annotationsto the statements (reification) by extending the W3C PROV-Oto create a GWAP ontology (http://swa.cefriel.it/ontologies/gwap)

� Cf. http://swa.cefriel.it/linkeddata/

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly16

Player

Input

Game

provo:Agent

provo:Entity

provo:Activity

Aggregated Output

playedBygeneratedBy

contributedBy

evidenceFrom

usedE

vidence

consolidatedFrom

Urbanopoly Evaluation (1/2)

� "Enjoyability" of the game (engagement potential):

� Average life play: ALP = Played Time / Active Players

� ~ 80 minutes � very good result ☺

� "Effectiveness" of the GWAP mechanism:

� Throughput = Solved Problems / Played Time

� ~ 5 consolidated statements / hour � can be improved �

� "Precision" of the results (measured on results' subset)

� Accuracy = ( (P – FP) + (N – FN) ) / (P + N)

� ~ 92 % � very good result ☺

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly17

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.

� First 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 ☺

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Conclusions

� Gaming features and design are core to find the best trade-off between players' engagement and effectiveness to achieve the GWAP purpose

� Getting both a high ALP and a high throughput is a challenge, while getting a high accuracy is relatively easy

� Citizen Computation games with a "social" flavour appear a powerful means to collect and validate urban data� Meeting point of Human Computation, Social Computing and

Crowdsourcing

� Smart Cities stakeholders have a number of needs that could be fulfilled by this kind of solutions

� Origin/destination matrixes, pressure on parking maps, etc.

SoHuman Workshop @ SocialCom 2012 - 2012/09/03 Urbanopoly19

Thanks for your attention!Questions?

SoHuman Workshop @ SocialCom 2012 - 2012/09/03

Irene Celino – CEFRIEL, ICT Institute Politecnico di Milano

email: Irene.Celino@cefriel.it – web: http://swa.cefriel.it