Games with a Purpose (GWAPS) E-Book

Mathieu Lafourcade

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 255

Veröffentlichungsjahr: 2015

Beschreibung

Human brains can be seen as knowledge processors in a distributed system. Each of them can achieve, conscious or not, a small part of a treatment too important to be done by one. These are also "hunter / gatherers" of knowledge.  Provided that the number of contributors is large enough, the results are usually better quality than if they were the result of the activity of a single person, even if it is a domain expert.  This type of activity is done via online games.

Leseprobe

Table of Contents

Cover

Title

Copyright

List of Figures

Introduction

1: Biological Games

1.1. Foldit

1.2. EteRNA

1.3. Nanocrafter

1.4. Phylo

1.5. Fraxinus

1.6. Eyewire

1.7. Citizen sort

1.8. The Nightjar project

1.9. References

2: Games with a Medical Purpose

2.1. Nanodoc

2.2. Dizeez

2.3. The Cure

2.4. Malaria Training Game

2.5. Malaria Spot Game

2.6. Worm Watch Lab

2.7. Play to Cure: Genes in Space

2.8. References

3: GWAPs for Natural Language Processing

3.1. Why lexical resources?

3.2. GWAPs for natural language processing

3.3. PhraseDetectives

3.4. PlayCoref

3.5. Verbosity

3.6. JeuxDeMots

3.7. Zombilingo

3.8. Infection

3.9. Wordrobe

3.10. Other GWAPs dedicated to NLP

4: Unclassifiable GWAPs

4.1. Beat the Bots

4.2. Apetopia

4.3. Quantum Moves

4.4. Duolingo

4.5. The ARTigo portal

4.6. Be A Martian

4.7. Akinator, the genie of the Web

4.8. References

5: The JEUXDEMOTS Project – GWAPs and Words

5.1. Building a lexical network

5.2. JEUXDEMOTS: an association game

5.3. PTICLIC: an allocation game

5.4. TOTAKI: a guessing game

5.5. Voting games

5.6. Multi-selection games

5.7. From games to contributory systems

5.8. Data collected and properties of the games presented

Conclusion

Bibliography

Index

End User License Agreement

List of Illustrations

1: Biological Games

Figure 1.1. Foldit. The game interface is a three-dimensional view of the protein being studied. The molecular components (hydrogen bonds, hydrophobic chains, etc.) can be manipulated with the mouse, and each action alters the spatial conformation of the protein

Figure 1.2. EteRNA. Here, an RNA molecule in the spatial conformation that it must adopt if the proper sequence of nucleotides is performed, the one that will allow the establishment of bonds ensuring the stability of the structure. The circles in the molecule are to be replaced by the A, T, G and C bases chosen at the bottom right

Figure 1.3. Nanocrafter. In the configuration above, colored items represent fragments of single-stranded DNA that must be assembled respecting the color correspondences to form double-stranded structures

Figure 1.4. Phylo. The purpose is, by moving laterally the color squares, to find the best alignment compromise possible between the five presented fragments of sequences. Above the sequences, the colored bar illustrates the progression of the score, the small top triangle being the score achieved by the computer, which must be met and exceed to move to the next level

Figure 1.5. Fraxinus: sequences to be aligned. The purpose is to find the best way to vertically align the colors of the blocks constituting six sequences. They must be aligned between themselves AND with the visible reference sequence at the top. This is achieved by pushing laterally the sequences using the left and right arrow keys

Figure 1.6. Fraxinus: sequences almost aligned. Compared to the previous figure, it can be seen that the blocks of colors of the six sequences are almost perfectly aligned, both among themselves and with the model. But although the score has gone up from −148 to +425, the alignment can still be improved since it can be read, in the bottom left, that the record to beat is 520

Figure 1.7. The interface of Eyewire. On the left, the “cube” (fragment of a histological section of the retina) which contains the neural branch to be outlined, of which a fragment can be seen. On the right, the corresponding transversal cross-section where the player “colors” areas that seem to him/her to belong to the neuron. He/she, therefore, “follows” the neural branch by traversing the entire thickness of the cube, through which he/she moves with the arrow keys of the keyboard

Figure 1.8. Eyewire. This image from the blog of the game highlights a synapse (the point of junction between two neurons) discovered by means of the activity of the players

Figure 1.9. Citizen Sort: Happy match. The first screen of the game presents 10 pictures of butterflies. At this stage, the player must just validate the pictures, that is to eliminate those that are blurry, truncated or of too poor quality to be used. In the following screens, he/she will categorize butterflies following various morphological criteria (wing shape, dominant color, etc.)

Figure 1.10. The Nightjar project. The introduction screen of the Nightjar game, one of the games of the project

Figure 1.11. Nightjar game. A nightjar (designated by the arrow) is hidden in this setting, and the player has 30 s to locate it and click on it

Figure 1.12. The game Egglab. Making an Ester egg hunt is a variant of the EGGLAB game: the player chooses a setting, and then hides himself/herself the eggs by clicking and dropping them in areas of his/her choice. He/she can then send the url of the created game to his/her friends

2: Games with a Medical Purpose

Figure 2.1. Nanodoc. The objective is to build the combination that will fulfill the mission shown in the left figure by using the nanoparticle editor. On the right, the result (success): all the cancer cells (in gray) have been destroyed. For a color version of this figure, see www.iste.co.uk/lafourcade/games.zip

Figure 2.2. The Cure. By analogy with poker, it is necessary to constitute a hand by choosing 5 genes in the central part. The selected genes appear in the top window, and the text on the right gives information about the gene when the mouse passes over it, in order to guide the choice. Each gene chosen contributes to the scores, the goal is to beat that of Barney (the algorithm of choice)

Figure 2.3. Malaria training game. Top figure: the cells are characterized (positive, negative and questionable) by clicking them after choosing the appropriate tool in the menu on the right. The figure on the bottom shows the score at the end of the game

Figure 2.4. Malaria Spot Game. The homescreen of the game acts as a tutorial: circles designate the forms corresponding to parasites to be discovered, while the crosses indicate cellular structures that must not be confused with a plasmodium

Figure 2.5. Worm Watch Lab. On the left of the figure, the display allows visualizing a worm in motion for 30 s. The player clicks on the z key whenever it is seen laying an egg. On the right, the result of a sequence of observation is displayed, as well as the number of eggs observed by another player, if the sequence has already been viewed

Figure 2.6. Play to Cure: Genes in Space

3: GWAPs for Natural Language Processing

Figure 3.1. PhraseDetectives: “Name the culprit”. The player is asked what term (if it exists in the displayed text) constitutes the antecedent of the anaphora highlighted. When the player moves his/her mouse over the sentence, the terms or groups of terms become highlighted. The player also has the opportunity to state that it is not an anaphora, by clicking on “Not mentioned before” or “This is a property”

Figure 3.2. PhraseDetectives: “Name the culprit”. Screen showing the player’s response (The term banhammer), highlighted. The last thing for him/her to do is to click on “Done”

Figure 3.3. PhraseDetectives: “Detectives Conference”. The player is asked to validate or not, the proposal made earlier by another player. If the player disagrees with the proposal, he/she will have the possibility to indicate which term, according to him/her, is the antecedent of the anaphora, analogously to the mode “Name the Culprit”

Figure 3.4. PlayCoref. Example of a screen showing the coreference relations proposed by the player

Figure 3.5. Verbosity: guesser player. Here, the player must guess the word from the proposed clues

Figure 3.6. Verbosity: descriptor player. Here, the player must make other players guess the word from the proposed clues. The clues proposed here follow the instructions of types, but no verification is carried out about this matter in real time. In addition, it is sometimes difficult to give information about some clues (for example, here: what is the opposite of “squirrel”?)

Figure 3.7. Zombilingo: annotation of the subject. The player must indicate which word of the sentence (As for Mr. Fogg, he rested as peacefully as if he had been in his quiet house in Saville Row) is, according to him/her, the subject of the verb (rested)

Figure 3.8. Zombilingo: annotation of the complement of object In the sentence ACT values 5 minutes after the bolus of bivalirudin reach in average 365 ± 100 seconds. the player must annotate the complement of object of the verb reach

Figure 3.9. Infection: instructions

Figure 3.10. Infection: the launched match

Figure 3.11. WORDROBE: a game from Others, one of the seven annotation games In the displayed sentence, the player must indicate to what word highlighted corresponds the word others displayed in bold, by selecting the corresponding item in the suggested list below. The cursor at the bottom left allows bets to be made on one’s response, and one’s gain to be maximized (but taking the risk to obtain the opposite effect, if the answer given is not that chosen by the majority of the other players)

4: Unclassifiable GWAPs

Figure 4.1. Apetopia. The home screen of the game

Figure 4.2. Duolingo. The home screen of the game which summarizes the progress through the different learning modules, and offers either to strengthen knowledge or to test it by translating texts extracts from the press

Figure 4.3. Artigo. At the end of the game and for each work of art, the score that the player obtained with each is accessed (common words are displayed in another color), and so is the identification information (title, author, etc.)

Figure 4.4. Be A Martian. The home screen offers various crowdsourcing activities related to the collection and analysis of the mass of data collected by satellites and exploration rovers

Figure 4.5. Akinator: main part of the home screen. This screen shows a particularly ludic interface: the game is available in several languages (currently 14), it is possible to play on different types of smartphones, and there is a specific version for children. The results of the last 10 games are also displayed, thus showing AKINATOR’s success rate (90% on the screen presented here), on characters sometimes little known or little publicized

Figure 4.6. Akinator screens. Series of some images screens showing examples of questions raised by the genie AKINATOR. Observe its different facial expressions, in particular his satisfaction when he believes he has found

5: The JEUXDEMOTS Project – GWAPs and Words

Figure 5.1. Illustration of a lexical network. Diagram of a portion of a lexical network bringing forward some relations

Figure 5.2. A typical JeuxDeMots game. The player has to suggest terms that he/she associates with the target word “meuble” (furniture). His/her suggestions are shown on the right as he/she inserts them in

Figure 5.3. The result of the previous game. The active player Kaput has seven terms in common with the passive player Eolidou. The two players have scored 275 credits and 10 honor points

Figure 5.4. Home page of the game JeuxDeMots

Figure 5.5. PtiClic typical game. For the target word restaurant, the three target relations proposed are hypernymy, synonymy and association of ideas

Figure 5.6. Typical TOTAKI game. To make TOTAKI guess Belle de Fontenay, three hints were enough

Figure 5.7. Success rate of TOTAKI. Evolution of the success rate of TOTAKI to correctly guess the term targeted by the player

Figure 5.8. Typical Askit game. On the left, the statement about which the player must give his/her opinion by responding“yes”, “no” or “possibly but uhh”, on the right, the result: The percentage of players of the same opinion being displayed, as well as the progress bar of the associated score

Figure 5.9. Typical LikeIt game. Example of two consecutive LikeIt screens. Following the response in the left screen, the player sees immediately at the top of the next screen (right image), the percentage of players who share his/her opinion: direct feedback is thus given, while the game is immediately rerun with a new question

Figure 5.10. Typical SEXIT game. The player must choose between two possibilities: has the word any relation with sex (non-barred heart) or not (barred heart). By clicking, one is directly brought to another game, while the result of the previous choice (percentage of players of the same opinion) is displayed at the top of the screen

Figure 5.11. Typical COLORIT game. For the word vegetable, the player must either click on the color that he/she most spontaneously associates with this term, or suggest several of them and/or some others through the text field. His/her response causes a new term to be displayed with the score in points at the top of the screen and on the right the answers of the other players for the previous term, with their percentages

Figure 5.12. Regular EMOT game. The player must associate one or more emotions/feelings with the term generosité, either by clicking on a smiley or by entering words in the text area. As for COLORIT, the answer causes the suggestion of a new term, with the score in points being displayed together with the responses of the other players and their proportions

Figure 5.13. Regular POLITIT game. The player must associate the term race with a political tendency. Only one choice is possible. The bottom image shows the percentage of players who have made the same choice, and the distribution of the responses of the other players between the six possibilities, and between right and left (here, a particular case showing a unanimous choice)

Figure 5.14. Typical TIERXICAL game. Among nine possible characteristics, the player is prompted to select in the order the three terms that he/she considers most relevant of characteristics for the term quince. On the right, it can be seen that the result of this game is a boxed trifecta

Figure 5.15. ASKU screen. The player/contributor is invited to give an opinion about a number of suggestions relating to the term felicity in the sense of happiness. For each suggestion, a gradation of possible responses is available, ranging from the unreserved consent true to total rejection false

Figure 5.16. Typical DIKO screen. The user has displayed the entry mulot (mouse), and the terms related to mulot by various relations can be seen. The interface is configurable and the level of detail (number of words to display, accuracy of the information, etc.) can be adjusted by the user

Figure 5.17. DIKO screen in contribution mode. The user has displayed the entry grande marée (big tide), and the terms proposed but not yet validated can be seen (these are the words followed by little squares used to vote for or against these word as relevant or irrelevant proposals). The small hearts correspond to the polarity. The interface is configurable and the colors of the labels of the relations have been adjusted by the user

Guide

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Table of Contents

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FOCUS SERIES

Games with a Purpose (GWAPs)

Mathieu Lafourcade

Alain Joubert

Nathalie Le Brun

Joseph Mariani

Patrick Paroubek

First published 2015 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK

www.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA

www.wiley.com

© ISTE Ltd 2015

The rights of Mathieu Lafourcade, Alain Joubert and Nathalie Le Brun to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2015940033

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISSN 2051-2481 (Print)

ISSN 2051-249X (Online)

ISBN 978-1-84821-803-1

List of Figures

It should be noted that all figures are also available in color at www.iste.co.uk/lafourcade/games.zip.

1.1. Foldit

1.2. EteRNA

1.3. Nanocrafter

1.4. Phylo

1.5. Fraxinus: sequences to be aligned

1.6. Fraxinus: sequences almost aligned

1.7. The interface of Eyewire

1.8. Eyewire

1.9. Citizen Sort: Happy match

1.10. The Nightjar project

1.11. Nightjar game

1.12. The game Egglab

2.1. Nanodoc

2.2. The Cure

2.3. Malaria training game

2.4. Malaria Spot Game

2.5. Worm Watch Lab

2.6. Play to Cure: Genes in space

3.1. PhraseDetectives: “Name the culprit”

3.2. PhraseDetectives: “Name the culprit”

3.3. PhraseDetectives: “Detectives Conference”

3.4. PlayCoref

3.5. Verbosity: guesser player

3.6. Verbosity: descriptor player

3.7. Zombilingo: annotation of the subject

3.8. Zombilingo: annotation of the complement of object

3.9. Infection: instructions

3.10. Infection: the launched match

3.11. Wordrobe: a game from Others, one of the seven annotation games

4.1. Apetopia

4.2. Duolingo

4.3. Artigo

4.4. Be a martian

4.5. Akinator: main part of the home screen

4.6. Akinator screens

5.1. Illustration of a lexical network

5.2. A typical JeuxDeMots game

5.3. The result of the previous game

5.4. Home page of the game JeuxDeMots

5.5. PtiClic typical game

5.6. Typical TOTAKI game

5.7. Success rate of TOTAKI

5.8. Typical Askit game

5.9. Typical LikeIt game

5.10. Typical SEXIT game

5.11. Typical COLORIT game

5.12. Regular EMOT game

5.13. Regular POLITIT game

5.14. Typical TIERXICAL game

5.15. ASKU screen

5.16. Typical DIKO screen

5.17. DIKO screen in contribution mode

Introduction

Since the 15th Century, the oxymoron serio ludere has suggested the idea of combining the concepts of games and serious subjects. Humanist literature would extensively use this concept to denounce all kinds of social problems. Then, until the development of computing, the armies of the world would exploit this concept through war games, which are ludic simulations for developing new tactics and training officers1. The modern concept of the serious game dates back to 2001–2002, with the video game AMERICA’S ARMY2, developed for the US military to simulate training exercises. But almost simultaneously, the notion of the serious game would be popularized by its application to the educational world. Today, the title serious game refers to such diversity in terms of support, concepts, intentions, approaches and target audiences that it is difficult, if not impossible, to confine this concept into an exhaustive definition. One of the least restrictive definitions refers to a computer application that combines serious intent, education-oriented, and that is informative, communicative, marketing, ideological, or for training, with recreational parameters issued from video games or computer simulations.

Karen Chabriac, in her review of all the attempts of definition of serious games3, concludes that the most synthetic is that of [MIC 06]: any type of game whose purpose is other than mere entertainment.

Due to the diversity of themes, objectives and approaches, there are numerous attempts regarding the classification of “serious games”, depending on their purpose (advertising, recreational–educational, military, simulation, prevention, training, rehabilitation, etc.), or even depending on the serious function associated with the ludic basis (informative broadcast, educational, persuasive, military, etc.), provide training to improve the physical or cognitive potential of players, promote the exchange of data between players (or between the designer of the game and players), and/or the associated market sector (the type of public targeted). There is even an interactive site dedicated to the research of serious games based on several simultaneous criteria, divided into three categories: intention, market and public4.

The general idea is that there are only two broad categories of games: ludic games designed for entertainment and serious games in which the player learns. In fact, in parallel to this concept, a third category of games has been emerging for slightly more than a decade, the Games With A Purpose (GWAPs), in which it is the player who teaches something to the machine. The concept of GWAPs is based on the idea of harnessing human skills for purposes of research and/or data production, whether destined to support programs to progress in their understanding of the world or more simply to use home computers to increase the computing power at the service of a research project. In either case, the ludic component is essential to motivate the public. The applications are numerous and the sector is growing. The concern is to exploit the available brain time (available and not only willing, but enthusiast if possible) to perform tasks that machines are (still) unable to do. A non-negligible or even crucial aspect is that this type of games, directed toward the production of all kinds of data, makes it possible to, therefore, use the creativity, the imagination, the knowledge and the know-how of hundreds or even thousands of users at a lower cost. It should be noted that unlike the AMT system5 (resource collection tool that uses crowdsourcing and offers a derisory remuneration as well as conditions not complying with the French labor law) the principle of GWAP does not raise any ethical problem, as long as it remains free and does not offer prizes that look like disguised salaries [SAG 11].

Originally, at the formalization of the concept of GWAP, there were CAPTCHAs, which were invented by Luis Von Ahn [AHN 06a], an American academic: these are small tests based on the deciphering and the input of a sequence of characters, which are employed to differentiate a human from a computer on the Internet, and thus to prevent spam, phishing or any other malicious activity by automatic means. Luis Von Ahn realized that the 10 s spent by a human to decipher a CAPTCHA (therefore to do something which a computer does not know how to do) could be usefully employed. He then created RECAPTCHA: from now on, when a captcha is decrypted, not only does it identify the user as a human being, but it also helps to digitize books by deciphering sequences of characters that the optical character recognition (OCR) is unable to decipher. The principle of the GWAP was born, and will be illustrated by ESP GAME [AHN 04]: the father of CAPTCHAs invented a game that consists of presenting the same image to two players who will score points and progress as soon as they suggest the same keywords to define it. The interest is naturally to make searching for images by keywords in a search engine more powerful, accurate, fast and relevant.

The use of GWAPs, either to collect data, annotate images or documents, or to solicit the public for solving major scientific problems, is currently expanding and it concerns all areas. Nonetheless, it gives rise to the most high-profile experiences and results in the life sciences and medical fields. The concept of citizen science reflects not only a change in the way that scientific issues are perceived by the public, but also a willingness to take science out of laboratories and researchers out of their ivory towers. By making the challenges of research accessible and understandable by ordinary people, science is demystified and desecrated. For researchers, the ludo-collaborative approach is a powerful way to involve the public and to mobilize its support and its empathy, while soliciting and evaluating its non-specialist outside perspective. It should be noted that, according to Luis Von Ahn and during the years 2005–2010, almost 1010 (i.e. 10 billion) hours have been spent annually by individuals playing on the Internet (which globally corresponds to an average slightly higher than 1 h per person and per year). Why not try to deviate from it, at least a tiny portion, for useful games allowing the acquisition of resources?

GWAPs are thus numerous in multiple disciplines, and it is now obvious after a careful overall review that the effort of giving a really recreational dimension to a useful task is very uneven. As a result, games where the interest is all the more stimulated by a real challenge, by emulation among players, by a motivating classification system and, above all, by a real interest of the underlying task are found less often than games stimulated by the idea of helping science and/or of doing good work. Frequently, various parameters are borrowed from the universe of games (design, avatar, sounds, etc.) to give a ludic polishing to a monotonous and repetitive task. It is clear that in many cases game designers primarily rely on the players’ civic zeal by means of the excitement caused by participative science and the extremely rewarding feeling to achieve something useful in a field which remains prestigious in the eyes of the general public.

With regard to GWAPs, and since they are all based on the principle of crowdsourcing, large discrepancies can be observed according to the nature and the magnitude of the task, the target audience, the field of research, the skills required on the part of the players, the ludic and/or the educational dimension, and the manner in which the data generated by the game are processed. The choice of criteria for establishing a classification is, therefore, difficult; however, the classification of [GOO 13], which is based on the nature, the extent and the complexity of the task, can be considered as interesting. In fact, these authors make the distinction between microtasks and macrotasks in systems using crowdsourcing for scientific purposes. Microtasks are tasks that can be solved within seconds by anyone who is able to read some simple instructions, and macrotasks, on the contrary, concern complex problems that are resistant to the qualified experts of the institutional research. The first category of tasks require a large number of people who will process a huge volume of data in a short period time, and whose contributions, (strongly) redundant between players, will be aggregated in order to provide data of a quality as good as experts’ annotations. For the second category, resorting to crowdsourcing makes possible to detect the few talented people within a large population of potential candidates with very heterogeneous skills. Through the provided interactive environment, they will not only demonstrate but also develop the inventiveness, the curiosity and the creativity necessary to meet the challenge and allow real scientific progress.

It should be noted that among GWAPs, a huge majority concern microtasks.

It should also be noted that games with a large audience whose spectacular results are subject to a wide media coverage, and which are generally macrotasks (FOLDIT6, EYEWIRE7), all have a dedicated website while GWAPs, with a more modest ambition, instead related to microtasks, are often proposed through portals. The most famous and the oldest is ZOONIVERSE8.

At the origin of the ZOONIVERSE portal, there is GALAXYZOO9, an online astronomical project which somewhat symbolizes the beginnings of the type of science known as citizen. GALAXYZOO is a scientific project based on volunteers, destined to characterize galaxies from pictures, and the success was such (in 2007, 85,000 contributors in five months, according to Wikipedia10) that the idea to secure the cooperation of the general public has inspired many other programs. Currently, the ZOONIVERSE portal is a huge international platform, which brings together a large number of collaborative projects among which some have borrowed attributes from games to present a more attractive appearance. After registering (more than one million people have registered around the world), it is possible to collaborate in all the projects of the portal, which are classified by main themes (space, weather, nature, humanities and biology). Within each theme, various crowdsourcing activities are proposed, almost all dedicated to the processing of a large volume of data. These activities can either be identifying fauna and flora on pictures of seabeds (SEAFLOOR EXPLORER), or wild animals which pass through the field of a camera installed in a natural reserve (SNAPSHOT SERENGETI). It can also involve the deciphering of handwritten labels of animal or botanical specimens kept in museums of natural history (NOTES FROM NATURE), as well as many other useful tasks and for which automated processing is excluded. All of these activities fall within the scope of the voluntary participation rather than that of gaming. This is true despite the presence of ludic elements such as a score, or the creation of a collection