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GAPARS SIGNED

Gamification of participatory science for training and education purposes

Total Cost €

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EC-Contrib. €

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Partnership

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Project "GAPARS" data sheet

The following table provides information about the project.

Coordinator
MMOS SARL 

Organization address
address: ROUTE DE L'ILE-AU-BOIS 1A
city: MONTHEY
postcode: 1870
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Project website http://gapars.mmos.ch
 Total cost 1˙661˙852 €
 EC max contribution 573˙297 € (34%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2016-1
 Funding Scheme IA
 Starting year 2017
 Duration (year-month-day) from 2017-01-01   to  2019-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MMOS SARL CH (MONTHEY) coordinator 0.00
2    UNIVERSITEIT VAN AMSTERDAM NL (AMSTERDAM) participant 263˙391.00
3    CCP HF IS (REYKJAVIK) participant 92˙098.00
4    MUSEUM NATIONAL D'HISTOIRE NATURELLE FR (PARIS) participant 89˙024.00
5    KUNGLIGA TEKNISKA HOEGSKOLAN SE (STOCKHOLM) participant 64˙391.00
6    VIB BE (ZWIJNAARDE - GENT) participant 64˙391.00
7    UNIVERSITE DE GENEVE CH (GENEVE) participant 0.00
8    Virgo Systems Kft. HU (BUDAPEST) participant 0.00

Map

 Project objective

Creating effective ways for citizen science is immensely important. Scientists in all fields increasingly rely on active public participation for experiments and analyses of complex and/or massive data, and the outreach and education possibilities of citizen science are enormous.

Yet there are three key issues for any citizen science project: (i) reach out to a sufficiently large audience, (ii) lower the threshold to participation as much as possible, and (iii) provide incentives to continue participant engagement.

We created Massively Multiplayer Online Science to connect scientific research and video games as a seamless gaming experience. Research tasks completely integrated with game mechanics, narrative and visuals can open up a new channel between the gamer and the scientific community. Converting a small fraction of the billions of hours spent with playing video games will bring an enormous contribution to scientific research, and in the meantime will change how video games’ expertise is perceived.

The goal of GAPARS project is to develop and validate the reference platform enabling the injection of scientific tasks into on-line communities, such as gamers. To do so, we gathered a unique team of prestigious participants and one major game editor, all with a track-record of excellence in management and in their respective domain of expertise. This project will put Europe on the map with a new genre of serious games.

 Deliverables

List of deliverables.
Report on small scale experiment Documents, reports 2020-01-14 16:55:43
MMOS Platform Game engine and client modules Demonstrators, pilots, prototypes 2020-01-14 16:55:44
Interface and gamified environment Websites, patent fillings, videos etc. 2020-01-14 16:55:44
Report on social risks Documents, reports 2020-01-14 16:55:54
Report and lessons learned on The Story of Proteomics (t+30) Documents, reports 2020-01-14 16:55:43
Report on Project Impact Documents, reports 2020-01-14 16:55:44
Project final report Documents, reports 2020-01-14 16:55:45
Dissemination and Communication Report Documents, reports 2020-01-14 16:55:53
Report on gaming strategies and guidelines Documents, reports 2020-01-14 16:55:44
Statics of Small Scale Experiments Open Research Data Pilot 2020-01-14 16:55:44
Testing and CI beta setup Demonstrators, pilots, prototypes 2019-10-09 11:30:50
Project Web site Websites, patent fillings, videos etc. 2019-10-09 11:30:55

Take a look to the deliverables list in detail:  detailed list of GAPARS deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Devin P Sullivan, Casper F Winsnes, Lovisa Åkesson, Martin Hjelmare, Mikaela Wiking, Rutger Schutten, Linzi Campbell, Hjalti Leifsson, Scott Rhodes, Andie Nordgren, Kevin Smith, Bernard Revaz, Bergur Finnbogason, Attila Szantner, Emma Lundberg
Deep learning is combined with massive-scale citizen science to improve large-scale image classification
published pages: 820-828, ISSN: 1087-0156, DOI: 10.1038/nbt.4225
Nature Biotechnology 36/9 2019-07-18

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The information about "GAPARS" are provided by the European Opendata Portal: CORDIS opendata.

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