Title	THE END OF SOCIETY SIMULATOR
Brand	UBISOFT
Product/Service	UBISOFT
Category	A04. Data Visualisation
Entrant	BETC Paris, FRANCE
Idea Creation	BETC Paris, FRANCE
Production	MAKE ME PULSE Paris, FRANCE
Additional Company	BETC DIGITAL Paris, FRANCE

Name	Company	Position
Stéphane Xiberras	BETC	CCO
Christophe Clapier	BETC	Creative Director
Ivan Beczkowski	BETC	Executive Creative Director
Vincent Blachère, Raphaël Perrollier	BETC	Art Director
Adrien Héron, Alban Gallee, Simon Lamasa	BETC	Copywriter
Thibault Dargeou, Frédéric Petitpont, Alexis Galbourdin	BETC	Creative Technologist
Nicolas Barradeau	BETC	Lead developer
Kevin Hutchings	BETC	Strategy Planning
David Ronai	Make me pulse	Producer

The Campaign

To make this simulator as realistic as possible we gathered thousands of data from cities worldwide. Then each city was built around key urban locations (hospitals, pharmacies, supermarkets, venues, places, airports...) featuring almost half a million of them in 3,800 cities. That’s how we enabled people to start from wherever they want and demonstrated how quickly the cities and society that we take for granted can fall. In the background, all the gathered data made the development of a pandemic algorithm possible. The algorithm - inspired by existing epidemic models with input from Emergency risk specialists - helps demonstrate the fragility of society by displaying the spread of the virus and calculating the casualties. Using data from all over the world was the key component to create an experience where people could be patient zero on a map and be taken into a journey where everything that they know around their home would act as a catalyst for the storytelling and the fall of society

LIST THE DATA DRIVEN RESULTS (200 WORDS) The business impact for the brand was huge. The momentum gained by the website lasted for weeks as Collapse has attracted almost 3 million visitors and still attracted over 60K visitors/day a month later. Thousands of posts, shares and tweets from users highlighted the astounding realism and hyper-personalisation of the experience. Media impressions were numerous with articles in mainstream media (Motherboard, Time Magazine, The Daily Mail, I fucking love science, L’Express …) and video game specialized media (Kotaku, PC Gamers, vg247, gamerant ...) The success contributed to the awareness of the game beyond the gamers. The impact for the brand is undeniable as the game has become the best-selling new game franchise in an opening week and sold more copies in its first 24 hours than any game in Ubisoft’s history. Ubisoft is now the number one software publisher for Q1 2016, with a unit sales increase of close to 130%.

Based on the fictive yet realistic storyline of Tom Clancy’s The Division, Collapse is an end of society simulator that uses real data to create a hyper-personalised experience of the fall of society. Users begin by entering an address to start their simulation, as it depends on the starting point, population density, number of hospitals, the city local and global connection… 3,800 cities and half a million amenities (from OpenStreet Map and Iata) are used to generate the simulation. Data from the WorldBank, WHO, History of Vaccines and an emergency management specialist are gathered to display facts for users.

Data was imported from Web Services or by scraping them from the web. They were inserted into a database that enabled us to check whether all the data we had was included in their respective city Bounding Box. When the data and the bounding box didn’t match the city was excluded for it meant we couldn’t provide a functional hyper-personalised user experience. Then we exported the data into Json files with custom scripts which processed everything to clean, reformat and check the relations between amenities, cities and countries. Some more cities were then excluded as their number of amenities was too low to provide a meaningful user experience. As generating the spread of the virus with particles on-the-fly was too demanding for computers, we pre-rendered binaries files for each of our 3,800 cities (7Gb of particle data). Finally - based on the SIR epidemic model - we developed an algorithm to simulate a virus spread using the : ? starting point chosen by the user ? city population ? number of hospitals and distance between them ? virus infection, mortality rates ? city connection locally and globally ? and specifically on mobile: the user behaviour (eg. number of friends met)