Location based data visualisation framework for web

Takram has developed a web-browser-based framework for visualising geographical big data. Three visualisations were created for Media Ambition Tokyo 2017, presenting data on language, air traffic, and population. The framework is designed to achieve both analytical and immersive visual experience through the use of various techniques such as parallel projection and depth of field.

Photo by Koki Nagahama / 2017 Getty Images

#1 Tweeted Languages

This scene visualises 627,308 tweets posted between the 28th of January and the 8th of February 2017. The 62 languages that were detected in the tweets during this period are ranked according to the frequency of usage. Tweets are then stacked based on language. English, the most widely-tweeted language globally, is placed at the bottom of the stack whereas the least-tweeted languages are placed at its top. The scene also includes 2,639 global languages represented by white spheres. Their classification and location are based on a publication of the Max Planck Institute for Evolutionary Anthropology.

#2 Estimated Population 2050

This scene visualises the population of Japan in 2010 based on the census result, and one in 2050 based on the forecast by Statistics Bureau, Ministry of Internal Affairs and Communications. With a resolution of 500 metres, the height and colour of each column represent the population of the area. The forecast also included regional population changes and projected age distributions from 2010 to 2040 which can be accessed by selecting an individual prefecture.

#3 World Air Traffic

This scene visualises the flight paths of the 6,763 planes that were in the air at 8:36 on 21st of January 2017. The red dots represent all 16,405 airports in the world, and are scaled based on the number of flights that they accommodate.


Design & Development:
Shota Matsuda

Onden Imaizumi BLDG
5-7-4 Jingumae
150-0001 Tokyo, JAPAN


First Floor
7 Bath Place
London EC2A 3DR, UK

New York

68 Jay Street, Suite 432, Brooklyn, NY 11201, USA


109, 18F, L'Avenue
No.99, Xianxia Road, Changning District
Shanghai, China