Created for iPhone using Unity3D, GoogleVR, Adobe AfterEffects, XML feed.


Data visualization of Google search trends in Virtual Reality which focuses on the mobile brands from 2011 until now.

Group members: Feng Yuan, Jad Rabbaa and Yiyi Shao

My responsibilities: coding


In the name of fast paced digital technology brands such as Motorolla, Nokia, etc. birth and die and new brands appear like the iPhone. Hashtags birth and die such as #MannequinChallenge #IceBucketChallenge and #HarlemShake. New words emmerge such as “Unlike”, “Unfriend” “WTF” and “OMG” etc.. and they even go out of the digital ream to get used in real life communication and conversation and even take place in international dictionaries and shape languages.

As Digital futures enthusiasts we have a huge interest in the past of the digital media and technology and how it evolved through the years. Google today is the most used search engines in the world and google analytics is a great source to have as accurate data as possible about different trends and mentions from any past till this date. Google as a platform operates 1.2 trillion searches per year, which means 3.5 billion searches PER DAY. Digital technologies such as the floppy disk which was greatly used in the 90s and early 2000s is no longer existant, it was replaced by other technologies such as the CD ROM, the DVD ROM, the usb flash drive, the external hard drive and today the Cloud! Even though a millennial can search today what a floppy disk means, the current used technology will be by far the one known and searched or mentioned on google today hence our choice and interest to go with Google trends as a data source. With the emergence and use of Big Data and 5G the world is looking a new challenge: storage! In the 90s floppy disk was one of the most used disks for data storage and it was only 3.5 MB, todays that seems insane and extremely unuseful. We aim to visualize the billions of mentions of this word relatively to other relevant storages today such as the Hard drive and the cloud storage.


To be able to visualize these tremendous amounts of mentions we needed to scope them down to percentages to visualize them in relativity to each other. In order to give the user/viewer a feeling of the “Sea” of mentions and this endless digital world of words and digits we aim to transport the human from the physical space to a digital virtual one using virtual reality. The words or mentions will be flying around the user with a rotating dial at the feet level that spins as the months and years pass by to make it an experience of 2 minutes or so.

Using Scenario

Mainly used as an art piece in art gallery or public space Tool for SEO (Search engine optimization).


PHASE 1 : Brainstorming & Research for Data | 13 March 2018:

In the class we tried to find some interesting datas source. Below is some data sources we found in class.

  • Asteroids movement:http://www.asterank.com/
  • Geological information:http://refikanadol.com/
  • Genomic data api:
    • 23ANDME api The 23andMe API Developer Program is free for developers.
    • OpenSNP Tons of data free for download, including many actual 23AndMe data sets. This is where I got my data on how much research has been done for any given SNP. The OpenSNP ranking is based on entries in the SNPedia, papers published in PLoS and Genome.gov, annotations in the Personal Genome Project and papers on Mendeley.
    • SNPedia — This is an open wiki for SNP associations. It has an enormous amount of information on specific SNPs, the different variations and their associations with phenotypes and medical conditions. It doesn’t have the raw data files available through OpenSNP, but it has far more detail on the associations of individual SNPs.
    Astrology (MIT) data source recently available to the public: http://news.mit.edu/2017/dataset-nearby-stars-available-public-exoplanets-0213 How many Stars die in a minute:https://www.quora.com/How-many-stars-die-in-a-minute US electric system operating data: https://www.eia.gov/realtime_grid/#/data/graphs?end=20180316T17&start=20180309T21

PHASE 2 : Group Meeting | 19 March 2018:

Visible stars in Milky Way: 100 Billion Stars Visible stars to human bared eyes: 5000 stars SCREEN RESOLUTION (2880 x 1800) = 5,184,000 PIXELS (iMAC) We are stuck with the visualization of stars dying and birthing in a more effective way instead of just fading in and out, we are also not sure about fit this huge amount numbers in the platform that we are working on, so we take this idea as a plan B and coming up with a new idea.

Final idea - Visualize the keyword that people put in google search engine per minute, themes we have in mind:

  • Political parties in US
  • Social media platforms
  • Iphone, Samsung, Google Pixel, LG, Nokia, Huawei
  • Google home, Amazon Alexa

Google now processes over 40,000 search queries every second on average (visualize them here), which translates to over 3.5 billion searches per day and 1.2 trillion searches per year worldwide. How many google searched today: http://www.internetlivestats.com/google-search-statistics/ Google Trend API: https://www.npmjs.com/package/google-trends-api Visualization tool: processing or p5.js Installation: projection mapping on a physical “G”

PHASE 2 : Group Meeting & Develpment | 19 March 2018:

Firstly we export the .csv file to .xml file which contains correct tags of each types of data that can be load from Unity3D through xml function. And then Unity get the data as String which can be used as variables to assign to game objects. For this project, we used particle systems to generate the visualization as our base data is numerous. We import GoogleVR package(V1.11) into unity to build the VR environment. It’s running perfectly in Unity but after building out to iPhone, the XML file has been baked to another format with different path. After a lot of research and debugging, we finally found a solution to solve this problem after reading a post here: http://www.cnblogs.com/wuzhang/p/wuzhang20140731.html

Feedback and The Future

We were able to achieve many of the goals we set out to early on in the process; we incorporated a space filled with overwhelming amount of words or mentions around the user and created an immersed environment. In potential future interactions we would like to both refine and expand on the work completed here based off of class discussion and different feedback we received throughout the process:

  • Immersion of the user in data can take one step back from how we presented the data. It could be a good pay-off to combine in the visualization how the binary system of a computer works and place the user inside that virtual environment to simulate the process of how computer process data. In this way, audience can “see” the data from where it is generated.
  • In the version of the prototype that we presented in class we studied the amount of mentions related to storage in particular, but as mentioned in the feedback comments, the topic can be anything really. From hashtags used thousands and thousands of times to different brands or technologies searched so many times over the years.
  • Also in our version, we only presented three mentions because of the limits of using unity building the VR environment. The more mentions used the bigger number of cameras needed in Unity to render a good visualization requiring a lot of space and a very powerful computer. In order to import more different data, we can try to move everything to another development engine, such as Unreal, which may provide better support for VR environment.