Hercules is a data visualization platform custom built for the Global Data Observatory (GDO) that allows users to seamlessly build multi-screen analytics dashboards without any coding. It takes any tabular data, performs analysis to determine column types and statistics, and deploys interactive visualizations to the GDO wall. The architecture includes a control server, data warehouse for storage and analysis, and a control app for dataset exploration and visualization deployment.

1. Hercules
Interactive Data Visualisation
on 100MP wall

2. Global Data Observatory

3. Global Data
Observatory
64
1080p tiled
monitors

4. Global Data
Observatory
130+
MegaPixels of
total resolution

5. The Problem
Each Visualisation is a bespoke
application in GDO
Each new dataset and visualisation requires
custom preparation and ad-hoc coding
The initial cost of data
exploration is too high

7. The Solution
Visualise any data on the cave
without any coding required
We want to make the incredible features
of GDO accessible to all
Data agnostic visualisations:
build once, work on any data!

8. What is Hercules?
A data visualisation platform
custom built for GDO
It allows the user to seamlessly build
multi-screen analytics dashboards
It’s a tool for teams to play and
experiment with their data

9. Demo

10. Architecture

11. Global Data Observatory
Control
Server
Overview

12. Pipeline
Data Warehouse Control App Visualisation
• Upload any TSV or
CSV dataset onto
our platform via a
tablet.
• Perform type
inference and
compute statistics
• Explore the data
available and pick a
dataset to plot
• Deploy visualisation
to sections
• Filter the dataset
• See your data on
the screen

13. Visualisation

14. D3.js
JS library for manipulating
documents based on data

15. DD3
D3.js
DD3
SignalR
Peer.js
D3.js

16. Visualisation
Data is sent to the browser instances of the
visualisation app running on the cave nodes
DD3 analyses the data to determine the
dimensions required
Data Points Rendered!
Dimensions are scaled to fit on the
allocated screen space
1
2
3
4

17. Data Warehousing

18. Type InferencePlain DatasetParser
Rich Dataset
CSV
Row PruningDatabase
Data Warehousing

19. Type Inference
Integer
Floating
Bool
URL
DateTime
Text
Enums
Special Case

20. Statistical Analysis
• Prune Incompatible Rows
• Compute statistics on each column
Min/Max
Mean
Median Modes
Var/StDev
Text

21. Database
Dataset
Rows
Miniset
Column Types
and Statistics
Dataset
Information

22. Control App

23. React Flux💙

24. Action Controller Model View
MVC

25. Action Controller
Model View
Model View
Model View
Model View
Model View
Model View
Model View
MVC

26. Action Dispatcher Stores Views
Action
the flux unidirectional cycle

27. Case Study
Editing a text field

29. Material Design

31. Team
Management

32. Division of Labour
• Project split into 3 ‘Pillars’
• 1 member assigned to each
• Other 3 swap as required
• Adaptive to changing workloads and different
challenges
All pillars progress at all times

33. Team Coordination

34. Challenges & Retrospective
• Large scale project
• Platform
• Inherited codebase
• Exams
• Learned new technologies

35. Conclusion

36. Conclusions
• Lots of new concepts (large group, Visual
Studio, new languages/libraries)
• Great to work with the Cave

37. “Hofstadter's Law: It always takes longer
than you expect, even when you take into
account Hofstadter's Law.
”

38. Thanks!