The Future Of Data Visualization with Gert Franke OVERVIEW Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations? In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like. OBJECTIVE Show the history, potential and future of data visualization. TARGET AUDIENCE People that want to understand the possibilities of interactive data visualizations. FIVE THINGS AUDIENCE MEMBERS WILL LEARN The history of data visualization The reasons why data visualization became so hot the last few years The potential of data visualization The things we have to be aware of when creating (interactive) data visualizations What might the future look like with the use of data visualization

1. CLEVER°FRANKE — FITC — 22-02-’16
—
THE FUTURE OF DATA
VISUALIZATION

2. What is data visualization?

3. My approach

4. PERSPECTIVEData Visualization+

5. CLEVER°FRANKE combines strategy, design and technology to
create data driven tools that drive change.
Who are we?
FOUNDED
IN 2008

6. THE FUTURE
So let’s start with the history!

7. Clay tablet with map of the Babylonian city of Nippur (ca. 1400 BC)

8. social
Cholera Map (1854)
John Snow

9. Statistical Atlas of the United States of America (1880)
Henry Gannett

10. Weather chart
1963

11. At any time Specific In summary Encourages actionInforms
±’90: TV weather forecast ’97 Website ’06 Radar image ’11 Personalised app ’14 Personalised alerts
Will it rain?
Current history

12. C°F weather charts:
visualizing weather data

13. OPEN
DATA

21. What’s needed to create
a data visualization?

22. ROUGH INGREDIENTS FOR DATA VISUALIZATION
Presentation
Platform
Data Visualization tool

23. ACQUIRE PARSE FILTER VISUALIZE ENRICH INTERACTANALYSE
based on Computational Information Design by Ben Fry
METHOD

24. ACQUIRE PARSE FILTER VISUALIZE ENRICH INTERACTANALYSE
based on Computational Information Design by Ben Fry
METHOD

25. Easy to use
Advanced
Data Design
Google Fusion Tables
TIBCO Spotfire
MagnaView
QlikView
Tableau (public)
Cytoscape
Mapbox
GeoCommons
CartoDB
QGIS
D3.js
threejs
Raphael
Processing 2
NodeBox
Open Refine
Excel / OpenOffice
Mr. Data Converter
DataWrangler
R-Project
Timeline
RAW
Quadrigram
Visage
Circos
Many Eyes
DataWrapper
SOFTWARE TOOLS FOR VISUALIZATION

26. TEAM
Source: Andy Kirk

27. Comparing quantitative and
categorical values
Charting hierarchical and
part-to-whole relationships
Plotting trends and changes
over time
Graphing connections and
multivariate relationships
Mapping spatial data
DIFFERENT CHART TYPES

28. Make decisions
Viewing data in context
Finding patterns
Understanding a story
Getting inspired
GOALS

29. THERE IS MORE
AND MORE DATA
COLLECTED…
WHICH IS
PROCESSED AND
ENRICHED
IN MORE WAYS
AND PRESENTED
AT MORE AND
MORE WAYS
AND STORE AT
MORE AND MORE
LOCATIONS…

30. The future of data visualization for
Governments

31. CASE:
Visualising Chicago’s mobility and
infrastructure towards a
prosperous future.
—
WEBSITE » ANALYSIS, DESIGN & DEVELOPMENT

33. Excel Tableau QGIS Processing Illustrator After Effects

40. C°F

41. The future of data visualization in
health care

42. PHILIPS: VISION OF THE FUTURE

43. PROJECT ARA

44. OXFORD NANOPORE MINION

47. The future of data visualization in
agriculture

48. DACOM

49. GROVE LABS

50. Conclusion

51. The world is changing rapidly from
generalised overviews to targeted,
personalised, localised information
From macro to micro

52. How data visualisation evolves will be
determined by the way we can access data,
and how we process & present it.
Access & presentation

53. Data visualisation is a means to an end. As
we’ve seen in all the examples, data
visualisation is just a small element in
a larger ‘system’.
Means to an end

54. We must design for the whole
ecosystem in which data ‘lives’ and
creating awareness of the whole
system to users (data literacy).
Data literacy

55. Creators need to think about the balance
between giving the full insight or just
summarise information.
Challenge for designers

56. Data visualisation professionals must do everything they
can to guide users through complexity and contribute to
the understanding of people about the world around
them.
What data visualisation can do
EXCITING TIMES!

57. @cleverfranke/cleverfranke
cleverfranke.com
THANK YOU!f