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
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
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
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
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…
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!