This presentation shows the how the data can be represented in various ways for easy interpretation of data

1. DATA VISUALIZATION
PRASAD NARASIMHAN – Software Architect

2. MEANING
• Data visualization or data visualisation is a modern
branch of descriptive statistics.
• It involves the creation and study of the visual
representation of data, meaning "information that has
been abstracted in some schematic form, including
attributes or variables for the units of information".

3. GOAL
• The main goal of data visualization is to communicate
information clearly and effectively through graphical
means.
• To convey ideas effectively, both aesthetic form and
functionality need to go hand in hand, providing insights
into a rather sparse and complex data set by
communicating its key-aspects in a more intuitive way.

4. APPLICATIONS
• Data visualization is closely related to information
graphics, information visualization, scientific visualization,
and statistical graphics.
• In the new millennium, data visualization has become an
active area of research, teaching and development
• Also been linked to enhancing agile software
development and customer engagement.

5. ANALYTIC ACTIVITIES OF DATA
VISUALISATION USERS

6. CHARTS USED FOR DATA
VISUALISATION
Name
Visual
Dimensions
Bar Chart
 length
 color
Streamgraph
 width
 color
 time (flow)

7. 
Treemap
 size
 color
Gantt Chart
 color
 time (flow)

8. Scatter Plot
 position x
 position y
 color

9. EG :Visualizing Meteorite Impacts
• The data set was provided by The Meteoritical Society, an
organization that has been documenting meteorites since
1933.
• The data set received contained :
• the name of each meteorite,
• the weight,
• the year when it fell or was found
• as well as its coordinates

10. • Concept : material of the meteorite gives some hints
about its origin,
• After some research found that the types can be
categorized into :
• ‘stony meteorite’,
• ‘stony iron meteorite’,
• ‘iron meteorites’ and
• in this case also ‘other’ which would include unknown and smaller
groups of meteorites.
• The overall dimensions included in the visualization is the
:
• types,
• the location and
• the size of the meteorites, which eventually was chosen to be
shown in the first part of the visualization on the globe.

11. • Different colors
were used to
clearly indicate
the four
categories of
meteorites and
their location
shown on a map.
• The second part
would use the
same categories
but put them in a
time perspective
and point out the
yearly amount of
meteorites and
what category
they belong to.

12. • Eventually be
projected onto a
globe showing all
the continents and
the meteorites as
different sized dots
and colors.
• To do this an
‘azimuthal’ equal
area projection was
used in D3.js that
would show all the
meteorites and
continents at once.

14. IMPORTANCE OF DATA
VISUALISATION
• When data volumes are very large, patterns can be
spotted quickly and easily.
• Visualizations convey information in a universal manner
and make it simple to share ideas with others
• It lets people ask others, “Do you see what I see?” And it
can even answer questions like “What would happen if we
made an adjustment to that area?”

15. COMMON TECHNIQUES
• Understand the data you are trying to visualize, including
its size and cardinality (the uniqueness of data values in a
column).
• Determine what you are trying to visualize and what kind
of information you want to communicate.
• Know your audience and understand how it processes
visual information.
• Use a visual that conveys the information in the best and
simplest form for your audience.

16. Modern approaches
Displaying News
Newsmap4 is an application that visually reflects the constantly changing landscape
of the Google News news aggregator. The size of data blocks is defined by their
popularity at the moment.

17. Voyage6 is an RSS-feader which
displays the latest news in the
“gravity area”. News can be zoomed
in and out. The navigation is possible
with a timeline.
Digg BigSpy8 arranges popular
stories at the top when people digg
them. Bigger stories have more
diggs.

18. Digg Stack10: Digg stories arrange
themselves as stack as users digg
them. The more diggs a story gets,
the larger is the stack.
Time Magazine16 uses visual hills
(spikes) to emphasize the density
of American population in its map.

19. CrazyEgg lets you explore the
behavior of your visitors with a
heat map. More popular sections,
which are clicked more often, are
highlighted as “warm” – in red
color.
Trendalyzer software (recently acquired by
Google) turns complex global trends into
lively animations, making decades of data
pop. Asian countries, as colorful bubbles,
float across the grid — toward better
national health and wealth. Animated bell
curves representing national income
distribution squish and flatten. In Rosling’s
hands, global trends — life expectancy,
child mortality, poverty rates – become
clear, intuitive and even playful.

20. Three Views shows three views of
the earth, in which each country is
represented by a circle that shows
the amount of money spent on the
military (size of circle) and what
fraction of the country’s earnings
that uses (colour). Compact and
beautiful presentation of data.
Elastic Lists33 demonstrates the
“elastic list” principle for browsing
multi-facetted data structures. You
can click any number of list entries to
query the database for a combination
of the selected attributes. The
approach visualizes relative
proportions (weights) ofmetadata by
size and visuzalizes
characteristicness of a metadata
weight by brightness. Author’s blog34
regularly informs about new
experiments in the area of data

21. Musiclens gives music
recommendations and presents
your current mood and musical taste
as a diagram.
Spacetime59 offers Google,
Yahoo, Flickr, eBay and images in
3D. The tool displays all of your
search results in an easy to view
elegant 3D arrangement.
Company promises that the days
of mining through pages and
pages of tiny thumbnails in an
effort to find the item you are
looking for are over.

22. Munterbund39 showcases the
results of research graphical
visualization of text similarities in
essays in a book. “The challenge
is to find forms of graphical and/or
typographical representation of the
essays that are both appealing
and informative. We have
attempted create a system which
automatically generates graphics
according to predefined rules.”