The creation
and study of visual representation of data is known a Data visualisation. The
main goal of data visualization is to communicate information clearly and
effectively through graphical means. An ideal visualisation should not only communicate
clearly, but stimulate viewer engagement and attention. Data visualization is
closely related to information graphics, information visualization, scientific
visualization, and statistical graphics.
There are different approaches on
the scope of data visualisation. One common focus is on information
presentation. The seven subjects of data visualisation are Mind maps,
Displaying news, Displaying Data, Displaying connections, Displaying websites,
Articles & resources, and Tools and Services. On the other hand, from a
computer science perspective, it can be categorized as Visualisation algorithms
& techniques, Volume visualisation, Information visualization, Multi resolution
methods, Modelling techniques, and Interaction techniques & architectures.
There are various visualisation
softwares available which caters to the uses of different segments of users.
Some of them are
- · Amira : For Scientists
- · Avizo : Engineers and Scientists
- · DAVIX : Security Consultant
- · Datawatch : Business users
- · Fusioncharts : Programmers
- · Gephi : Statistician
- · Tulip : Researchers and Engineers
- · Qunb : Non-expert Business users
Data presentation architecture is a skill-set that seeks to
identify, locate, manipulate, format and present data in such a way as to
optimally communicate meaning and proffer knowledge. It is the art of
discovering valuable information from data and making it usable, relevant and
actionable with the arts of data visualisation and other techniques. Data
presentation architecture is neither an IT nor a business skill set but exists
as a separate field of expertise. Often confused with data visualization, data
presentation architecture is a much broader skill set that includes determining
what data on what schedule and in what exact format is to be presented, not
just the best way to present data that has already been chosen (which is data
visualization). Data visualization skills are one element of DPA."
The main objectives of DPA are
- · To use data to provide knowledge in the most effective manner possible
- · To use data to provide knowledge in the most efficient manner possible
With the above objectives in mind, the actual work of data presentation
architecture consists of:
- · Defining important meaning (relevant knowledge) that is needed by each audience member in each context
- · Finding the right data (subject area, historical reach, breadth, level of detail, etc.)
- · Determining the required periodicity of data updates (the currency of the data)
- · Determining the right timing for data presentation (when and how often the user needs to see the data)
- · Utilizing appropriate analysis, grouping, visualization, and other presentation formats
- · Creating effective delivery mechanisms for each audience member depending on their role, tasks, locations and access to technology
