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