Data-Information-Knowledge-Wisdom

Data, noun

  1. Facts.
    1. Digital quantities, characters, or symbols.
    2. Things known or assumed as fact.

Information, noun

  1. Facts provided or learned, about something or someone.
    1. Processed data.
    2. That which is conveyed or represented by a particular arrangement or sequence of things.

Knowledge, noun

  1. Facts, information and skills acquired through experience or education.
    1. The sum of what is known.
    2. Understanding, as opposed to opinion.

Wisdom, noun

  1. The quality of having experience, knowledge and good judgement.
    1. The fact of being based on sensible or wise thinking.
    2. Body of knowledge and experience.

At Design Academy Eindhoven we view design as one possible method for understanding the world. Designers process signs and transform these into meaningful objects and narratives. In doing so, they need to understand the knowledge hierarchy of data–information–knowledge–wisdom, and the role played by each in this hierarchy.

Data does not have a built-in visual form, it needs to be translated, given form, in order to become information. In information graphics or in data visualisations, data has been transformed into information. Information differs from data in that it can be useful. Knowledge is the understanding of information, through experience or education. The ability to use knowledge for the greater good is called wisdom. Wisdom requires a sense of ethics – good versus evil.

In the digital age, new technologies and tools for collecting data have emerged, such as GPS and the smartphone. These technologies allow users to map the world from the bottom-up but they have also resulted in an explosion of data depicting our individual and collective patterns of behaviour, transactions and thoughts. The visual translations of these flows of data are known as data visualisations or information graphics.

At Design Academy Eindhoven we look at data in a critical way. Data visualisations may appear to give a neutral, independent, objective, observational description but, in fact, they are constructed interpretations. At DAE we explore new forms and formats of data visualisations that acknowledge this.

DAE examples

  • Aude Prevost, Fill the Gap, Graduation project, Master Information Design, 2016

  • Kaichu Wu, Page Facts, Graduation project, Master Information Design, 2014

  • Kim Constantino, Obama–Romney, First year project, Master Information Design, 2013