ABCs of KMKnowledge visualization

Design elements towards knowledge visualization efficacy [Knowledge visualization series part 4]

This article by Hanlie Smuts is part 4 of a series of articles exploring knowledge visualization aspects from an organizational perspective.

Knowledge visualization refers to the application of visual representation techniques from multiple visualization domains aiding knowledge-intense processes such as knowledge sharing among employees in an organization. Knowledge visualization in our organizational context support you to manage and reduce complexity, and to nurture understanding. It therefore supports the creation and transfer of insights between individuals and within teams as it supports learning, communication and interaction through new approaches and techniques. In this context, knowledge visualization may provide individuals and teams with a shared syntax for representing their knowledge, as they learn about their reciprocal interdependencies. It can also contribute to address assumptions made by individuals and teams at hand over points, as it presents border lines explicitly. I shared the framework in part 1 of the series and include it here for context and to show the topic areas of the series of articles.

Key aspects for the application of knowledge visualization as an organizational knowledge sharing tool

Our focus for this part is on design elements. Design elements includes graphical excellence, legend and visual integrity. These are typical elements that relates to the interface with employees and in particular the usability of the knowledge visualization interface.

Visual integrity, points to the principle that the knowledge visualization should have uncompromising adherence to underlying knowledge and should not create a false impression or interpretation of that knowledge. The focus of graphical excellence is on usability of the visualization and ensuring that irrelevant items or decoration do not distract the target audience from the content of the topic. The legend element provides the information needed for the knowledge visualization to make sense and assists in explaining meaning and interpretation.

  1. Although you may be lured to apply an artistic perception of the knowledge that you are visualizing, ensure that the knowledge you want to share through your visualization, are not distorted.
  1. The dimensions in the knowledge visualization should be limited to the dimensions within the underlying knowledge to be shared.
  1. Ensure that your legends are undistorted and unambiguous. Leaving it open to interpretation may result in an unintended knowledge sharing outcome.

In part 5 of the series, I will describe the design principles relevant to the target audience you are creating the knowledge visualization for.

Next part (part 5): Knowledge visualization, it is about the context.

Header image source: Gerd Altmann on Pixabay, Public Domain.

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Dr Hanlie Smuts

Dr Hanlie Smuts is an Associate Professor in the Department of Informatics at the University of Pretoria since 2017. During her tenure in industry, her role aimed to deliver consistent, customer relevance across all digital touch points, to empower customers through convenient and effective self-service, and to drive growth through personalised digital offerings. Through a deeper understanding of the digital and adjacent ecosystems, she championed transformation to digital and the need for collaboration in this context. Her thorough understanding of the digital and adjacent ecosystems also enabled her to implement digital financial solutions for the mass markets in South, East and West Africa. Her current research focuses on information systems and the organisation, with particular emphasis on digital transformation, disruptive technologies (4th Industrial Revolution) and the management of big data and knowledge. The combination of these research areas enables cross-domain research in the field of knowledge visualisation as an organisational tool, as well as collaboration between human and machine knowledge (artificial intelligence and machine learning) for knowledge-related work. Dr Smuts has published several papers and book chapters in her field of study.

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