Towards a Structural Framework for Explicit Domain Knowledge in Visual Analytics
This work addresses the need for better support for clinicians and analysts handling complex healthcare data, but it is incremental as it builds on existing theoretical discussions without introducing a new paradigm.
The paper tackles the lack of a generalized structural framework for integrating explicit domain knowledge in visual analytics, proposing a model based on linked data and demonstrating its applicability in a physiotherapy environment.
Clinicians and other analysts working with healthcare data are in need for better support to cope with large and complex data. While an increasing number of visual analytics environments integrates explicit domain knowledge as a means to deliver a precise representation of the available data, theoretical work so far has focused on the role of knowledge in the visual analytics process. There has been little discussion about how such explicit domain knowledge can be structured in a generalized framework. This paper collects desiderata for such a structural framework, proposes how to address these desiderata based on the model of linked data, and demonstrates the applicability in a visual analytics environment for physiotherapy.