Understanding Concept Maps: A Closer Look at How People Organise Ideas Open Data Collection.

Research into creating visualisations that organise ideas into concise concept maps often focuses on implicit mathematical and statistical theories which are built around algorithmic efficacy or visual complexity. Although there are multiple techniques which attempt to mathematically optimise this multi-dimensional problem, it is still unknown how to create concept maps that are immediately understandable to people. In this paper, we present an in-depth qualitative study observing the behaviour and discussing the strategy used by non-expert participants to create, interact, update and communicate a concept map that represents a collection of research ideas.

Our results show non-expert individuals create concept maps differently to visualisation algorithms. We found that our participants prioritised narrative, landmarks, abstraction, clarity, and simplicity. Finally, we derive design recommendations from our results which we hope will inspire future algorithms that automatically create more usable and compelling concepts maps better suited to the natural behaviours and needs of users.

CC-BY dataset for Understanding Concept Maps: A Closer Look at How People Organise Ideas CHI’17 Paper by Stefano Padilla is licensed under a Creative Commons Attribution 4.0 International License. Stefano Padilla, Thomas S. Methven, David A. Robb, Mike J. Chantler. 2017. Understanding Concept Maps: A Closer Look at How People Organise Ideas.

In Proceedings of the 2017 CHI ACM Conference on Human Factors in Computing Systems (CHI ’17). ACM, Denver, CO, USA. DOI: dx.doi.org/10.1145/3025453.3025977