Exploring, browsing and interacting with multi-scale structures of knowledge

TL;DR

This paper introduces a novel visualization approach for multi-scale knowledge structures using phylomemetic networks, enabling interactive exploration of complex scientific and clinical data through an open-source tool.

Contribution

It presents a new endogenous visualization method combining synchronic and diachronic views, implemented in Memiescape, for exploring reconstructed knowledge histories.

Findings

Effective visualization of multi-scale knowledge structures.

Successful browsing of scientific and clinical data histories.

Open source tool facilitates interdisciplinary knowledge exploration.

Abstract

The ICT revolution has given birth to a world of digital traces. A wide number of knowledgedriven domains like science are daily fueled by unlimited flows of textual contents. In order to navigate across these growing constellations of words, interdisciplinary innovations are emerging at the crossroad between social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct multi-level and multi-scale structures of knowledge by means of phylomemies: inheritance networks of elements of knowledge. In this article, we will introduce an endogenous way to visualize the outcomes of the phylomemy reconstruction process by combining both synchronic and diachronic approaches. Our aim is to translate high-dimensional phylomemetic networks into graphical projections and interactive visualizations. To that end, we will use seabed and kinship views to translate the multilevel and multi-scale properties of complex branches of knowledge. We will then define a generic macro-to-micro methodology of exploration implemented within an open source software called Memiescape and validate our approach by browsing through the reconstructed histories of thousands of scientific publications and clinical trials.