How to Improve Utilizing Neural Interface by Means of Ontology-Driven Scientific Visualization Tools

Abstract

The technological progress in the field of Brain-Computer Interface and its integration with IoT have now put on the agenda the question of the fast transition of the technology from laboratory experiments into everyday life. The paper presents an approach to improve utilizing neural interface with the help of ontology-driven scientific visualization tools taking into account the urgent problems of automatic adaptation to the specifics of different IoT infrastructure, models and datasets. Some issues of replicability and reproducibility of experiments are also under discussion in this paper. Using the principles of "clean-room reverse engineering" methodology to rewrite existing EEG device drivers we make it possible to embed visualization tools which dynamically render the streaming data coming from different EEG devices within a diverse IoT infrastructure without any legal complications.

Feature analysis of ontology visualization methods and tools

“…The plug-ins are used to visualize the taxonomical structure, relations and axioms of ontology. In this section, visualization plug-ins used in Protégé [20], NeOn Toolkit [21], SWOOP [22] and ONTOLIS [23] ontology editors is described.…”