Supporting Neuroscience Literature Exploration by Utilising Indirect Relations between Topics in Augmented Reality

Abstract

Neuroscientists need to analyse a large number of publications to identify potentially fruitful experiments. This task is necessary before undertaking any costly practical experiments. Exploring direct relations between topics (rather than publications), such as brain regions and brain diseases, has been shown to help neuroscientists identify fruitful experiments. In previous studies, users were able to query and visualise direct relations between topics using DatAR, an Augmented Reality prototype. Neuroscientist participants suggested that identifying previously unknown, or indirect, relations between topics could provide additional information for identifying fruitful experiments. I follow a user-centred design approach: defining functional requirements for finding indirect relations, designing interactive AR visualisations for the specified functionalities, and engaging neuroscientists in evaluating the usefulness of finding indirect relations. Neuroscientists who participated in my initial study of finding indirect relations, pointed out the potential of current indirect relations by demonstrating how indirect relations in the past may have evolved into present direct relations. This suggestion informs Study 2 on exploring publication-date dependent direct and indirect relations. Participating neuroscientists also suggested providing specific intermediate topics, such as genes, when indicating indirect relations between topics. This proposal informs Study 3 on identifying specific intermediate topics and publications indicating indirect relations. My final study will assess the usefulness of the designed DatAR in neuroscientists' daily research work for identifying potentially fruitful experiments.