We present a research proposal that investigates the use of 3D representations in Augmented Reality (AR) to allow neuroscientists to explore literature they wish to understand for their own scientific purposes. Neuroscientists need to identify potential real-life experiments they wish to perform that provide the most information for their field with the minimum use of limited resources. This requires understanding both the alreadyknown relationships among concepts and those that have not yet been discovered. Our assumption is that by providing overviews of the correlations among concepts through the use of linked data, these will allow neuroscientists to better understand the gaps in their own literature and more quickly identify the most suitable experiments to carry out. We will identify candidate visualizations and improve upon these for a specific information need. We describe our planned prototype 3D AR implementation and directions we intend to explore.
Maintaining an overview of publications in the neuroscientific field is challenging, especially with an eye to finding relations at scale; for example, between brain regions and diseases. This is true for well-studied as well as nascent relationships. To support neuroscientists in this challenge, we developed an Immersive Analytics (IA) prototype for the analysis of relationships in large collections of scientific papers. In our video demonstration we showcase the system's design and capabilities using a walkthrough and mock user scenario. This companion paper relates our prototype to previous IA work and offers implementation details.
Neuroscience researchers are interested in understanding relation between anatomical regions of the brain and disorders that affect them, for example. Using the topics themselves, rather than individual articles, to examine relation in a large body of literature, can provide a higher-level approach. I investigate the use of 3D representations in Augmented Reality to aid neuroscientists to explore literature and understand relations between brain-related topics, given the three-dimensional nature of the brain. Distant reading refers to comprehending the results of studies of a large number of articles, as opposed to the more common "close reading" of individual publications. For distant reading of neuroscience literature, I identify visualization and interaction design requirements. My assumption is that by providing overviews of the correlations among topics through the use of literature, these will allow neuroscientists to better understand the gaps in the literature and more quickly identify the most suitable experiments to carry out. The DatAR team at Utrecht University has created a prototype 3D AR implementation using which I have carried out two studies of a literature exploration interface. These studies showed that visualizing topics and their relation in an immersive AR environment is clear, understandable and helpful for exploring neuroscience literature. In the following, I will carry out a study that participants can make parallel query and compare the results. I will further investigate in finding indirect relations between brain regions and brain diseases. The last study will support neuroscience students to understand course material. Interface improvements are considering where necessary.
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