Brainiac: a Graph-Based Literature Visualization

Nowadays, users face the problem of too much information available. A user trying to research into a new topic will face a collection of context-specific documents, and exploring this collection may require knowledge on specific concepts that is only available with more experienced users. In this work, we address this problem, in the neuroscience context, creating a visualization, in collaboration with Instituto de Biofı́sica e Engenharia Biomédica (IBEB), that helps users analyzing a collection of documents, indicating documents that may be similar. The developed visualization has potential to help users in this context, by interacting with different views, it allows to combine a document search by similarity and by different topics. We conducted an evaluation, to measure the usability of the developed application, and its utility, to validate the data visualized. The results from the usability test were very good, with no obvious interface problem. Validation of the processed data also show good results, with room for improvement with some errors detected in text processing.