Families of database schemas for Neuroscience experiments

• Grant number: 14/18216-2
• Support Opportunities: Scholarships in Brazil - Master
• Start date: November 01, 2014
• End date: January 31, 2016
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Kelly Rosa Braghetto
• Grantee: Larissa Cristina Moraes
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat, AP.CEPID

Abstract

In Neuroscience, we use several kinds of experiments to investigate the brain functioning, aiming to understand the neural structures and their relations with the body. In order to be able to reuse experimental data out of the scope of the study where they were collected, neuroscientists need to have access to data provenance information, i.e., a description of the experiment protocol and other information about its execution (such as where, when and by whom it was performed). Neuroscientists normally store experimental data as common files in a computer, without a standard format. This approach makes difficult the maintenance, recovery, sharing and reuse of data, mainly when the collected data volume starts to increase. One of the biggest challenges of creating patterns to represent and store these data is the great variability that exists in the experimental protocols in Neuroscience. This master project proposes the creation of a family of data schemas for Neuroscience experiments, which will enable us to deal with the variability of the data structures of this domain. The family may be extended by neuroscientists by means of an easily understandable notation, so that it will be able to represent new types of experiments whenever it is necessary. Based on the software product lines paradigm, we will also create a tool that generates databases to store experimental data customized for the needs of a particular laboratory or research group. (AU)