QEF ( Query Evaluation Framework )

The QEF framework provides a Query Execution Environment Framework that helps users define and execute several types of requests. By "request", we mean a set of user defined operations or functions. Our system manages the execution of the request in a distributed environment (Grid environment), the communication between query execution components, and the access to heterogeneous data sources. read more



Y-DB ( Data-driven hypothesis management and analytics )

Scientific Hypothesis form the basis of a research by specifying the problem being investigated and experiments to refute it. In computational modelling, natural phenomena are studied and their interpretation translated into a system of mathematical equations, formalising the scientific hypothesis. Upsilon-DB is an approach for managing scientific hypothesis as data. The simulation results obtained from the system of equations are loaded into the system having fundamental properties automatically computed: the corresponding phenomenon; the empirical and theoretical uncertainty. The results are loaded into a MayBMS database and are used to support scientific evolution and model tuning. read more



SimDB ( Simulation Database )

The investigation of a natural phenomenon explores its occurrence in some space-time reference frame. Typically, scientists select a set of observables that represent the phenomenon and record the latter through a spatio-time series defined by the former. Numerical Simulation reproduces a natural phenomenon by representing the space using a geometry mesh and computing the values of observables through time steps. In this work, we present SimDB, which is a system designed to manage numerical simulation data with observable values varying in space-time. We adopt a multidimensional array data model in which dimensions correspond to space, time and numerical simulation trials. The mapping of numerical simulation data to a multi-dimensional array is, however, not trivial. Particularly, for non-uniform dimensions, as is the case of irregular meshes, a naive mapping produces an extremely sparse array, jeopardising query response time. SimDB proposes technique that transforms nun-uniform dimensions in uniform one, producing compact dense regions, which are efficiently accessed by the multi-dimensional system. SimDB is built on top of SciDB to take advantage of its parallel capacity.

This project is developed in collaboration with the Inria Zenith group, in the context of the Music Project.



SAHA ( Sistema para acompanhamento holístico de atletas )

Human Centric computing is a new area that places the human being at the heart of systems' functionality. In this work we present a system of this kind that supports the follow-up of high performance athletes. The system is structured on the follow-up of variations of athlete's observable conditions in time. A mobile object trajectory conceptual model has been adapted to model the variations of observable conditions on a virtual space, which has been named metaphoric trajectories. This system enables registering and analyzing athlete's metaphoric trajectories of different observable elements, such as heartbeats, glucose, lactose, etc., and even the athlete's psychological estate. The metaphoric trajectory model supports interesting time-variation analyses that put into perspective the organic behavior of different athletes of the same discipline with impacts on athlete nutrition and training planning. This system is being used by the Brazilian Olympic Committee (COB) and will support Brazilian athlete's follow-up during the Olympic Games. read more



Constellation Queries

This software aims at exploring pattern queries on large scientific datasets. We are interested in queries specifying some kind of geometric patterns in 2D. Examples of such patterns include: Einstein Cross, Seismic dataset features, etc. The system is implemented in Apache Spark.