Antonio Falcao


António J. Falcăo holds a Licenciatura in Computer Science Engineering from the Faculty of Sciences and Technology of the New University of Lisbon, and a Master of Science (M.Sc.) degree in Computer Science Engineering from the same University. He is a project manager and research engineer at the CA3 Computational Intelligence Research Group at Uninova (New Technologies Research Institute) working on projects for the European Space Agency since 2002. His research interests include automated analysis of large non-categorical time series datasets. He’s looking at automatic detection of correlations and patterns within these datasets, as well as focusing on the topic of causality between these non-categorical data. He is a Certified Scrum Master, as well as having several specific training courses, including Agile Requirements Management, Agile Estimation and Planning. He also concluded Software Engineering and Quality Assurance training courses, both organized by ESA.

Interactive Visualisation Exploitation of Large Archives, Big Data Analytics for the Gaia mission

For Space sciences, most of the data leading to new discoveries are now expected to come from huge online archives. Still, in an age where automated massive data analysis is becoming mainstream, visual exploration remains essential for the understanding and critical interpretation of data and results.

Our work tackles two main challenges: how to interactively visualise very large amounts of multidimensional point-cloud data and how to perform complex selections within 3D representations. Most users will interface with large archives using normal hardware, such as desktops, laptops and mobile devices. Giving these devices the ability to explore big data in real-time must be provided by off-loading strategies implemented at the level of a visualisation server, preferably close to the archive in order to overcome bandwidth limitations. We explore strategies regarding data off-loading, details on demand, sub-sampling and dimensionality reduction.

The second challenge handles the issue of interpreting user interaction and providing mechanisms for complex 3D selections. We consider how widespread 3D interaction devices such as the Microsoft Kinect and more recently the Leap Motion may eventually be used to navigate the data and create spatial selections in conjunction with the normal keyboard and mouse interfaces.

We will present developments within the IVELA project – a demonstrator for a 3D interactive environment for visualisation and selection of the archive of the European Space Agency Gaia mission. Although oriented towards research in astronomy, its design is general and suitable for the visualisation of other large datasets of multidimensional point sources.


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