Publications related to Scalable Exploration of Spatial Data in Large-Scale Scientific Simulations

Related publications (6)

DAI: How Pre-computation Speeds up Data Analysis

As data sizes continue to expand, the challenge of conducting meaningful analysis grows. Utilizing I/O (Input/Output) libraries, such as HDF5 (Hierarchical Data Format) and ADIOS2 (Adaptable IO System), facilitates the filtering of raw data, with prior res ...

Springer Science and Business Media Deutschland GmbH2024

Hybrid Simulator for Capturing Dynamics of Synthetic Populations

Michel Bierlaire, Marija Kukic

This paper presents a novel hybrid framework for generating and updating a synthetic population. We call it hybrid because it combines model-based and data-driven approaches. Existing generators produce a snapshot of synthetic data that becomes outdated ov ...

IEEE2024

Adaptive Recursive Query Optimization

Anastasia Ailamaki, Martin Odersky, Guillaume André Fradji Martres, Anna Patricia Herlihy

Performance-critical industrial applications, including large-scale program, network, and distributed system analyses, are increasingly reliant on recursive queries for data analysis. Yet traditional relational algebra-based query optimization techniques d ...

IEEE2024

A 3D indicator for guiding AI applications in the energy sector

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Alessandro Francesco Aldo Virtuani, Christian Rod, Hugo James André Quest, Marine Dominique Cauz, Fabian Heymann

The utilisation of Artificial Intelligence (AI) applications in the energy sector is gaining momentum, with increasingly intensive search for suitable, high-quality and trustworthy solutions that displayed promising results in research. The growing interes ...

2022

An End-to-End Data Pipeline for Managing Learning Analytics

Denis Gillet, Juan Carlos Farah, Sandy Ingram, Joana Catarina Soares Machado

Despite the importance of learning analytics in digital education, there is limited support for researchers in education to generate, access, and share experimental data while complying with ethical and privacy legislation. We propose a set of related tool ...

2021

Geospatial analysis of individual-based Parkinson's disease data supports a link with air pollution: a case-control study

Stéphane Joost

Background: The etiology of Parkinson’s disease (PD) remains unknown. To approach the issue of PD’s risk factors from a new perspective, we hypothesized that coupling the geographic distribution of PD with spatial statistics may provide new insights into e ...

Elsevier2021