SciQLop & Speasy: Open-Source Tools for Unified Planetary and Heliospheric Data Analysis

The surge of planetary and heliospheric data from missions like MAVEN, Juno, and Solar Orbiter demands flexible, open-source tools that simplify cross-mission analysis while adhering to open science principles. SciQLop (Scientific Qt application for Learning from Observations of Plasmas) and its data engine Speasy address this challenge by enabling seamless access, visualization, and correlation of datasets from multiple servers and archives (e.g., AMDA, CDAWeb, CSA) through a modular, user-driven framework.

SciQLop, powered by Speasy, streamlines access to heterogeneous datasets with an architecture designed to easily integrate new servers or archives. Researchers can dynamically combine in-situ measurements and event catalogs (via TSCat) into interactive workflows. Key features include:

• Lightning-fast interaction: Seamless, lag-free zoom/pan keeps exploration fluid, even for gigabyte-scale datasets.
• Drag-and-drop simplicity: Build workflows, layer data, and customize plots with clicks, not code.
• Reproducible pipelines: Build custom plot panels and virtual products from shareable Jupyter Notebooks, aligning with FAIR principles.
• Event-driven analysis: Elaborate, browse or edit catalogs (e.g., CMEs, Magnetopause crossings, conjunctions, ...)

By prioritizing adaptability for established repositories like NASA’s Planetary Data System (PDS) and fostering collaborative workflows, SciQLop and Speasy empower researchers to unlock insights from planetary and heliospheric data—today and tomorrow.