Introduction

Modern exoplanetary research increasingly requires combining expertise from astronomy, data science, and research software engineering. The complexity and volume of data from current and future missions demand not only robust processing techniques, but also transparent and reproducible analysis frameworks. In this context, we present a modular, open-source software framework developed to support systematic comparison of different data processing and modelling methods. Its architecture allows for flexibility, extensibility, and collaboration across disciplines.

The primary aim of this tool is to improve the reliability and interpretability of data-intensive exoplanet analysis workflows. By enabling the side-by-side application of multiple methodologies, researchers can better understand how specific assumptions and preprocessing decisions affect the outcomes of scientific inference.

Method

The framework allows researchers to create interchangeable modules covering stages such as data preparation, detrending, modelling, and parameter estimation. Each module is designed to operate independently within a defined interface, allowing researchers to substitute components and evaluate their effects on final results.

This design supports collaborative development and integration of methods by contributors with varied technical backgrounds. It facilitates comparative workflows and improves reproducibility by preserving the full sequence of processing steps used in each analysis.

As a proof of concept, the framework has been applied to the analysis of the long-period exoplanet candidate TOI-4409 b. This target was observed across 21 transits using a combination of ground-based and space-based photometric instruments, including TESS, ASTEP, CHAT, OMES, LCOGT, and PEST. The tool was used to integrate the datasets and test multiple modelling approaches in order to refine the planet’s properties. Additionally, the framework is being used in the analysis of archival TESS survey data to explore the effects of different noise-processing strategies on large-scale population-level studies.

Results

The application of the framework to TOI-4409 b demonstrated its capacity to manage multi-instrument datasets and compare model outputs under controlled conditions. The combined light curve analysis yielded updated estimates of the planet’s physical and orbital parameters, building on previos findings.

In parallel, its use in TESS archive analysis highlights the framework’s scalability and utility in benchmarking data-processing techniques across large datasets, allowing users to evaluate the impact of algorithmic variation on statistical outcomes.

Conclusion

This modular framework contributes to current efforts in research software engineering by providing a reproducible and extensible platform for astronomical data analysis. Its structure supports interdisciplinary collaboration by enabling clear communication and integration of alternative methodologies.

By presenting this tool within the EPSC-DPS community, particularly in the context of cross-disciplinary planetary science collaboration, we aim to introduce it as a useful addition to researchers' analytical toolkits, and to gather practical feedback from a diverse range of users to guide its development and ensure it aligns with real scientific needs.

How to cite: Reller, P., Waldmann, I., and Merín, B.: Building Cross-Disciplinary Collaboration in Data-Intensive Astronomy: A Modular Framework for Transparent Analysis, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-1030, https://doi.org/10.5194/epsc-dps2025-1030, 2025.

How to cite: Yip, K. H. (., Mugnai, L., Papageorgiou, A., Bocchieri, A., Faucoz, O., Syty, A., Waldmann, I., and Morello, G.: Ariel Data Challenge 2025: Advancing Exoplanetary Signal Extraction for the Ariel Space Telescope, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-1675, https://doi.org/10.5194/epsc-dps2025-1675, 2025.

A chemist, two planetary scientists, and four systems engineers walk into a room. While it sounds like the setup to a joke, this was the opening scene of a presentation I delivered at the European Space Agency entitled “MOMA: A Summary”. As a recent graduate of organic chemistry, I had been asked to explain the Mars Organic Molecule Analyser (MOMA), a complex mass spectrometer instrument on board the Rosalind Franklin rover, to a room of non-chemists. For one hour, my goal was to bridge the gap between chemistry and planetary science.

The case for chemistry in planetary science has long been made. Experiments such as the Miller-Urey experiments in 1952, which simulated early-Earth atmosphere and environment, set a historical precedent for research into prebiotic Earth – which remains a major reason for Mars exploration. Indeed, as was explained in my presentation, there is no agnostic life detection without chemistry; how can we develop instruments to detect something that might be unique to life on Earth? The answer lies in universal chemical principles, such as chirality, molecular complexity, and molecular mass. Many agnostic life detection methods may be taken advantage of with MOMA’s laser desorption and gas chromatography modes.

The main challenge lies in engaging the audience in concepts they may be unfamiliar with; not just explaining the terminology and the concepts but creating a memorable experience for long-lasting knowledge retention. In the talk, there were expected challenges in communicating rather complex chemical concepts to non-experts. I employed the use of visuals and metaphors; a gas chromatography column could be likened to a horse race.

We can correlate components of the horse race (the horses, the wind, and the track) to their chromatographic equivalents (sample, mobile phase, and stationary phase, respectively). The horses of the same colours (i.e. molecules with similar polarity) all have the same speeds on this track, meaning that we can separate out the different colours of horses, and track their arrival at the destination (mimicking the elution times of a separated sample). After the talk, this metaphor was specifically mentioned in later discussions as a helpful memory aid, due to its absurdity in this context.

Metaphors, storytelling, and analogies are all powerful tools in interdisciplinary science. Not only does this help people from different expertise understand and share knowledge, but it also facilitates scientific communication skills even within academic spaces. This case highlights the potential of creative and targeted communication in planetary sciences and across disciplines, ensuring that the base chemical knowledge vital to astrobiology is available to all who are seated at the table.

How to cite: Tacconi, B., Vago, J., and Sefton-Nash, E.: ExoMars’ MOMA: A Live Example of Interdisciplinary Communication, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-2063, https://doi.org/10.5194/epsc-dps2025-2063, 2025.