VESPA is a data infrastructure intended for both users and data providers, developed during the recent Europlanet 2020 and 2024 Research Infrastructure programmes. VESPA not only provides a simple way to identify and access data of interest in the field of Solar System studies, it also proposes an easy solution for small teams to share newly-derived data from a publication or a research project – a typical application is to provide access to the results of a national or European programme, which has become a systematic requirement.

VESPA relies on the infrastructure of the astronomical Virtual Observatory and enlarges its standards to support Solar System studies.

Current status: Data can be accessed by issuing standard queries from a variety of tools and interfaces. Physical and observational conditions are described using a vocabulary similar to PDS4, designed for this purpose (EPN-TAP). VESPA is an active member of the International Virtual Observatory Alliance (IVOA) and uses the astronomical Virtual Observatory infrastructure for planetary science and heliophysics [1]. EPN-TAP is an IVOA standard and has benefited from deep formal reviews [2]. Nearly 250 EPN-TAP data services of various size are declared in the IVOA registry, of which 94 are currently validated and accessible via the portal - including ESA's PSA. Data services are installed on the provider side, who keeps control of the content and accesses. Reference maps have also been converted to a mutiresolution format (HiPS) to provide the context (currently 69 maps).

An entry portal is available to issue simple queries based on this description, including cross-matches between data services (Fig. 1 — https://vespa.obspm.fr). Recent functionalities include a thumbnail gallery mode, restrictions to given science fields, and a global table of results from all services for further analysis.

Fig.1: new VESPA portal layout. Categories can be selected to speed up the query process

Other APIs provided by community python libraries (astropy, pyvo, etc) allow the user to issue more sophisticated queries, e.g., retrieving spectra of asteroids from a specific family or with given dynamic parameters.

The main VO tools have been enhanced with many new functions to help support planetary data: Aladin, AladinLite, TOPCAT, and CASSIS in particular. For instance, TOPCAT can now overplot images on 3D shape models of small bodies (Fig. 2), and AladinLite can query the USGS gazetteer of planetary nomenclature for feature names and characteristics.

Fig.2: VIRTIS cubes on 67P shape model in TOPCAT (as a point cloud)

Developments: The next upgrade of EPN-TAP (v2.1) is in progress. This version will strengthen links with astronomy, heliophysics and GIS practices.

It will also include a mapping of the vocabularies used in specific fields: planetary surfaces (STAC), small bodies (JPL SSD, SSODNet, etc), heliophysics (SPASE), radio observations, etc. This will help access existing data services in these fields from an EPN-TAP interface and vice-versa.

A workflow platform is used to install pipelines and provide run-on-demand functionalities. Assessment studies include spectral fits and classifications.

The new geospatial portal (Fig. 3) will focus on 2D geographic searches from a graphic interface. This relies on a centralised database of all metadata and footprints, and extensive use of IVOA standards: multiorder spatial footprints (MOC), mutiresolution maps (HiPS), etc. GIS footprints (geojson, kml, and shapefiles) are also supported. Such spatial queries can be combined with any other parameter to refine the result list.

Fig.3: VESPA geospatial portal (under development). Data is found inside footprints provided in various formats

How to cite: Erard, S. and the VESPA team: Virtual European Solar & Planetary Access (VESPA) 2025: Reload, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-937, https://doi.org/10.5194/epsc-dps2025-937, 2025.

The MASER (Measuring Analyzing and Simulating Emissions in Radio frequencies, https://maser.lesia.obspm.fr/) service proposes a set of tools for low frequency radio astronomy, allowing the research teams to access, dispaly, analyse, model and publish radio astronomy data products. 

Thanks to the EU-funded OSTrails project (https://ostrails.eu/), the MASER team is developing an open science pilot implementing and testing the three pillars of OSTrails:

- Plan: adopting and implementing a Data Management Plan tool, to streamline the data life cycle management and prepare the publication of the MASER datasets.

- Track: linking datasets, services, instruments, researchers and institutions in a knowledge graph, to enhance data discoverability as well as better measuring the impact of the MASER service

- Assess: design adapted FAIR evalution metrics and tests for astronomy, to assess the FAIRness of the research products published in MASER.

We present the first results of the OSTrails developments and how this applies to MASER and the astronomy community.

This project has received funding from the European Union's Horizon Europe framework programme under grant agreement No. 101130187. 

How to cite: Cecconi, B., Debisschop, L., Stoll, V., Servillat, M., Le Sidaner, P., and Savalle, R.: MASER: an Astronomy Open Science Pilot within the OSTrails project, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-756, https://doi.org/10.5194/epsc-dps2025-756, 2025.

 Introduction

The Planetary Science Archive (PSA) of the European Space Agency hosts all the data from ESA’s planetary missions. It aims to provide a single entry-point for discovering, filtering and using the data, all of which adopt the Planetary Data System (PDS) format.

In 2024 support has been added for data from two ESA-funded instruments on-board the Chang’e 6 and Peregrine-1 spacecraft.

The PSA itself has been updated with several major new features list the last EPSC.

Download manager

The PSA divides data products into two types – the primary observational data, which are the focus of the interface, and secondary (or auxiliary) products, including geometry and calibration data, documentation etc. Taking advantage of the strong links present in PDS4, the new download manager presents the user with several options to find and download these secondary products.

Display of DOI

Each PDS3 dataset and PDS4 collection in PSA are issued with a DOI. To enhance the use of these DOIs, any data products belonging to a dataset with a DOI is now presented in the user interface.

Ingestion of geometry from PDS4 labels

Due to the inhomogeneity of PDS3 geometry information, older missions archiving in PSA used an external tool called to calculate a uniform set of geometric parameters. With PDS4 this information is much more structured. As a result, several PDS4 geometry attributes matching the existing geometry data have been identified and are now automatically ingested into the PSA database, if present in a data product. As a result, they immediately benefit from the extensive geometry filtering in PSA.

In addition, footprints stored in PDS4 meta-data for supported planetary bodies are now automatically extracted and used to populate the corresponding map view, allowing search and retrieval of data by their observational footprints.

Mercury map view

After completing its last Mercury flyby, BepiColombo is on track to reach the innermost planet in late 2026. To prepare for this, the PSA now includes a Mercury map view, offering several basemaps from MESSENGER data, and taking advantage of the ingestion of geometry and footprints as described above.

Quick access to documents

The download manager now allows for users to find instrument and mission documentation for selected products. To make it even easier, the user interface now dynamically displays all such documents for a selected data product and allows them to be opened in the browser.

Integration with ESA Datalabs

ESA Datalabs is a compute platform which runs on ESA premises next to the archive data volumes and thus allows online analysis without downloading the data. A PSA Datalab was already published last year loaded with the key python software libraries used for planetary science. A new addition since then is the publication of the absolute path to each public data product in a new column in the EPN-TAP table. This table, accessible via an API, lets users query the meta-data of public products. The new column allows users in the PSA Datalab to, for example, write a Jupyter notebook that requires no knowledge of the volume and file structure, starting an analysis with a database query using the EPN-TAP API. Example notebooks are now included in the PSA Datalab to demonstrate this.

Future plans

In the coming year, the PSA team plans to give particular attention to the map view and GIS capabilities of the user interface to make them faster and more responsive. Community feedback is critical here and you are invited to contact the PSA team with your use cases so that we can design the best tool for you.

How to cite: Bentley, M., Coia, D., Cornet, T., Docasal, R., Grotheer, E., Heather, D., Lim, T., Oliveira, J., Osinde, J., Raga, F., Ramos, G., Trejo, A., and Saiz, J.: ESA’s Planetary Science Archive: what’s new, and what’s to come, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-1655, https://doi.org/10.5194/epsc-dps2025-1655, 2025.

Introduction:  SPICE is an information system the purpose of which is to provide scientists the observation geometry needed to plan scientific observations and to analyze the data returned from those observations. SPICE is comprised of a suite of data files, usually called kernels, and software -mostly subroutines [1]. The user incorporates a few of the subroutines into his/her own program that is built to read SPICE data and compute needed geometry parameters for whatever task is at hand. Some examples of geometry parameters typically computed are range or altitude, latitude and longitude, illuminations angles (phase, incidence and emission), instrument pointing and field-of-view calculations, reference frame transformations, and coordinate system conversions. SPICE is also very adept at time conversions. By combining just a few of these SPICE functions, users can compute complex quantities with only a few lines of code.

The ESA SPICE Service:  The ESA SPICE Service (ESS) leads the SPICE operations for ESA missions. The group generates the SPICE Kernel Datasets (SKDs) for missions in development (ExoMars Rover, RAMSES, Comet-Interceptor, EnVision, M-MATISSE), missions in operations (Mars Express, ExoMars 2016, BepiColombo, Solar Orbiter, INTEGRAL, JUICE and Hera) and legacy missions (Venus Express, Rosetta and SMART-1). Moreover, ESS provides SPICE support Kernels for Gaia, James Webb Space Telescope and Euclid. The generation of SKDs includes the development and operation of software to convert ESA orbit, attitude, payload telemetry and spacecraft clock correlation data into the corresponding SPICE format. ESS also provides consultancy and support to the Science Ground Segments of the planetary missions, the Instrument Teams and the science community. The access point for the ESS activities, data and latest news can be found at the following site https://www.cosmos.esa.int/web/spice. ESS works in partnership with NAIF (Navigation and Ancillary Information Facility, URL: https://naif.jpl.nasa.gov/naif/).

Status of the Kernel Datasets: The current status and latest developments of the SKDs for the before mentioned missions will be described in this contribution. In general, the ESS is reviewing the legacy and operational datasets and developing the ones for future missions. It is worth mentioning the cruise operations of JUICE now on its way to Jupiter system and the successful launch of Hera in October 2024 followed by a Deimos and Mars fly-by in March 2025.

SPICE Kernels Archived in the PSA. ESS is also responsible for the generation of PDS3 and PDS4 formatted SPICE Archives that are published by the PSA (Planetary Science Archive, URL: https://psa.esa.int/psa). ESS in close collaboration with NAIF, peer-reviews the operational kernels for the PSA [2] in order to publish being compliant with the Planetary Data System (PDS) standards and uses them in the processes that require geometry computations. The latest PDS4 SPICE Bundles are produced using the NAIF PDS4 Bundler tool [3] .

Figure 1: M-MATISSE studies geometry analysis reports for different scenario candidates.

From Concept to Legacy: SPICE has played a vital role in all ESA planetary missions, serving as a foundational tool for both planning future observations and analyzing scientific data. Even before the operational phase begins, SPICE is extensively used during Long Term Planning (LTP) to assess mission feasibility, evaluating factors such as target coverage, observation conditions, ground station visibility, illumination, power constraints, and other mission-critical events. For the most recent missions, its application has extended even earlier, into the initial stages of mission development and concept design. By modeling preliminary spacecraft configurations, potential design variations, and a range of candidate trajectories and attitude profiles within the SPICE framework, teams can extract valuable performance metrics. These insights not only help refine the mission architecture and evaluate high-level science objectives but can also directly influence spacecraft systems design, for instance, by optimizing payload placement and orientation.

Extended Services: ESS offers other services beyond the generation and maintenance of SPICE Kernel Datasets, such as instances and configuration for WebGeocalc and Cosmographia for the ESA missions, and additional software packages for geometric data exploitation.

SPICE-Enhanced Cosmographia. NAIF offers for public use a SPICE-enhanced version of the open source visualization tool named Cosmographia. This is an interactive tool devoted to 3D visualizations of celestial bodies ephemerides and shape models, spacecraft trajectories and orientations, movable parts position, and instrument field-of-views and footprints. ESS provides the framework and configuration required to load the ESA missions in Cosmographia, this contribution will demonstrate its usage for the ESA Solar System missions and how it supports critical events like the Hera Mars fly-by.

Figure 2: Hera spacecraft observations of Deimos and Mars on 12^th March 2025 during its fly-by displaying the pointing and field-of-views of Hera payload.

WebGeocalc. The WebGeocalc tool (WGC) provides a web-based graphical user interface to many of the observation geometry computations available from the SPICE APIs. A WGC user can perform SPICE computations without the need to write a program; just a web browser is required. WGC is provided to the ESS by NAIF. This contribution will outline the WGC instances for ESA missions.

References: [1] Acton C. (1996) Planet. And Space Sci., 44, 65-70. [2] Bessel, S. et al., (2017) Planet. And Space Sci. [3] Sitja, M. C. (2022) Journal of Open Source Software

How to cite: Escalante Lopez, A., Vallés, R., Andrés, R., and Arviset, C.: SPICE Status and Updates for ESA Missions, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-324, https://doi.org/10.5194/epsc-dps2025-324, 2025.

Planetary science researchers, whether making reference measurements of instrument performance or Earth analogs in a lab, or carrying out in-situ investigations around or on another body, generally focus on obtaining meaningful, high-quality results. Their output often is added to a publicly available archive, driven by funding or publication requirements. The community is becoming more aware of the effort needed to improve the usefulness and usability of their data, requiring intentional action that transforms work once destined for the library stacks into immortal data having broad reach, applicability, and use for the coming decades and beyond. 

Investing seed capital 

Creating immortal data requires a meticulous and forward-thinking approach to documentation, accessibility, and interoperability. This ensures that planetary science datasets not only serve their immediate purpose but also remain valuable resources for decades to come. Researchers must carefully construct their data with an emphasis on usability, reproducibility, and transparency, ensuring future scientists can interpret and apply these assets effectively. This should be done in partnership with the archiving agency, who can provide useful tools and consultation, and will curate these data beyond the lifetime of the researcher’s funding. The Planetary Data System (PDS), with established standards defined by its PDS4 data architecture and information model [1] provides such a framework.

Foundational to the process is the inclusion of robust metadata that serve as the structural backbone of a dataset, providing essential descriptions of experimental conditions, methodologies, instrumentation, calibration processes, and contextual background. Without detailed metadata, datasets become difficult to interpret, limiting their usability. A well-documented dataset should include comprehensive information about collection procedures, observational parameters, and any transformations or corrections applied post-collection. Additionally, metadata should be standardized across datasets to ensure consistency in archival and retrieval processes.  

Closely tied to the need for thorough and thoughtful metadata is adherence to open science principles. Preserving data using standard, non-proprietary archive formats prevents obsolescence due to outdated software dependencies. Data transformation tools can assist with maintaining compatibility with commonly used tools, enhancing accessibility and usability. The archiving agency must anticipate future technological shifts and structure their standards and tools accordingly. Beyond formats, open science principles emphasize unrestricted access to datasets. Making data available without restrictive licensing enables researchers across disciplines to leverage the data for novel discoveries and interdisciplinary applications.  

To maximize usability, datasets must adhere to FAIR principles—ensuring data is Findable, Accessible, Interoperable, and Reusable. Findability is key in ensuring that researchers can readily locate datasets relevant to their studies. This requires clear indexing, structured metadata, and search-friendly documentation. Datasets should be systematically cataloged, complete with proper identifiers and links to supplementary materials. Additionally, integrating datasets with established scientific repositories enhances discoverability. Accessibility involves making datasets easily retrievable, readable, and navigable. Much of the burden of adhering to FAIR principles falls on the archiving agency, especially beyond the conclusion of the funded research. However, the researcher must lead in the development and preparation of metadata required to support these principles. 

Researchers should also prioritize interoperability, ensuring datasets seamlessly integrate with evolving analytical methodologies. Standardized protocols for data exchange and interoperability between repositories facilitate cross-disciplinary research. In planetary science, datasets must be compatible with diverse tools used in data analysis, visualization, and modeling. Reusability underscores the importance of structuring data in a way that allows future scientists to apply it across different contexts.

Immortal data on the mission level 

Scaling creation of long-lived, impactful data to the mission level underscores the complexities involved in data preservation and accessibility. Planetary missions typically deploy multiple instruments, each managed by a specialized team focused on its specific development and research objectives. While this structure optimizes individual instrument performance and scientific output, it often results in fragmented data archives, where essential metadata for connecting observations across instruments, and even across missions, is insufficiently captured. Ideally, properly documented observations follow strict standards that expose such cross-instrument and cross-mission relationships. 

A significant challenge stems from the evolving nature of data product creation throughout the mission life cycle. During the pre-launch phase, mission teams concentrate on developing data products that are expected to be of high interest to both the operations team and the broader science community. These early-stage definitions often prioritize operational efficiency and immediate scientific goals. However, as the mission progresses, new data products emerge, sometimes out of necessity, sometimes from unexpected scientific opportunities. While some of these newly defined products find their way into formal archives, others remain confined to mission websites, where they are made available to the public in an ad hoc manner. Still others are never publicly accessible, limiting their potential contribution to future research.  

Another recurring shortfall in mission data management is the failure to capture, document, and archive materials that provide essential context such as why specific measurements were taken or particular targets were of interest. Historically, few resources have been devoted to capturing or archiving these materials. Including non-archived resources such as daily operations reports, activity plans, observation targets, and other mission records in the PDS Analyst’s Notebook [2] vastly improves accessibility and usability of landed mission archives for the broader research community. However, these materials rarely have dedicated champions advocating for their systematic capture and integration into archives alongside instrument data. Without careful documentation, metadata linking observational data to mission context, and the addition of non-traditional materials in the archive, future researchers, especially those outside the original mission team, face significant hurdles in applying archival data to new investigations.  

Conclusion 

Intentionality in data preservation does more than safeguard scientific records, it ensures that planetary science research remains a dynamic and evolving legacy. By embracing best practices in metadata structuring, accessibility, and principled archival strategies, researchers forge scientific assets with lasting significance. Immortal data empowers future scientists to repurpose archived observations, apply novel analytical techniques, and contribute to long-term planetary exploration.  

References

[1] Planetary Data System. (2025). PDS4 Information Model Specification (Version 1.26). NASA. Retrieved from https://pds.nasa.gov/datastandards/documents/im/current

 [2] Stein, T. et al. (2025) LPS LVI, abstract #2438

How to cite: Stein, T. and Hughes Touran, M.: Immortal Data: Intentional Steps to Creating a Legacy , EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-1127, https://doi.org/10.5194/epsc-dps2025-1127, 2025.

The Comet Asteroid Telescope Catalog Hunter¹ (CATCH) is a search tool for large astronomical data sets designed with small bodies in mind.  With the GUI as an extension of the API base, the CATCH service can be easily used in automated software routines. The service is cloud-deployed, and virtual machines can be scaled up to support higher user loads as needed.  CATCH was built as a service to find observations of moving targets, i.e., comets and asteroids. Use CATCH to help identify pre-discovery observations of a target, to examine past cometary activity, or to help you understand why a survey did not detect or report observations of an object. Now on its third version, CATCH service now includes capabilities to search for astrophysical datasets. It also identifies stellar sources within the images, and provides additional visualization for the viewing geometries, in addition to augmentations that increase the speed of the tool and allow for larger datasets to be added to the search tool’s database. CATCH allows for the extraction of individual exposures of specified small bodies for study from massive quantities of all-sky survey exposures. In order to accomplish the required search through the data in reasonable query-times, the team has developed novel temporal-spatial indexing techniques and database architectures.

We will discuss the current state of CATCH, and future plans for software augmentations that will allow for photometry and astrometry analysis products for users to assess the data quality on the fly and better support reporting of precovery detections to the Minor Planet Center.

¹ https://catch.astro.umd.edu/about

How to cite: Bauer, J., Kelley, M. S. P., Kim, Y., Sharkey, B., and Dailey, J.: CATCHing the Sky, EPSC-DPS Joint Meeting 2025, Helsinki, Finland, 7–13 Sep 2025, EPSC-DPS2025-1814, https://doi.org/10.5194/epsc-dps2025-1814, 2025.