Discover and access data for your solar and planetary science research

The VESPA Portal provides access to many observational, modeling, and laboratory data services related to the field of planetary science, heliophysics and exoplanets.

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Key Features

Query

Simousltaneoulty query all data services based on science-related parameters.

All data services are accessible through a common VO framework, which includes an EPNCore metadata dictionary allowing to perform data discovery in the Solar System related science fields. Query parameters describe data products coverage (temporal, spectral, spatial, photometric), origin (instrument, facility), content (target, physical parameters), access, and references. Learn more about EPNCore parameters.

Download

Browse data services matching your query and download data products of interest, or their metadata.

Search results for a given data service are provided as a metadata table listing data products, which includes EPNCore parameters and optional service-specific parameters. In some cases, a table can hold data by itself (typically a catalog). In all cases, a downloaded table is available in the VOTable format. Data products are available in various formats, including VO formats.

Visualise

Send data products or their metadata to third-party VO tools for advanced visualisation and analysis.

Making use of Astronomy VO standards and protocols, all data service products metadata can directly be sent to the TOPCAT application, and data products in VO formats can directly be sent to dedicated VO applications. In order to use this feature, VO tools must be installed locally on your computer. Learn more about VO tools.

Search parameters

Simousltaneoulty query all registered data services based on science-related parameters.

Target

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Target types

Planet
Natural satellites only — artificial satellites are handled though space- craft or spacejunk.
Satellite
Dwarf Planet
Asteroid
Asteroid
Comet name
Comet
refers in particular to interplanetary dust observed in context (not to samples), or to simulations (e.g., of primordial nebula). Details can be provided through target_region.
Interplanetary Medium
refers to lunar or planetary samples, to meteorites, but also to terrestrial samples, e.g., in laboratory studies.
Sample
typically used for calibration targets, and for the Sun.
Star
Exoplanet
Exoplanet

Data product types

Scalar field with two spatial axes, or association of several such fields, e.g., images with multiple color planes, from multichannel or filter cameras. Preview images (e.g. map with axis and caption) also belong here. Conversely, vectorial 2D fields are described as spatial_vector.
Image
Scalar field / rasters with two spatial axes covering a large area and projected either on the sky or on a planetary body, associated to spatial_coordinate_description and map_projection parameters (with a short enumerated list of possible values); each pixel is associated to 2D coordinates (e.g., fits with WCS). This is mostly intended to identify radiometrically calibrated and orthorectified images with complete coverage that can be used as reference basemaps, but this also includes HiPS.
Map
Measurements organised primarily along a spectral axis, e.g., radiance spectra. This includes spectral aggregates (series of related spectral segments with non- connected spectral ranges, e.g., from several channels of the same instrument, various orders from an échelle spectrometer, composite spectra, SED, etc).
Spectrum
Consecutive spectral measurements through time, organized primarily as a time series. This typically implies successive spectra of the same target / field of view.
Dynamic spectrum
Scalar or vectorial measurements along 1 spatial dimension, e.g., atmo- spheric profiles, atmospheric paths, sub-surface profiles, traverses
Profile
Sets of consecutive spectral measurements with 1 or 2D spatial coverage, e.g., imaging spectroscopy. The choice between image and spectral_cube is dictated by the characteristics of the instrument (which dimension is most resolved and which dimensions are acquired simultaneously). The choice between dynamic_spectrum and spectral_cube is related to the uniformity of the field of view and by practices in the science field.
Spectral cube
Scalar or vectorial measurements along 1 angular dimension, e.g., phase or polarization curves, phase functions, emission-phase function sequences... Does not handle variations along several angular axes. This is typically associated to variations in illumination angle parameters.
Photometric function
Measurements with 3 spatial dimensions, e.g., internal or atmospheric structures, including shells/shape models (3D surfaces).
Volume
Multidimensional data with 3 or more axes, e.g., all that is not described by other 3D data types such as spectral cube or volume. This is intended to accommodate unusual data with multiple dimensions. This can be used for 3D ancillary data associated to spectral cubes, e.g., providing the coordinates or illumination angles for each spectrum.
Cube
Sets of chronological 2D spatial measurements (consecutive images).
Movie
Measurements organized primarily as a function of time (with exception of dynamical spectra and movies, i.e. usually a scalar quantity). Typical examples of time series include space-borne dust detector measurements, daily or seasonal curves measured at a given location (e.g. a lander), and light curves.
Time series
Supplies to a granule providing a catalogue of object parameters, a list of features, a table of granules in another TAP service, a list of events, a list of spectral lines... The result metadata table of a service query can also be considered as a catalogue. Catalogues can be provided as VOTable (possibly containing multiple tables, although this is not supported by SAMP). It is good practice to describe the type of data included in the catalogue using a hash-separated-list (e.g., a table of spectra should be described by ca#sp, so that it will respond to a query for spectra).
Catalogue
Vector information associated to localization, such as a spatial footprints, a GIS-related element, etc — e.g. a kml or geojson file (STC-S strings are provided though the s_region parameter, though). This includes maps of vectors, e.g., wind maps.
Spatial vector
Introduces individual VOevents formatted according to IVOA standard (or possibly events with other formatting). Characteristics are provided via the event_* parameters.
Event

Scientific use cases

Explore the results of the following query examples corresponding to scientific use cases.

Titan atmosphere profiles

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Sample spectral library

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Olympus Mons images

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Mars subsurface radargram

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Mars plasma model

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Mars atmosphere profiles

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Mars atmosphere model

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Lunar geological map

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Jupiter magnetosphere

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Exoplanets catalog

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Ceres surface

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Alternative access modes

Powerful alternative access modes are available from the command line, VO tools, python, or Jupyter notebooks.

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Publish your data

Any data provider can benefit from VESPA's infrastructure by providing an EPN-TAP interface to their database and declaring their service in the registry.

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Europlanet 2024 RI has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149