HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

ESASky 7 featuring FITS support, projections, and a Time-Series Visualiser

Projections, FITS, and HiPS FITS, are now available in ESASky, thanks to Aladin Lite 3. You can also continue where you left off with the new User Area. Save and restore sessions, upload your own data, and customise the layout to get the most out of ESASky.

In addition, we recently released a multi-mission, multi-object Time-Series Visualiser. It lets you quickly combine and inspect time-series data from different missions and observations. This first release will soon have even more features and support an ever-increasing number of missions. Continued IVOA standardisation of time-series data is greatly appreciated!

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

MIVOT updates

I will review the status of the various tools related to the MANGO/MIVOT ecosystem (services, validator, PyVO...)

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

HiPS2MOC, generating MOC from constraints on HiPS values.

This new service allows one to generate the MOC corresponding to a set of constraints on the HiPS tiles values. For instance, one can easily ask for questions like "what is the coverage of GALEX NUV pixels with a flux greater than 10 Jy/steradian?" or "give me the MOC of Mars locations with an elevation greater than 6000 meters (using MOLA DEM HiPS data) ?

HATS: Hierarchical Adaptive Tiling Scheme (nee HiPSCat)

We'll briefly discuss the progress on HATS, a Parquet-based partitioned format for distribution of very large sky catalogs. Since the Sydney presentation, we have completed the work on shuffle-free cross-matching, worked on improving the compatibility with HiPS, and the ecosystem of tools and datasets has grown. We're also working towards being ready to deploy early Rubin datasets in HATS mid next year

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.

VOTable Metadata for Parquet

Parquet is becoming an important format for bulk data storage and processing, but it lacks rich metadata. There has been some work on combining it with VOTable to make up for that. I will review existing proposals and implementations and suggest next steps towards standardisation.