Gaia-CU9 2019-2024 (Bristol element)
Lead Research Organisation:
University of Bristol
Department Name: Physics
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Planned Impact
While the primary motivation for Gaia is to revolutionise our understanding of the Universe, Gaia is also a software and technology mission. Gaia UK technology development has two aspects. Industrial developments, for example of new classes of CCDs, ESA-funded at e2v, are already proving of wider importance, have earned the UK the Euclid contract, and are generating other new international markets. Precision control systems, and on-board real-time image processing systems (Astrium Stevenage) are intended to be applied much more widely. There are many ESA-UK industry-UK academic partnerships built on Gaia. The first Gaia data releases have underpinned significant outreach activities. The Gaia data are the basis for a range of deep learning investigations, and are being used in PhD training programmes, for instance the STFC-funded CDT network in Cambridge.
The majority of development, however, involves fast and complex processing of large data volumes, and the development of tools to allow fast public access to huge and heavily-structured data sets. This naturally builds on and expands the Big Data and Virtual Observatory developments of late. The Cambridge developments in very large database systems (Spark/Hadoop) have been adopted mission-wide, illustrating one more area of technical leadership. Gaia is the next "big beast" in data volumes, with Gaia learning experience showing applications to astronomy (Euclid/PLATO) and wider implications for science and aspects of the digital economy. Big Data problems generically involve gathering subsets of the data for further exploration and visualising those data in some fashion. The techniques already in use in TOPCAT provide some important software approaches, and the developments to be driven by this work will be applicable in other fields, for example visualising remote sensing data monitoring crop rotation, relevant to areas such as the STFC Food network.
The majority of development, however, involves fast and complex processing of large data volumes, and the development of tools to allow fast public access to huge and heavily-structured data sets. This naturally builds on and expands the Big Data and Virtual Observatory developments of late. The Cambridge developments in very large database systems (Spark/Hadoop) have been adopted mission-wide, illustrating one more area of technical leadership. Gaia is the next "big beast" in data volumes, with Gaia learning experience showing applications to astronomy (Euclid/PLATO) and wider implications for science and aspects of the digital economy. Big Data problems generically involve gathering subsets of the data for further exploration and visualising those data in some fashion. The techniques already in use in TOPCAT provide some important software approaches, and the developments to be driven by this work will be applicable in other fields, for example visualising remote sensing data monitoring crop rotation, relevant to areas such as the STFC Food network.
Publications
Taylor M. B.
(2019)
All of the Sky: HEALPix Density Maps of Gaia-scale Datasets from the Database to the Desktop
in Astronomical Data Analysis Software and Systems XXVI
Collaboration G
(2020)
Gaia Early Data Release 3: Acceleration of the solar system from Gaia astrometry
in arXiv e-prints
Collaboration G
(2020)
Gaia Early Data Release 3: Structure and properties of the Magellanic Clouds
in arXiv e-prints
Collaboration G
(2020)
Gaia Early Data Release 3: The Gaia Catalogue of Nearby Stars
in arXiv e-prints
Cecconi B
(2022)
JSON Implementation of Time-Frequency Radio Catalogues: TFCat
Lutz Katharina A.
(2022)
Spreading the Word - Current Status of VO Tutorials and Schools
in Astronomical Society of the Pacific Conference Series
Taylor M. B.
(2019)
TOPCAT and Gaia
in Astronomical Data Analysis Software and Systems XXVII
Taylor Mark
(2022)
TOPCAT Visualisation Over the Web
in Astronomical Society of the Pacific Conference Series
Collaboration G
(2019)
VizieR Online Data Catalog: Gaia DR2. Variable stars in CMD (Gaia Collaboration+, 2019)
in VizieR Online Data Catalog
Title | TOPCAT |
Description | TOPCAT is the most-used astronomical catalogue handling tool. It is extensively used to handle Gaia data and to create exploration plots of stellar populations, as well as in many other astronomical applications. It is also used for education in astronomical methods in the UK, Africa, and elsewhere. The underlying libraries are also used extensively for software developments. |
Type Of Material | Improvements to research infrastructure |
Provided To Others? | Yes |
Impact | Extensively used world-wide. |
URL | http://www.star.bris.ac.uk/~mbt/topcat/ |
Description | GAIA team |
Organisation | ESA - ESTEC |
Country | Netherlands |
Sector | Public |
PI Contribution | Taylor has written much of the database access code for end-users, including major graphical display improvements. |
Collaborator Contribution | ESA satellite project to map star positions in the Galaxy: highly successful at generating vast database, requiring our database access methodology |
Impact | Extensive database for studies of structure of Galaxy. |
Start Year | 2009 |