Download Data Visualisation / Astronomy

Data Visualisation / Astronomy
Challenges to commonality
‹ How does Astronomical visualisation
differ from others?
„ Infrastructure Requirements
‹ Grid Requirements
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Nature of Astronomical Data &
Visualisation
Largely Static
‹ 2d tables (catalogues)
‹ pixel images
‹ Metadata (some)
„ Exploration – largely visual
„ Hypothesis testing – largely mining
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Challenges
Lots of loud astronomers
„ Hard to Normalise, esp between disciplines.
Yet need to retain access to ‘raw’ data.
„ Objects move…
„ Large images / tables Æ sample, aggregate
„ Finding out about existing tools
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More Challenges
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Special Science Requirements for tools (eg finding
distances on images) Æ plugins
Noisy data (but bio / meteo have same problem)
Incomplete/high error models (bio / meteo again)
Inherent Mk 1 eyeball limitations. Solid cubes.
Make use of colours, shapes, movies. 7d on paper.
Need pre-visualisation methods AND retain
access to raw data.
Grid Requirements
Reliability – the right data to the right
machine!
„ Speed & Latency (for visualisation)
„ Collaboration (not yet)
„ Integration – access to eg stats services
„ Easy / simple controls – focus on science
not infrastructure.
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Summary
Tools exist
‹ ‘generalising’ + ‘modularisation’
„ Expertise exists – ‘synergy’ with
professional visualisors
„ Astronomy data not unique – ‘synergy’ with
other disciplines
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