XML for taming data to be visualized over the Grid – within the gViz project
R&D in Grids & e-science is
transforming:- data access and
- discipline-oriented data
e.g. :- Marine XML
- Earth Science
Markup Language
- NERC Data Grid
- CCLRC Data Portal
But there is still a gap to be bridged between:multiple data formats
and models
and
Precious legacy data
multiple preferred
visualization systems
Programming script
oriented e.g. Matlab
Satellite data HDF5
MVE e.g. Iris
Explorer
New data
Joe Bloggs’ data
Applicationoriented XML
Conventional approaches:- “That’s easy, I’ll write a converter”
- “Collaborating team uses just one viz
system”
But Grid-enabled VO encourages teams that:
- form, change and disperse
- are multidisciplinary
So we would prefer to have:-
??
Toolkit e.g. VisAD,
PV3
Precious legacy data
Programming script
oriented e.g. Matlab
Satellite data HDF5
MVE e.g. Iris
Explorer
New data
Joe Bloggs’ data
Applicationoriented XML
Toolkit e.g. VisAD,
PV3
…. move from Axmxn to Bxm+Cxn+D
(and avoid making B,C,D too big)
Investigating an approach which:-
Current work, investigating:-
•Processes structure by sequence of filters
•Relies on effective coordination of filters (e.g.
skML?)
•Processes bulk data (e.g. re-sequence) as late as
possible (lazy transformation) – e.g. use handles
•Bulk data can be text-based or binary
•Uses intermediate XML-based language - e.g.
XDFor GGF’s DFDL (Data Format Definition
Language) – to express structure.
•If not XML, then expresses structure in XML as
early as possible
•Each filter should be straightforward e.g.
•Splitter/combiners; XML transforms (XSLT);
regular expressions
•Uses existing tools: e.g. XSLT, OGSA-DAI
•Each filter should be expressable as a Web/Grid
Service
Feasibility for small set of diverse data sources
and viz systems
Extent of performance loss for bulk data cf
existing alternatives
Convenience for new combination of data source
D and viz system V
Framework for processing components
Future
Feasibility and benefit for highly structured data
Xquery / XPath 2.0
Frequently updated data (simulations,
experiments)
More general metadata (not only structure)
I am interested in testing the approach
with diverse datasets.
Please contact Julian.Gallop@rl.ac.uk
e.g.
large

legacy
XML
front
end

subset
handle
intermediate

language

viz
viz
system- 
system
specific