Scalable Science on the Web? Challenges and Possibilities Don Brutzman Modeling, Virtual...
Transcript of Scalable Science on the Web? Challenges and Possibilities Don Brutzman Modeling, Virtual...
Scalable Science on the Web?Challenges and Possibilities
Don Brutzman
Modeling, Virtual Environments and Simulation (MOVES)Naval Postgraduate School, Monterey California
NSF Workshop: Grand Challenges eScience
5 December 2001 THE MOVES INSTITUTE
Two topics (rants)
Scientific method, modeling & simulationProposed “grand challenge” for Science on Web
Enabling technologies
3D, XML languages, behaviors, networking, physics
aka large-scale virtual environments
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Some definitions
ModelRepresentation of process in real world
SimulationBehavior of a model over time
5 December 2001 THE MOVES INSTITUTE
Scientific method
For many hundreds of years, scientific method has essentially been repetition of two steps:
Theory Experiment
However, two virtual analogs now exist:
Modeling Simulation
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Typical process: hypothesize, test, repeat
Theory Experiment
Modeling Simulation
Process of scientific inquiry
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Actual practice more often a combination of each:
Theory Experiment
Modeling Simulation
Process of scientific inquiry
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Simulation advantages over experimentation
Repeatable, adjustable, low cost or “free”
Can insert various error distributions Zero-error perfect case for algorithm correctness Statistically definable for measuring variations, rigor Can be intentionally extreme to test robustness
Can predict otherwise-impossible conditions
Catastrophic failure (of simulated system) is OK
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Simulation complementing experimentation
Forward: can sometimes insert experimental data into simulations
Mix of both needed for Verification (computationally stable)Validation (predictions match measured results)
Reverse: can sometimes insert simulation data into experiments
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Most Ignored Word in Computer Science
“Science”
How many computer scientists run experiments?Fairly widespread problem / occupational hazardTry looking for Experimental Results section in
conference, journal papersMost other disciplines won’t publish without resultsHmm, what about Simulation Results sections?
and the answer is…
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Science characteristics
Theories and models tend to be disjointor at least disconnected
Assumptions, limitations and inputs of one model tend to be outputs of another modelConjectural, but experts tend to know how
contributions in their field all fit together
Biggest challenges are often cross-disciplinary
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Science characteristics
Good experimental data is usually available for theoretical modelsAt least within limited ranges of experimentsNot usually available, though (despite NSF efforts)
Simulation results crucial to conducting sciencebut simulations are rarely reported, published, linked
or re-used Interchangeability of simulations and experiments is
not supported
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proposed Grand Challenge in e-Science
Enable scalable interconnection of Science on the Web, using
theoretical models, experimental results and simulation results.
5 December 2001 THE MOVES INSTITUTE
Enabling technologies
XML schemas for Scientific languages: MathML, Chemistry ML, etc. Others possible, even experiment-specific schema Integration feasible through XML namespaces
Metadata Dublin Core, Resource Description Framework (RDF) Semantic Web enables agents and other processes
Internationalization (i18n) and Localization We also live on planet Earth, not just in U.S.A.
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Enabling technologies
X3D graphics: Web interchange for 3D modelsmodel composition occurs in virtual environments Web-adept integration with other XML languages
Behavior protocolsSo scenes, models, humans etc. (i.e. applications)
can interact
Networking infrastructureClient, server, peer-to-peer, monitoring, services
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Extensible 3D (X3D)
X3D graphics: Web interchange for 3D modelsVirtual Reality Modeling Language (VRML) 3rd generation ISO standard with XML encoding3D render hardware already deployed everywhereGet 3D models “out of box,” out of proprietary islandshttp://www.web3D.org
Deliverables:Specification Tagset
API Authoring tools
Content Conformance
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Configuring Powerpoint for 3D
Takes a few minutes of configuration to set up:
http://web.nps.navy.mil/~brutzman/Savage/ InstallingCortonaBrowserAsPowerpointControl.ppt
http://web.nps.navy.mil/~brutzman/Savage/ InstallingCortonaBrowserAsPowerpointControl.html
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online X3D/VRML example: gimbals[go to full-screen Presentation mode to activate]
[PgUp/PgDn to change viewpoints, arrow keys or mouse to rotate][PgUp/PgDn to change viewpoints, arrow keys or mouse to rotate]
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online X3D/VRML example: kelp forest[go to full-screen Presentation mode to activate]
[PgUp/PgDn to change viewpoints, arrow keys or mouse to rotate][PgUp/PgDn to change viewpoints, arrow keys or mouse to rotate]
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3D myths, enablers
File size is bigActually much smaller than video/audio, with added
benefits of interactivity and viewpoint independence
Modeling is hardData-driven autogeneration using templates works “Content is king”
Navigation interfaces are klunkyYes, sorta like hypermedia prior to NCSA Mosaic
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A simple challenge?
Goal: Clearly demonstrate XML language interoperability
Example: Collaborative visualization for cardiac diagnosis
XHTML: hypermedia web pagesSVG: Scalable Vector Graphics 2D diagramsSMIL: Synchronized Multimedia Interface Language streamsMathML: biomechanical, biochemical modelsX3D: visualize changes to 3D model of heart
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Behavior protocols
Highly specialized application-level protocols
Perhaps unique to each type of model
Examples: IEEE Distributed Interactive Simulation (DIS) protocolW3C XML Protocol (XP) work, SOAP, othersNPS Dynamic Behavior Protocol
XML-defined packet payload, can modify/replace at run time
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Network considerations, needs
Client operations: applications, obviously
Server operations: needed but typically blocked
Multicast: multiple interactions simultaneously Scalable peer-to-peer communications Area of interest management (AOIM) Robust fallback to unicast tunneling
Network monitoring Controlled, repeatable experimental environment Repeatability more important than strict causality Much bigger than 2-point optimization
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Network considerations, needs
Support services NTP for clock synchronization LDAP for directory/discovery services, e.g. VRDNS Security for signing, authenticity, etc. Repositories and archives of interoperable content
Common theme: “middleware solutions” needed but framework is the enabler, not a legislative end goal
Forcing function/goal: growth, composability and scalability matching the capabilities and growth patterns of Web
Push all the way to desktops, not just infrastructure
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Some physics considerations
Physics of interactions between models needed Important part of VR is reality, not virtual
Some intractable problems are yieldinge.g. N-N collision detection appears tractable using
variable-resolution algorithms + network partitioningShared supercomputer problems, solutions
Typically low-resolution physics on clients, then high-res physics on servers as shared resourceGood application area for reliable multicast
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Some physics considerations
Contrast in disciplines Operations Research (OR) has rigorously consistent
mathematical notation, definitions Mechanical Engineering (ME) hydrodynamics doesn’t
Progress is much harder to validate, repeat Probably typical situations for other sciences too
Backdrop of “real world” data has caught up Terrain, satellite imagery, remote sensing, etc. etc. Needs to be available on demand as initial conditions,
bounding assumptions, model/simulation/experimental data in its own right
5 December 2001 THE MOVES INSTITUTE
proposed Grand Challenge in e-Science (reprised)
Enable scalable interconnection of Science on the Web, using
theoretical models, experimental results and simulation results.
Web 3D virtual environments are where these capabilities will be most needed and most visible.
5 December 2001 THE MOVES INSTITUTE
Contact
Don Brutzman
http://web.nps.navy.mil/~brutzman
Code UW/Br, Naval Postgraduate School
Monterey California 93943-5000 USA
831.656.2149 voice
831.656.3679 fax