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Semantically-Enabled Science Informatics: With Supporting Knowledge Provenance and Evolution Infrastructure Highlights. Deborah L. McGuinness Tetherless World Senior Constellation Chair and Professor of Computer Science and Cognitive Science

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Semantically-Enabled Science Informatics: With Supporting Knowledge Provenance and Evolution Infrastructure Highlights

Deborah L. McGuinness

Tetherless World Senior Constellation Chair and

Professor of Computer Science and Cognitive Science

(previously Acting Director of the Knowledge Systems Laboratory at Stanford University)

Joint work with Peter Fox and James Hendler

Tetherless World Constellation

Rensselaer Polytechnic Institute

McGuinness – Microsoft eScience – December 8, 2008

selected examples and foundations
Selected Examples and Foundations
  • Semantic Technologies used in eScience (currently funded)
    • Virtual Solar Terrestrial Observatory (vsto.org)
    • Semantic Provenance Capture for Data Ingest Systems (SPCDIS)
    • Semantically-Enabled Scientific Data Integration (SESDI)
    • A Community-Driven Scientific Observations Network to Achieve Interoperability of Environmental and Ecological Data
  • Semantic Foundations
    • Inference Web – Environment for Explanation, Transparency, and Trust
    • PML – Knowledge Provenance Interlingua (Proof Markup Language)
    • Ontology Environments: Ontology Repositories, Ontology Editing, Semantic Wiki (Semantic History), …
    • Scalable Web Science – New Web Science Center – part of Web Science Research Initiative, …

McGuinness – Microsoft eScience – December 8, 2008

virtual solar terrestrial observatory vsto org
Virtual Solar Terrestrial Observatory (vsto.org)
  • Interdisciplinary Virtual Observatory for searching, integrating, and analyzing observational, experimental, and model databases.
  • Subject matter: solar, solar-terrestrial and space physics
  • Provides virtual access to specific data, model, tool and material archives containing items from a variety of space- and ground-based instruments and experiments, as well as individual and community modeling and software efforts bridging research and educational use
  • 3 year NSF project; initial deployment in year 1, multiple deployments by year 2; year 3 outreach and broadening
  • While aimed at one interdisciplinary area, it also

serves as a replicable prototype for

interdisciplinary virtual observatories

  • Current NSF follow on for provenance

extension (Semantic Provenance Capture

in Data Ingest Systems)

McGuinness – Microsoft eScience – December 8, 2008

slide4
Semantic filtering by domain or instrument hierarchy

Partial exposure of Instrument class hierarchy

McGuinness – Microsoft eScience – December 8, 2008

quick look browse
Quick look browse

5

McGuinness – Microsoft eScience – December 8, 2008

20080602 Fox VSTO et al.

inference web explanation architecture
Semantic Web based infrastructure

PML is an explanation interlingua

Represent knowledge provenance (who, where, when…)

Represent justifications and workflow traces across system boundaries

Inference Web provides a toolkit for data management and visualization

Inference Web Explanation Architecture

WWW

Toolkit

Trust computation

IWTrust

OWL-S/BPEL

SDS

Trace of web service discovery

Proof Markup Language (PML)

End-user friendly

visualization

IW Explainer/

Abstractor

*

Learners

Learning Conclusions

Expert friendly

Visualization

Trust

KIF/N3

JTP/CWM

IWBrowser

Theorem prover/Rules

search engine

based publishing

Justification

SPARK-L

SPARK

IWSearch

Trace of task execution

Provenance

provenance

registration

Text Analytics

IWBase

UIMA

Trace of information extraction

McGuinness – Microsoft eScience – December 8, 2008

global view and more
Global View and More

Views of Explanation

  • Explanation as a graph
  • Customizable browser options
    • Proof style
    • Sentence format
    • Lens magnitude
    • Lens width
  • More information
    • Provenance metadata
    • Source PML
    • Proof statistics
    • Variable bindings
    • Link to tabulator

filtered

focused

global

abstraction

Explanation

(in PML)

discourse

trust

provenance

McGuinness – Microsoft eScience – December 8, 2008

provenance view
Provenance View

Views of Explanation

  • Source metadata: name, description, …
  • Source-Usage metadata: which fragment of a source has been used when

filtered

focused

global

abstraction

Explanation

(in PML)

discourse

trust

provenance

McGuinness – Microsoft eScience – December 8, 2008

conclusion and links
Conclusion and Links
  • Knowledge Provenance is growing in criticality as applications become more distributed, hybrid, and collaborative
  • Inference Web and PML provide an open infrastructure and starting point that is being used more in a wide set of applications. inference-web.org
  • Semantic eScience class link (with book to follow) http://tw.rpi.edu/wiki/Semantic_e-Science
  • Sample of implemented eScience applications using semantic technologies:
    • Interdisciplinary Virtual Observatory (VSTO): vsto.org
    • Semantic Provenance: (SPCDIS): tw.rpi.edu/wiki/SPCDIS
    • Volcano/Atmosphere/Plate tectonics (SESDI): sesdi.hao.ucar.edu/

McGuinness – Microsoft eScience – December 8, 2008

extra
Extra

McGuinness – Microsoft eScience – December 8, 2008

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