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
1
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
2
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
3
Semantic filtering by
domain or instrument
hierarchy
Partial exposure of
Instrument
class
hierarchy
McGuinness – Microsoft eScience – December 8, 2008
4
Quick look browse
5
20080602
FoxeScience
VSTO–et
al.
McGuinness
– Microsoft
December
8, 2008
5
Inference Web Explanation Architecture
WWW
SDS
OWL-S/BPEL
Trace of web service discovery
Learners
*
Proof Markup
Language (PML)
Toolkit
IWTrust
Trust computation
IW Explainer/
Abstractor
End-user friendly
visualization
Learning Conclusions
JTP/CWM
KIF/N3
Trust
Theorem prover/Rules
SPARK
SPARK-L
Trace of task execution
Justification
Provenance
Text Analytics
UIMA
IWBrowser
Expert friendly
Visualization
IWSearch
search engine
based publishing
IWBase
provenance
registration
Trace of information extraction
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
McGuinness – Microsoft eScience – December 8, 2008
6
Global View and More
Views of Explanation
filtered
focused
Explanation
(in PML)
provenance
Explanation as a graph
Customizable browser options
Proof style
Sentence format
Lens magnitude
Lens width
More information
McGuinness – Microsoft eScience – December 8, 2008
abstraction
discourse
trust
global
Provenance metadata
Source PML
Proof statistics
Variable bindings
Link to tabulator
…
7
Provenance View
Source metadata: name, description, …
Source-Usage metadata: which fragment
of a source has been used when
Views of Explanation
filtered
focused
Explanation
(in PML)
trust
McGuinness – Microsoft eScience – December 8, 2008
global
abstraction
discourse
provenance
8
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
9
Extra
McGuinness – Microsoft eScience – December 8, 2008
10
McGuinness
NSF/NCAR May 6, 2008
11
0
