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Semantic Provenance and Integration

Peter Fox and Deborah L. McGuinnessJoint work with Stephan Zednick, Patrick

West, Li Ding, Cynthia Chang, …Tetherless World Constellation

Rensselaer Polytechnic Institute

Thanks to Rob Raskin (JPL), UTEP and NASA Goddard Space Flight Center Projects funded by NSF Office of Cyberinfrastructure and NASA Advanced Information

Systems Technology

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Provenance• Origin or source from which something

comes, history of ownership, intention for use, who generated something, what is generated for, manner of manufacture, sense of place and time of manufacture, production or discovery, documented in detail sufficient to allow reproducibility

• Knowledge provenance; enrich with ontologies and ontology-aware tools

Proof Markup Language (PML)

• A new kind of linked data on the Web

• Modularized & extensible– Provenance: annotate provenance properties– Justification: encodes provenance relations– Trust: add trust annotation

• Semantic Web based

Enterprise Web

Enterprise Web

World Wide Web

D D

PMLdata

PMLdata

DD

D

PMLdata

PMLdata

…

PMLdata

D

D PMLdata

PMLdata

D

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Selected Application Drivers

Mobile Wine Agent

GILA

Combining Proofs in

TPTP

CALO

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Knowledge Provenance

In Virtual Observatories

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Intelligence Analyst Tools

PML Provenance It is about provenance concepts• URI for identifying and addressing • Declarative metadata• Taxonomy

#info1 a pmlp:Information;pmlp:hasRawString “(type TonysSpecialty SHELLFISH)” ;pmlp:hasLanguage <http://inference-web.org/registry/LG/KIF.owl#KIF> ;pmlp:hasFormat <http://inference-web.org//registry/FM/PDF.owl#PDF> ;pmlp:hasPrettyString “Tonys’ Specialty is ShellFish” ;

pmlp:hasURL “http://inference-web.org/documents/tonys_fact.kif”.

Science and data

• Science is built on verifiability and reproducibility

• As more layers are inserted between the scientists and the origin data, or when the data is out of the usual realm of familiarity– Trust must be established– Sources must be verifiable and proved– Explanations must be given and connected

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20080602 Fox VSTO et al.7

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Example Use Cases

• What was the cloud cover and atmospheric seeing conditions during the local morning of September 19, 2008 at MLSO?

• Find all good images on September 21, 2008.

• Why are the Quicklook images from September 21, 2008, 1900UT missing?

• Why does this image look bad?

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Explain Explain Explain

20080602 Fox VSTO et al.10

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Search and structured query

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Search StructuredQuery

Moving to faceted browse based on PML tags (facets), using jspace

20080602 Fox VSTO et al.13

Search

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Visual browse

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Tools

Implementation of PML model

• Retrospective – scraping the un-related sources– Needed to gain confidence and trust from the

users– PML generated after the fact (can re-generate)

which is very good at the development stage

• Proactive – PML on the fly as data passes through the pipeline– Preferred but only when model is mature

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Live demo

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Further Information

• pfox@cs.rpi.edu, dlm@cs.rpi.edu

• http://inference-web.org/

• http://tw.rpi.edu/portal/SPCDIS

• http://tw.rpi.edu/portal/MDSA

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