Ontologies in Data and Application Integration an Update

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Ontologies in Data and Application Integration
an Update
Kai Lin Bertram Ludäscher Knowledge-Based
Information Systems Lab Data and Knowledge
Systems (DAKS) San Diego Supercomputer
Center University of California San Diego
http//www.geongrid.org
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Outline

• Motivation
• Ontology Cheat Sheet
• Ontology-enabled Prototypes and Tools
• Data Service Registration (Structural
  Semantic)
• Scientific Workflows

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Ontology Cheat Sheet (1/2)

• What is an ontology? An ontology usually
• specifies a theory (a set of models) by
• defining and relating
• concepts representing features of a domain of
  interest
• Also an overloaded (sometimes sloppy) term for
• Controlled vocabularies
• Database schema (relational, XML, )
• Conceptual schema (ER, UML, )
• Thesauri (synonyms, broader term/narrower term)
• Taxonomies
• Informal/semi-formal representations
• Concept spaces, concept maps
• Labeled graphs / semantic networks (RDF)
• Formal ontologies, e.g., in Description Logic
  (OWL)
• formalization of a specification
• ? constrains possible interpretation of terms

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A Multi-Hierarchical Rock Classification
Ontology (GSC)
Genesis
Fabric
Composition
Texture
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Ontology Cheat Sheet (2/2)

• What are ontologies used for?
• Conceptual models of a domain or application,
  (communication means, system design, )
• Classification of
• concepts (taxonomy) and
• data/object instances through classes
• Analysis of ontologies e.g.
• Graph queries (reachability, path queries, )
• Reasoning (concept subsumption, consistency
  checking, )
• Targets for semantic data registration
• Conceptual indexes and views for
• searching,
• browsing,
• querying, and
• integration of registered data

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Application Example Geologic Map Integration
domain knowledge
Knowledge representation Ontologies!?
Nevada
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Geologic Map Integration in the Portal

• After registering datasets, ontologies (here
  classes), and an application (OMI), the
  datasets can be searched and displayed in an
  integrated way.

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Concept-Based Queries and Analysis

• After registering a source with one or more
  ontologies, concept-based queries and analysis
  can be launched
• Here light-weight client-side processing (SVG)

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Ontologies and Data Management

• Where do ontologies fit within data management
  architectures?
• Several answers, specifically
• An ontology is similar to a schema or conceptual
  model if one exists, but is
• Developed independently of a particular
  application
• Probably given in a different language
• Inherently more general
• Usually not a very good schema (weak structure)

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Ontologies and Data Management(? watch out for
Semantic Data Registration later)
Ontology
use concepts from (explicitly or implicitly)
Design Artifact
Conceptual Model
Conceptual Model
Schema
Schema
Schema
Schema
? Metadata
Data
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Creating and Sharing Concept Maps (here
Seismology concept map Cmap tool)

• Lock up scientists for 2 days
• Add CS/KRDB types
• Create concept maps
• Refine
• Iterate
• ? from napkin drawings, to concept maps, to
  ontologies

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Graph (RDF) Queries on Ontologies
visualisation
RQL Query Show all products
Query Results
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Community-Based Ontology Development

• Current concept maps and
• emerging ontologies
• Igneous Rocks/Plutons
• Seismology
• Geochemistry

• Draft of a geochemistry ontology developed by
  scientists

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Protégé ( not so ezOWL yet)
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Sparrow (a poor mans OWL tool )

• Simple ASCII-based RDF and OWL entry and
  manipulation

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Semantic Data Registration(joint work w/ Shawn
Bowers)
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What is Data/Ontology/ Registration?

• A mechanism by which data sources, ontologies,
  services,
• are published in a repository/registry
• for the purpose of smart discovery, querying,
  integration

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Things to Register

• Data files (individual files)
• Shapefile as a blob ( file type)
• Collections (of files nested eg satellite data)
• Databases (has schema and can be queried)
• Shapefile with schema registered
• Ontologies
• Services (web grid services)
• Other/external applications

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Connecting Datasets to Ontologies
Ontology (snippet)
How can we register the dataset to concepts in
the Ontology?
Dataset
Date Site Transect SP_Code Count
2000-09-08 CARP 1 CRGI 0 2000-09-08 CARP 4
LOCH 0 2000-09-08 CARP 7 MUCA 1
2000-09-22 NAPL 7 LOCH 1 2000-09-18 NAPL 1
PAPA 5 2000-09-28 BULL 1 CYOS 57
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Step1 Selecting Relevant Concepts
Concepts from an Ontology

• DataCollectionEvent
• AbundanceCollectionEvent

• Measurement
• Abundance
• SpeciesAbundance

• MeasurementContext

• Location
• LTERSite
• SBLTERSite
• naples

• MeasurableItem
• SpeciesCount

• Species

Dataset
Date Site Transect SP_Code Count
2000-09-08 CARP 1 CRGI 0 2000-09-08 CARP 4
LOCH 0 2000-09-08 CARP 7 MUCA 1
2000-09-22 NAPL 7 LOCH 1 2000-09-18 NAPL 1
PAPA 5 2000-09-28 BULL 1 CYOS 57
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Step1 Selecting Relevant Concepts
Concepts from an Ontology

• DataCollectionEvent
• AbundanceCollectionEvent

• Measurement
• Abundance
• SpeciesAbundance

• MeasurementContext

• Location
• LTERSite
• SBLTERSite
• naples

• MeasurableItem
• SpeciesCount

• Species

Dataset
Date Site Transect SP_Code Count
2000-09-08 CARP 1 CRGI 0 2000-09-08 CARP 4
LOCH 0 2000-09-08 CARP 7 MUCA 1
2000-09-22 NAPL 7 LOCH 1 2000-09-18 NAPL 1
PAPA 5 2000-09-28 BULL 1 CYOS 57
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Step2 Generate Object Model
Concepts from an Ontology

• DataCollectionEvent
• AbundanceCollectionEvent

• Measurement
• Abundance
• SpeciesAbundance

• MeasurementContext

• Location
• LTERSite
• SBLTERSite
• naples

• MeasurableItem
• SpeciesCount

• Species

Abundance Collection Event
contains
measureOf
SpeciesAbundance
SpeciesCount
hasSpecies
hasValue
hasUnit
Species
RatioUnit
RatioValue
hasTime
hasLoc
DateTime
SBLTERSite
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Applications of Semantic Registration

• Mentioned before
• Smart data discovery, integration etc.
• New application
• Generating data transformation semi-automatically
  for chaining together computational services

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Problem Service Reusability

• Unless designed to fit, independent services
  are structurally incompatible
• Generally, the source output type will not be a
  subtype of the target input type

Incompatible
StructuralType Pt
StructuralType Ps
(?)
Desired Connection
Source Service
Target Service
Pt
Ps
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Service Reusability

• A data transformation mapping (?) is required to
  connect the services artificially creating
  subtype compatibility
• If such a ? exists, the services are
  structurally feasible

Incompatible
StructuralType Pt
StructuralType Ps
(?)
?
?(Ps)
Desired Connection
Source Service
Target Service
Pt
Ps
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Service Reusability

• Idea
• annotate services with semantic types (concept
  expressions) primarily for discovery of services

Ontologies (OWL)
Compatible
(?)
SemanticType Ps
SemanticType Pt
Desired Connection
Source Service
Target Service
Pt
Ps
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Service Reusability

• Services can be semantically compatible, but
  structurally incompatible

Ontologies (OWL)
Compatible
(?)
SemanticType Ps
SemanticType Pt
Incompatible
StructuralType Pt
StructuralType Ps
(?)
?
?(Ps)
Desired Connection
Source Service
Target Service
Pt
Ps
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The Ontology-Driven Framework (work w/ Shawn
Bowers, SEEK)
Ontologies (OWL)
Compatible
(?)
SemanticType Ps
SemanticType Pt
Registration Mapping (Input)
Registration Mapping (Output)
StructuralType Pt
StructuralType Ps
Correspondence
?(Ps)
Generate
Source Service
Target Service
Transformation
Pt
Ps
Desired Connection
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Example Generated Data Transformation (in XQuery)

• Based on the structural correspondences and
  certain assumptions, we derive the transformation
  query

ltcohortTablegt for s in /population/sample
return ltmeasurementgt for c in
s/meas/cnt return ltobsgtc/text()lt/obsgt
for l in s/lsp return ltphasegtl/text()lt/pha
segt lt/measurementgt lt/cohortTablegt
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Scientific Workflows(Efrat Jaeger et al.)
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Reverse Engineering a Scientific Workflow using
the KEPLER Tool (Efrat Jaeger)
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A Scientific Workflow in Kepler
Extract mineral composition for row Id.
Igneous Rock Diagrams information.
Rock Name.
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A Scientific Workflow in Kepler
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A Scientific Workflow in Kepler
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Reverse-Engineered the Geological Map Integration
in Kepler
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DataMapper Sub-Workflow
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Result launched via the BrowserUI actor
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KEPLER and YOU

• Kepler
• is a community-based, cross-project, open source
  collaboration
• for minute made application integration
• using web (grid) services as basic building
  blocks
• has a joint CVS repository, mailing lists, web
  site,
• is gaining momentum thanks to contributors and
  contributions
• BSD-style license allows commercial spin-offs
• a pre-packaged, shrink-wrapped version
  (Kepler-to-GO) coming soon to a place near you

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F I N Questions?
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Additional Material
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The KEPLER GUI (Vergil from Ptolemy II)
Drag and drop utilities, director and actor
libraries.
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Running the workflow
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Distributed Workflows in KEPLER

• Web and Grid Service plug-ins
• WSDL
• ProxyInit, GlobusGridJob, GridFTP,
  DataAccessWizard
• SRB
• SSH, SCP
• Web Service Harvester
• Imports all the operations of a specific WS (or
  of all
• the WSs in a UDDI repository) as Kepler actors
• XSLT and XQuery transformers to link non-fitting
  services together
• Web Service Deployment (ongoing work)

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A Generic Web Service Actor

• Given a WSDL and the name of an operation of a
  web service, dynamically customizes itself to
  implement and execute that method.

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Set Parameters and Commit
Set parameters and commit
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WS Actor after Instantiation
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Web Service Harvester

• Imports the web services in a repository into
  the actor library.
• Has the capability to search for web services
  based on a keyword.

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Composing 3rd-Party WSs
Input of next web service
User interaction Transformations
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Providing DB Access through Kepler

• Database connection actor
• Opening a database connection and passing it to
  all actors accessing this database.
• Database query actor
• A generic actor that queries a database and
  provides its result.
• DBConnection type and DBConnectionToken
• A new IOPort type and a token to distinguish a
  database connection from any general type.

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Database Connection Actor

• OpenDBConnection actor
• Input database connection information.
• Output A DBConnectionToken, a reference to a
  database connection instance, through a
  DBConnection output port.

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Database Query Actor

• Database Query actor
• Input A query string (SQL) and a database
  connection reference.Parameters output type
  XML, Record or String.
  output each row separately or all at once.
  Process Execute query. Produce results
  according to parameters.

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Querying Example
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Resource Description Framework (RDF)

• Simple data model that consists of
• Resources (uniquely identified via URIs)
• Properties
• Values (resources or character strings)
• Data organized into triples (subject, property,
  value)

locatedIn
SonomaRegion
CaliforniaRegion
Property (Resource)
Subject (Resource)
Value (Resource)
locatedIn(SonomaRegion, California)
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RDF Schema

• Adds a set of pre-defined properties to define
  classes and properties
• Allows instances to be connected to classes
• Sub-class and sub-property (is-a) relationships

Region is a class locatedIn is a
property locatedIn connects Regions
locatedIn
Region
rdftype
rdftype
locatedIn
CaliforniaRegion
SonomaRegion
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OWL

• Adds additional pre-defined properties to further
  constrain an ontology
• (See http//www.w3.org/TR/owl-guide/)
• Note, RDF(S) and OWL use XML
• Some graphic tools exist (e.g., Protégé)

A Vintage is a class that is a subclass of an
unnamed class whose instances always have one
hasVintageYear property.
ltowlClass rdfID"Vintage"gt ltrdfssubClassOfgt
ltowlRestrictiongt ltowlonProperty
rdfresource"hasVintageYear"/gt
ltowlcardinalitygt1lt/owlcardinalitygt
lt/owlRestrictiongt lt/rdfssubClassOfgt
lt/owlClassgt
Note the uglified XML syntax The good news
meant for parsers, not humans!