Coastal Atlas Interoperability - Ontologies

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Coastal Atlas Interoperability - Ontologies

• Luis Bermudez
• Stephanie Watson
• Marine Metadata Interoperability Initiative

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Day 1
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Preparation
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Pre-paration (5 min)

• Create groups of 2.
• Every group will have a number (X)
• Your working ontology will be aX.owl
• Example Group 10 should work on a10.owl
• One group will also be the super atlas master
  group - so they will add resources to this
  ontology if needed. (more later)

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Pre-paration (10 min)

• Make sure that
• CMAP works
• TopBraidComposer works
• You can access the SVN repository

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CMAP

• tool to create concept maps

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TopBraidComposer (TBC)

• TBC is a tool to develop Semantic Web ontologies
  and semantic applications in RDF
• Walk through the help system and Ch 3. of the
  tutorial

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Help in TopBraidComposer

• Configuring Help
• Click on Help / Help Contents
• Click on Search Scope hypertext
• Click on New
• Give a name e.g. TopBraid
• Select TopBraid Composer
• Click OKs

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Subversion (SVN)
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Introduction to Subversion (SVN)

• an open source version control system
• allows users to keep track of changes made over
  time to any type of electronic data
• typical uses are versioning source code, web
  pages or design documents

• Used in this tutorial to publish ontologies...
  simulating a distributed environment

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Check that SVN is Installed in TBC

• Window Menu
• Show View
• Other

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Should See the SVN Repository Folder
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If not, install SVN plugin

• Help Menu
• Software Updates
• Find and Install

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• Click on new features
• Check subclipse update site box
• Click on new remote site

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• Type URL of the SVN plugin and follow instructions

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Create Project from SVN Repository

• Window Menu
• Show View
• Other

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• Select SVN Repository

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• A view titled SVN Repository should have
  appeared.
• Right click and select
• New
• Repository Location

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• Type the following URL https//ont.googlecode.com
  /svn/trunk/ and click on Finish
• User mmidemo
• Password j6x4e4b8

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• Right click on ont-coastal folder
• Choose Checkout
• Accept permanently

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• Checkout and create a new project, for example,
  ont-coastal
• You should have a project with the ontologies
  available

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SVN Operations
Explore changes
Publish changes
Update the files in your local directory
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Overview

• Goals
• Introduction to Ontologies
• Ontology Components and Practical Exercise
• Advanced Ontology Concepts
• Mappings
• Restrictions and Description Logic
• SPARQL and Rules
• MMI Tools
• Ontology Engineering
• Interoperability Demonstration
• Discussions

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Overview

• Goals
• Introduction to Ontologies
• Ontology Artifacts and Practical Exercise
• Querying Ontologies with SPARQL
• Advanced Ontology Concepts
• SKOS, Thesauri, and VINE
• Interoperability Demonstration
• Discussions

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Goals

• Gain an understanding of controlled vocabularies
  (CVs) and ontologies
• Hands on experience developing ontologies
• Learn enough to write proposal to go further
• Have fun

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Introduction to Ontologies (20 min)Semantic
Interoperability Problems

• Semantic Interoperability
• Controlled Vocabularies
• Ontologies, RDF, OWL etc..

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Interoperability
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Diversity
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Making Connections
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Confusion
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What happens if we are not semantically
interoperable ?

• We cannot find all the data that we are seeking.
• p. 41 of Workshop 1 report Terminology used to
  describe similar data can vary between
  specialties or regions, which can complicate data
  searches and data integration.
• We get too many results and they are hard to
  classify.

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Information Overload
Need Categorizations ...
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Cant find all the data
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Semantic Interoperability Problem Cant find all
the data
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Information Overload
Need Categorizations ...
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Semantic Interoperability ProblemInformation
Overload
Need Categorizations ...
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Agreements on content help solve semantic
interoperability problems.Ontologies could be a
mechanism
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Ontologies facilitate agreement on

• controlled vocabularies
• mappings
• categories
• knowledge of a domain

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Controlled Vocabularies (CVs) What are they?

• a set of restricted words, used by an information
  community when describing resources or
  discovering data
• prevents misspellings and avoids the use of
  arbitrary, duplicative, or confusing words that
  cause inconsistencies when cataloging or
  searching data.
• For example
• Glossary, dictionary
• Classifications and categories
• Relationship categories

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Examples of CVs in Use SeaDataNet -
http//www.seadatanet.org
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Examples of CVs in UseConsortium of
Universities for the Advancement of Hydrologic
Science (CUAHSI) http//www.cuahsi.org
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Examples of CVs in UseOGC URN Resolver
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SOAP WSDL
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• It is not always possible to agree
• on one and only one vocabulary

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Introduction to Ontologies

• In computer science -- an explicit and formal
  specification of mental abstractions, that
  conforms to a community agreement about a domain
  and design for a specific purpose (Gruber, 1993).
• Representation, in a machine-readable language,
  of terms important to a domain of interest (e.g.,
  coastal management). An ontology contains
• classes (concepts),
• individuals (members of the classes), and
• properties (relationships between individuals)

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Ontologiesfacilitate agreement on

• controlled vocabularies
• mappings
• categories
• knowledge of a domain

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Interoperability
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Ontologies facilitate agreement on

• controlled vocabularies
• mappings
• categories (is a type of mapping -gt )
• knowledge of a domain

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Categories Example - Oregon Coastal Atlas

• Example Oregon Atlas

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Ontologies facilitate agreement on

• controlled vocabularies
• mappings
• categories
• knowledge of a domain

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Knowledge Domain Representation
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OntologiesGood for Expressing Formally

• controlled vocabularies
• mappings
• categories
• knowledge of a domain

how ?

• formal
• machine friendly

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FormalRDFResourceDescriptionFramework
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RDF
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RDF Simple Graph Model
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RDF
feature of interest
http//geonames.usgs.gov/ pls/gnispublic/f?23432
2
http//marinemetadata.org/ platformMooredBuoy
platform
observed property
define in
bounded by
http//marinemetadata.org 9600/oostethys/sos
http//marinemetadata.org/cf sea_water_temperatur
e
crs
value
urnogcdefcrsEPSG6.54329
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URI
Most fundamental web stuff

• http//somehost/absolute/URI/resource.jpg
• ftp//somehost/resource.txt
• urnissn1535-3613
• mailtoinfobot_at_ex.com?subjectsuscribe
• SIN//16137224697

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RDF Serialization

• RDF/XML
• Turtle
• N3
• N-Triple
• ...

RDF is graph model that could be stored in
different formats
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Ontologies .. good for expressing formally

• controlled vocabularies
• mappings
• categories
• knowledge of a domain

how ?

• formal
• machine friendly

how ?

• RDF
• Web Resources

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Ontology Web Language IOWL) (OWL)

• RDF/XML is the syntax
• is a representation language for ontologies
• extends RDFS by allowing representation of more
  complex relationships and more precise
  constraints on classes and properties
• uses URIs
• is the lingua franca of the Semantic Web

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BREAK !

• Next SeaDataNet use case (Roy Lowry)

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SeaDataNet Ontology Use Case
Coastal Atlas Interoperability Workshop,
Corvallis, July 17-19 2007
( Lessons Learned)

• Roy Lowry
• British Oceanographic Data Centre

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Summary

• What is SeaDataNet?
• Some SeaDataNet semantic issues
• What has SeaDataNet done?
• What is SeaDataNet going to do?
• Is SeaDataNet relevant to CAI?

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What is SeaDataNet?

• SeaDataNet in a Nutshell
• Combine over 40 oceanographic data centres across
  Europe into a single interoperable data system
• Approach is to adopt established standards and
  technologies wherever possible
• Two phases
• One brings 12 centres together with centralised
  metadata and distributed data as files. Due fully
  operational in autumn 2008 (beta next February)
• Two introduces data virtualisation, aggregation,
  cutting and 30 more centres. Due in 2010
• Project is well on its way up the
  interoperability operational implementation curve

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SeaDataNet Semantic Issues

• The major problem facing the project is
  heterogeneous legacy content
• SeaDataNet inherited 3 independently-developed
  metadatabases
• Each is heavily populated (3000-30000 records)
• Each had its own independently developed
  controlled vocabularies
• These vocabularies
• Covered overlapping domains
• Said similar things in different ways
• Provided a shining example of how NOT to manage
  vocabularies

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Brief Diversion

• Vocabularies can have two types of governance
• Content governance
• Mechanism for making decisions on vocabulary
  population
• Expected deliverables include
• Vocabulary standards and internal consistency
• Change on a timescale matching the needs of the
  user community
• Terms with definitions!!!
• Technical governance
• Vocabulary storage, maintenance and serving
• Expected deliverables include
• Convenient access to up to date vocabularies
• Clear, rigorous vocabulary versioning
• Version history through audit trails
• Maintenance that doesnt break user systems

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SeaDataNet Semantic Issues

• Vocabulary content governance
• Done by individuals who were often inadequately
  qualified to do the job
• Metadata entry form with an Add to Vocabulary
  button used by students
• Vocabulary technical governance
• Scattered files on servers or inaccessible
  database tables
• Multiple data models (e.g. some with
  abbreviations, some without)
• No versioning
• Vocabularies updated by destructive overwrites
• Harmonisation required for related vocabularies
• Within centralised metadata
• Between partner local systems and centralised
  metadata

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What has SeaDataNet Done?

• Established content governance
• Within SeaDataNet (TTT e-mail list)
• Further afield (SeaVoX e-mail list)
• Established technical governance
• Adopted the NERC DataGrid Vocabulary Server
• Heavily defended Oracle back end
• Automated version and audit trail management
• Web Service API front end plus clients e.g.
  http//vocab.ndg.nerc.ac.uk/client/vocabServer.jsp
  
• Currently serving out 75 lists
• Established a Mapping Infrastructure
• List entries connected by SKOS RDF triples
• Operational mappings between parameter
  vocabularies (GCMD science keywords, CF Standard
  Names)

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What is SeaDataNet Going To Do?

• Harmonise centralised metadata vocabularies or
  map if too hard
• Map centralised vocabularies to partner system
  vocabularies
• Build metadata crosswalks and generators (e.g.
  from CF) that include semantics (Use case 1)
• Implement Smart Discovery for legacy plaintext.
  E,g. search for pigment, find chlorophyll (Use
  case 2)
• Establish URLs to represent vocabularies and
  individual entries delivering XML probably SKOS
  documents
• Extend mapping efforts to other areas such as
  devices
• Release a much improved Vocabulary Server API
  (mid-August)

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Is SeaDataNet Relevant to CAI?

• This workshop is about building a coastal atlas
  ontology that brings together semantic resources
  that say similar things in different ways
• The vocabulary entry semantic content may be
  different from oceanographic parameters, but the
  problem is essentially the same
• If it works for SeaDataNet it will probably work
  for the CAI community
• More important if it didnt work for SeaDataNet
  then it probably wont work for CAI

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Is SeaDataNet Relevant to CAI?

• What has worked for SeaDataNet
• The NERC DataGrid Vocabulary Server
• Content governance through a MODERATED e-mail
  list (also works pretty well for CF Standard
  Names)
• Representing vocabulary terms by URNs in metadata
  documents
• What I believe will work in the next 12 months
• Semantic interoperability through mappings
• The conceptual framework of RDF in general and
  SKOS in particular
• 21st Century tooling

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Is SeaDataNet Relevant to CAI?

• What hasnt worked for SeaDataNet
• Weak content governance
• Examples
• Terms without definitions
• Vocabularies without strict entity definitions
  populated by mixed entities e.g.
• helicopter class
• RRS Discovery instance
• Vocabularies without managed deprecation
• Poor technical governance
• Example
• A vocabulary served by
• Dynamic web page from database
• Static HTML page
• ASCII file as e-mail attachment
• Each having a different number of entries.

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Thats All Folks!

• Thank you for your attention
• Any questions?
• Morals
• Always provide definitions for your terms
• If you are going to use vocabularies to build an
  ontology make sure that they are properly governed

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Welcome back

• Recap
• Define an ontology
• Play with concepts
• Details on components of ontologies

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Ontologies .. good for expressing formally

• controlled vocabularies
• mappings
• categories
• knowledge of a domain

how ?

• formal
• machine friendly

how ?

• RDF
• Web Resources

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Ontologies basic definition
formal mechanism for

• capturing the knowledge of a domain, including
  simple controlled vocabularies
• expressing hierarchies of concepts
• interrelating vocabularies via formal mappings

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Components of an Ontology

• Classes
• Individuals
• Properties
• But first... what is a concept ?

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What is a Concept ?Graph of Concepts
Explicit representation of realities
Body of Water
LAKE
Feature
hasShape
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Concept Maps
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Warming upGraph of Concepts
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Concept Maps (10 min)

• Open CMAP tools
• Create a concept map about what you would expect
  to find on a Recreational Atlas Web site

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Concept Maps (5 min)

• In the middle of the exercise - ask about the
  treatment of nouns and verbs

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Classes

• Classes define concepts in a domain
• Nouns, boxes in previous exercise
• Classes are organized in hierarchies
• Example Habitat is super class of Wetland
• Classes are sets that contain individuals

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Individuals

• Individuals represent real objects in the domain
  in which we are interested.
• They are the members of a class.

Wetland
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Elkhorn Slough NERR
Malheur National Wildlife Refuge
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Ontology Example
GeographicFeature
Class
City
Wetland
Individual
Object Property
isLocatedIn
hasName Elkhorn Slough
hasName Monterey Area_in_skm xxx
Datatype Property
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Classes - subclasses
Geographic Feature
City
Wetland
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Individuals
GeographicFeature
Class
City
Wetland
Individual
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Properties

• Properties are relationships (loosely, verbs)
  between two individuals.
• lines in previous exercise
• 2 types
• Object Properties link an individual to an
  individual
• Datatype properties link an individual to a
  Literal (String, integer, etc..). Defined as XML
  Schema datatypes.

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Object Properties
GeographicFeature
Class
City
Wetland
Individual
Object Property
isLocatedIn
Domain of isLocatedIn
Range of isLocatedIn
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Domain and Range
City
Wetland
isLocatedIn
Class Wetland is Domain of isLocatedIn
Class City is Range of isLocatedIn
Object Properties have classes as domains Object
Properties have classes as ranges ... connect
objects, which are instances of a class
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Datatype Properties
GeographicFeature
Class
City
Wetland
Individual
Object Property
isLocatedIn
hasName Elkhorn Slough
hasName Monterey Area_in_skm 70
Domain is a class
Range is a simple type String, float, etc...
Datatype Property
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Ontology Example
GeographicFeature
Class
City
Wetland
Individual
Object Property
isLocatedIn
hasName Elkhorn Slough
hasName Monterey Area_in_skm 70
Datatype Property
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Viewing a Simple Ontology

• View an example ontology containing the Elkhorn
  Slough National Estuarine Research Reserve and
  the Malheur National Wildlife Refuge

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Open Ontology and Explore Classes

• View Classes tab
• Note icons on upper right
• create subclass
• create sibling class
• delete class
• menu triangle with different options including
  viewing the hierarchy as starting with class
  thing. This latter menu option is important,
  since this is not the default of TopBraid, but is
  a very useful way to view a class hierarchy.

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Explore Classes

• Double click on class Wetland (subclass of
  GeographicFeature) in wetlands.owl
• view class form, note annotations and axioms can
  drag and drop annotation properties onto the form
• can create subclasses by clicking on the name of
  the (super) class in the view class diagram
• see other classes and their relationships to
  (properties) this class
• view class diagram
• view instances tab, see list of instances of this
  class
• view import tab (this is where the namespaces of
  imported ontologies would appear)
• view domain tab
• view SPARQL tab Queries on your class(es)

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Create Your Own Classes
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Explore Individuals

• View instances tab
• Note the icons in the upper right. You can create
  (choosing the class to which it will belong,
  first) or delete an instance, or use the instance
  menu to accomplish such tasks as exporting the
  instances to a spreadsheet.
• Double click on the instance ElkhornSloughNERR
• View the resource form (just above the instances
  tab).
• Note the name of the instance annotations,
  properties (especially note that the property
  list for the instance will include any properties
  identified for the class of which that instance
  is a member)

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Create Individuals
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Properties

• Properties are relationships (loosely, verbs)
  between two individuals.
• lines in previous exercise
• 2 types
• Object Properties link an individual to an
  individual
• Datatype properties link an individual to a
  Literal (String, integer, etc..). Defined as XML
  Schema datatypes.

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Explore Properties

• Double click on the property hasActivity
• View properties tab (on right)
• Note icons for creating property, deleting
  property, menu triangle for creating specific
  types of properties (object, data type and
  annotation properties).
• View properties form
• Note that each property has a name, may have
  annotations, and may have axioms (e.g., domain,
  range)
• think of domain as the class that has this
  property (e.g., Wetland) and range as the valid
  value for the property (e.g., Activity)
• Note that each property can also be a(n)
• Subproperty of (properties can be hierarchical)
• Inverse of
• at the bottom, you should also see what type of
  property it is (object, datatype)

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Explore Properties

• View properties form (continued)
• Note menus on top right on the property form,
  that can
• add widget for property
• show widgets for all properties with matching
  domains,
• arrange widgets in 2 columns
• also, an inverted triangle menu with lots of
  options
• E.g., will find the property name on Google,
  Wikipedia
• E.g., will find all the usages of the property in
  your workspace, etc.)

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Create Properties
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Exercise

• (it should be 200 PM by now)

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Hands on exercise TBC
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Exploring TBC (140 - 230)

• Follow the guide TBC Getting-Started-Guide
• Lets all create a simple ontology ... follow the
  screen instructions

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Atlas Interoperability Exercise

• For any interoperability endeavor the first thing
  that should happen is getting the requirements
  right !

Use Cases
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Atlas Interoperability
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Use Case and Proposed User Interface
The topics found are the ones that will be
explicitly created as well as inferred ones
based on logic.
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Atlas OntWeb
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Note...

• Q Where is the data coming from ?
• A Distributed sources, which are simulated by
  each ontology you are creating.
• Very different from traditional databases.

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Process

1. Create person-topic ontology (- 330)
2. Break (330 - 345)
3. Map with Upper Level person-topic ontology (-
   430)
4. Publish to SVN
5. View web application - use case 1 completed !
6. Discussion (-500)
7. Map topics with Atlas Topics
8. Publish mappings

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Create a simple ontology that captures topics of
interest of persons

• Use concepts from the CMAP exercise, if possible
• Create at least
• 3 Classes (on any level)
• 1 Object Property - define domain and range
• 2 Datatypes Properties - define domain and range
• 2 Individuals for class Person, and 4 for each of
  the other classes you create
• Add properties and values to individuals. e.g.
  luis hasInterest YOGA
• For example, include as topics recreational
  concepts that you would expect to find on an
  atlas
• Have fun
• If problems occur, use help system or TBC
  tutorial. If more problems occur, raise your hand

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Make your person-topic ontology (XYZ)
interoperable with the FOAF ontology
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Interoperability
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We will make your person-topic ontology (XYZ)
interoperable with the FOAF ontology
your ontology
aX.owl
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Experts are now Atlases

• Which two groups created more topics than anybody
  else ?
• They will become atlases. They will map their
  classes and properties to a a super atlas
  ontology.
• Change the class name person to atlas to
  avoid confusion.
• Import superatlas.owl (an upper atlas ontology)
• Make your classes subclasses of Atlas, and
  Feature. Make one of your properties a subclass
  of hasFeature.
• Follow similar instructions as the other groups
  to make your ontology aligned with superatlas.owl.

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Map with Person Upper Level Ontology (foaf.owl)

• Import upper person ontology foaf.owl

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Map with person upper ontology
Make your classes as subclasses of a FOAF class.
For example if you have a class Person, make it
subclass of foafPerson
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Make one of your properties sub-properties of
foaftopic_of_interest
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Commit to SVN
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Check the web - is your filename there ? URL
is http//marinemedata.org9600/fs
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Discussion

• Did you need to do any changes to your ontology ?
• We are presenting values of instances in the web
  interface, but this is not always the case.

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Discussion

• You are a FOAF person because you created a
  statement that said that
• You foaftopic_of_interest Topic
• AND
• foaftopic_of_interest has domain foafperson
• Test it !
• Make your person class not
• a subclass of foafPerson
• Run the inference
• engine

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End Day 1

• Person (local name) with HasName property
  easier with semantically neutral key
• American vs. British English? HasLabel,
  HasLabel, HasLabel, or UKName, USName
• Reminder RDF Property is highest level, then OWL
  added new restrictions (ObjectProperty for
  individual-to-individual and DataProperty for
  linking integers, strings to individuals)
• We need to create an upper ontology
• Extract all your semantics into an ontology,
  build an upper ontology

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Examples of CVs in UseConsortium of
Universities for the Advancement of Hydrologic
Science (CUAHSI) http//www.cuahsi.org
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Day 2
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Wednesday Advanced Fun
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Recap from Yesterday

• We had an introduction to ontologies
• We had a hands on experience on linking topics
  of interest ontologies to an upper level
  ontology.

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Overview

• Goals
• Introduction to Ontologies
• Ontology Components and Practical Exercise
• Advanced Ontology Concepts
• Mappings
• Restrictions and Description Logic
• SPARQL and Rules
• MMI Tools
• Ontology Engineering
• Interoperability Demonstration
• Discussions

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Mapping ala SKOS
An RDF vocabulary for describing the basic
structure and content of concept schemes such as
thesauri, classification schemes, subject heading
lists, taxonomies, 'folksonomies', other types of
controlled vocabulary, and also concept schemes
embedded in glossaries and terminologies
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SKOS

• provides a standardized way of representing KOS,
  such as thesauri, classification schemes, and
  taxonomies
• uses RDF
• RDF vocabularies
• SKOS Core (for describing KOS)
• SKOS Mapping (for mapping between concepts -
  broad, narrow, exact match)
• SKOS Extensions

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Mapping ala SKOS

• import skos.owl
• it defines 3 convenient properties to relate
  instances

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Import the 2 atlas ontologiesthat were created
by the 2 groups
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• Make relations between your aX.owl file and one
  of the atlas files
• select one of your favorite topics in your aX.owl
  file and create an skosrelation (broad, narrow,
  exact match) to a topic from one of the atlases.
• Need to add the skosproperty in the Resource Form

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Adding SKOS Property(ies) in Resource Form
Drag and drop
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• Commit to SVN - check the web site to make sure
  your file is there
• Meanwhile, atlas experts - make SKOS type
  mappings among the terms in your atlases

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Categorization by propertiesor the world of
restrictionsor defining classes using
Description Logics (DL)
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Story...

• Facts
• We are in 2010...
• SuperAtlas is a super ontology for atlas
  features. It was signed in 2009 in Monterey by
  103 web atlas representatives.
• Each group is now an atlas and will have 4
  SuperAtlas Features available in the next 20
  minutes.

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Steps

• We will define categories as allowed in OWL-DL.
• The definitions of the categories are based on
  the SuperAtlas Ontology, which is the common
  vocabulary.
• We will run the inferencer, which will
  automatically categorize your instances.

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SuperAtlas Ontology
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Process

• Import SuperAtlas Ontology
• Create a class PersonRecreationalFeature which
  is a sub (or sub-sub) class of yourPersonConcept
  
• make it subclass of superatlasRecreationalFeature
  

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Create features (e.g. places that could appear
in an atlas)
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Add Facts about Those Features

• Relative location
• add values to isPartOf
• add an existing region
• Activities that can occur
• add an Activity
• create/add new instance

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• You should have 4 instances similar to these

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• Defining Classes using Description Logics

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Defining a Class in OWL DL

• Example Define EuropeanRegion
• All regions that are part of Europe.
• More formally

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Equivalent Restrictions
European Region
run inference
Classifies UnitedKingdom
If it is known that an individual is a European
Region, it can be inferred that it isPartOf
Europe and its also a Region AND also the
converse-- If it is known that an individual
isPartOf Europe and it is also a Region, then it
can be inferred that it is a European Region
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Subclass Restrictions
European Town
run inference
Classifies EuropeanTown
If it is known that an individual is a European
Town, it can be inferred that isPartOf a European
Region and its also a Region However, the
converse can not be inferred if it is known that
an individual isPartOf a European Region and it
is a Region that it is, in fact, a European Town
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Restriction Keywords
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Restriction Keywords (cont.)
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Complex Expressions
Example Person and hasChild some (Person and
(hasChild all Man) and (hasChild some Person))
describes the set of people who have at least
one child that has some children that are only
men (i.e., grandparents that only have
grandsons). Note that brackets should be used
to clarify the meaning of the expression.
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Restrictions Exercise
Create a WebCategory class with these
subclasses - AmericanRegion -
SwimmingPlacesInAmerica .....
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BREAK 1030-1045
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162
SPARQL AND RULES
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163
SPARQL

• Query language for RDF (similar to SQL)
• Think - triple triple triple

• How many triple matches the pattern
• x rdfstype y
• superAtlasSwimming x y
• superAtlasSwimming rdftype x

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164
SPARQL Examples

• PREFIX table lthttp//www.daml.org/2003/01/periodi
  ctable/PeriodicTablegt
• SELECT ?name ?symbol ?number ?color
• FROM lthttp//www.daml.org/2003/01/periodictable/Pe
  riodicTable.owlgt
• WHERE
• ?element tablename ?name.
• ?element tablesymbol ?symbol.
• ?element tableatomicNumber ?number.
• OPTIONAL ?element tablecolor ?color.

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Examples

• Find all the subclasses of superatlasFeature

SELECT ?subject WHERE ?subject rdfssubClassOf
superatlasFeature

• Find all the features that have an activity of
  type Sports

SELECT ?feature WHERE ?feature rdftype
superatlasFeature. ?feature
superatlashasActivity ?activity. ?activity
rdftype superatlasSports.
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Create your own queries

• ...

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Using Rules

• OWL is limited in expressiveness.
• cant combine properties (e.g., uncle is a
  composition of brother and parent)
• cant use computed values or arithmetic
  comparisons (e.g., stating that a teenager is a
  person with age between 13 and 19)
• Semantic Web Rule Language (SWRL)
• combines OWL and RuleML
• proposed to standardize the expression of rules
  in OWL
• Open ontology and view rules

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Rules

• Rule is simple If A then B or A -gt B
• Semantic Web Rule Language (SWRL)
• swrlbody -gt swrlhead
• or
• using JENA rules - very similar syntax

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Create Rules

• ensure your ontology imports these namespaces
• http//www.daml.org/rules/proposal/swrlb.owl
• http//www.daml.org/rules/proposal/swrl.owl
• SWRL rules are instances of swrlImp and can be
  created by
• Select swrlImp, edit body and head. e.g., to
  formalize the rule that says...
• (?a hasChild ?c) for swrlbody
• Parent (?a) for swrl head

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Rules Exercise

• Import jena.owl

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Configure Inferencing
1
2
3
5
4
6
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Example

• Create a rule to infer all american sports
• Create a class under WebCategories and add a
  jenaRule property (drag it)
• e.g. AmericanSports

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MMI Tools

• VOC2OWL
• to convert CVs into a common language, OWL
• VINE
• to map between CVs/ontologies represented in OWL
• SEMOR
• matches your search term to terms from other
  controlled vocabularies to find data and
  information

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Ontology Engineering
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Ontology Engineering
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(No Transcript)
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Engineering Lifecycle
From help system TobBraid Composer tutorial
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What we did ....

• Controlled Vocabularies
• your topics
• web portal controlled vocabulary
• Mappings
• among your topics and the FOAF one
• among atlas and upper atlas ontology
• Categories
• Infer hierarchies
• Knowledge of a Domain
• Formal definition of classes
• Rules expression
• MMI Tools
• Ontology Engineering

All web distributed All machine friendly
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Slides acknowledgments

• Robert Laurini INSA Lyon
• http//lisi.insa-lyon.fr/laurini
• TopBraid tutorial