Semantic Basics: Markup, Querying, and Reasoning

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Semantic Basics: Markup,

Querying, and Reasoning

Marlon Pierce Marlon Pierce

Community Grids Lab Community Grids Lab

Indiana University Indiana University

With Slides and Help from Sean Bechhofer, With Slides and Help from Sean Bechhofer, Carole Goble, Line Pouchard, and Dave De Carole Goble, Line Pouchard, and Dave De

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Reductio ad Absurdum



“

Physics is the study of the harmonic

oscillator.”

• H. L. Richards

H. L. Richards



“

Statistical Mechanics is the study of

the Ising Model”

• H. L. Richards

H. L. Richards



“

Web Service standards are the

study of <xsd:any> sequences”

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Which Web Service Specs?

<xs:element name="

<xs:element name="HeaderHeader" " type="

type="tns:Headertns:Header" /> " />

<xs:complexType <xs:complexType name="

name="HeaderHeader">"> <xs:sequence>

<xs:sequence>

<xs:any

namespace="

namespace="##any##any" " processContents="

processContents="laxlax" " minOccurs="

minOccurs="00" " maxOccurs="

maxOccurs="unboundedunbounded" /> " /> </xs:sequence>

</xs:sequence>

<xs:anyAttribute <xs:anyAttribute namespace="

namespace="##other##other" " processContents="

processContents="laxlax" /> " />

</xs:complexType></xs:complexType>

<xsd:complexType

name="

name="SecurityHeaderTypeSecurityHeaderType"" >

>

<xsd:sequence><xsd:sequence>

<xsd:any <xsd:any

processContents="processContents="laxlax" "

minOccurs="minOccurs="00" _"

maxOccurs="maxOccurs="unboundedunbounded">">

</xsd:any></xsd:any>

</xsd:sequence></xsd:sequence>

<xsd:anyAttribute <xsd:anyAttribute

namespace="namespace="####otherother" _"

processContents="processContents="laxlax" /> " /> </xsd:complexType>

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Which, What, and Why?



Which is what?

• Left is the definition of the SOAP header.Left is the definition of the SOAP header.

• Right is taken from Web Service Secure Messaging Right is taken from Web Service Secure Messaging Specification.

Specification.

• You will find this pattern repeated pretty often in web You will find this pattern repeated pretty often in web service specifications.

service specifications.



Why?

• We have limited ways of linking several XML schema We have limited ways of linking several XML schema data models.

data models.

 Imagine schemas for science applications and computing Imagine schemas for science applications and computing

resources.

• XML maps relationships to trees.XML maps relationships to trees.

 Link application and computer schemas with <xsd:any>.Link application and computer schemas with <xsd:any>.  In my application+computer schema, does application In my application+computer schema, does application

contain computer as child node, or vice versa?

• Graphs are a more natural way of expressing many Graphs are a more natural way of expressing many inter-relationships of concepts.

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XML is not enough



XML defines

grammars to verify

and structure

documents



The grammar

enforces constraints

on tags



Different grammars

define the same

content



XML lacks a

semantic model – it

only has a surface

model which is a

tree.

<uri> http://www.w3.org/Home/Lassila </uri> <name>Ora Lassila</name>

</Creator>

<Document uri=“http://www.w3.org/Home/Lassila” <Creator>Ora Lassila</Creator>

</Document>

“The Creator of the Resource

“http://www.w3.org/Home/Lassila” is Ora Lassila

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XML is not enough

 Meaning of XML documents is Meaning of XML documents is intuitivelyintuitively clear clear

• ““semanticsemantic” markup tags are domain terms” markup tags are domain terms

 But computers do not have intuitionBut computers do not have intuition

• Tag names Tag names per seper se do not provide semantics do not provide semantics • The semantics are encoded The semantics are encoded outsideoutside the XML the XML

specification specification

 XML makes no commitment on:XML makes no commitment on:

 Domain specific ontological Domain specific ontological vocabularyvocabulary  Ontological Ontological modeling primitivesmodeling primitives



 requires pre-arranged agreement on requires pre-arranged agreement on  & & 

Feasible for closed collaboration Feasible for closed collaboration

• agents in a small & stable communityagents in a small & stable community • pages on a small & stable intranetpages on a small & stable intranet



Semantic Web Markups often are expressed

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Enter the Semantic Web/Grid

“

The

_The

Semantic Web

_{Semantic Web}

is the

_{is the}

representation of

data

on the

World

Wide Web

. It is a collaborative

effort led by W3C with participation

from a large number of researchers

and industrial partners. It is based

on the

Resource Description

_{Resource Description}

Framework

(

RDF

), which integrates

a variety of applications using

XML

for syntax

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The Semantic Stack

XML

Defines the syntax for structured

documents.

XML

Schema

Defines rules for XML dialects (SVG,

GML, etc.) and also built-in data

types.

RDF

A data model definition language with

XML bindings

RDF

Schema

A way to define RDF-based languages

(DAML-OIL, OWL).

OWL

An extension of RDF/RDFS with

extensive property/relationship

definitions for expressing logical

relationships.

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Semantic Markups



All semantic markup languages

should be understood as

assertion

languages.

• We will assert that certain relationships

We will assert that certain relationships

between resources exist.

• We will express this using RDF, RDFS,

We will express this using RDF, RDFS,

and OWL using XML



We must still provide tools for

processing (and verifying) the

assertions.

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Resource Description

Framework

Overview of RDF basic ideas

and XML encoding.

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Resource Description Framework

(RDF)



RDF is the simplest of the semantic languages.



Basic Idea #1: Triples

• RDF is based on a subject-verb-object statement RDF is based on a subject-verb-object statement structure.

structure.

• RDF subjects are called resources (classes)RDF subjects are called resources (classes) • Verbs (predicates) are called properties.Verbs (predicates) are called properties.

• Objects (values) may be simple literals or other Objects (values) may be simple literals or other resources.

resources.



Basic Idea #2: Everything is a resource that is

named with a URI

• RDF nouns, verbs, and objects are all labeled with URIsRDF nouns, verbs, and objects are all labeled with URIs • Recall that a URI is just a name for a resource. Recall that a URI is just a name for a resource.

• It may be a URL, but not necessarily.It may be a URL, but not necessarily.

• A URI can name anything that can be describedA URI can name anything that can be described

 Web pages, creators of web pages, organizations that the Web pages, creators of web pages, organizations that the

creator works for,….

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RDF Graph Model



RDF is defined by a graph model.



Resources are denoted by ovals (nodes).



Lines (arcs) indicate properties.



Squares indicate string literals (no URI).



Resources and properties are labeled by a URI.

http://.../CMCS/Entries/X

H2O

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Encoding RDF in XML



The graph represents two statements.

• Entry X has a creator, Dr. Y.Entry X has a creator, Dr. Y. • Entry X has a title, H2O.Entry X has a title, H2O.



In RDF XML, we have the following tags

• <RDF> </RDF> denote the beginning and end of the <RDF> </RDF> denote the beginning and end of the RDF description.

RDF description.

• <Description>’s “about” attribute identifies the subject <Description>’s “about” attribute identifies the subject of the sentence.

of the sentence.

• <Description></Description> enclose the properties <Description></Description> enclose the properties and their values.

and their values.

• We import Dublin Core conventional properties (creator, We import Dublin Core conventional properties (creator, title) from outside RDF proper.

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RDF XML: The Gory Details

<rdf:RDF

xmlns:rdf='http://www.w3.org/1999/02/2

2-rdf-syntax-ns#'

xmlns:dc='http://purl.org/dc/elements/1.0

/'>

<rdf:Description rdf:about='http://.../X‘>

<dc:creator

rdf:resource='http://…/people/MEP‘/

>

<dc

:title rdf:resource='H2O'/>

</rdf:Description>

</rdf:RDF>

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Encoding RDF as Triplets



In addition to graphs and XML, RDF may

be written as triple “sentences”.



A triple is just the subject, predicate,

and object (in that order) of a graph

segment.

<http://.../CMCS/Entries/X>

http://purl.org/dc/elements/1.1/creator<

http://.../CMCS/People/DrY

>

•

This structure may look trivial but is

useful in expressing queries (more

later).

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Creating RDF Documents



Writing RDF XML (or DAML or OWL) by

hand is not easy.

• It’s a good way to learn to read/write, but after

It’s a good way to learn to read/write, but after

you understand it, automate it.



Authoring tools are available

• OntoMat: buggy

OntoMat: buggy

• Protégé: preferred by CGL grad students

Protégé: preferred by CGL grad students

• IsaViz: another nice tool with very good

IsaViz: another nice tool with very good

graphics.



You can also generate these

programmatically using Hewlett Packard

Labs’ Jena toolkit for Java.

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What is the Advantage?

 So far, properties are just conventional URI names.So far, properties are just conventional URI names.

• All semantic web properties are conventional assertions about All semantic web properties are conventional assertions about relationships between resources.

relationships between resources.

• RDFS and OWL will offer more precise property capabilities.RDFS and OWL will offer more precise property capabilities.

 But there is a powerful feature we are about to explore…But there is a powerful feature we are about to explore…

• Properties provide a powerful way of linking different RDF Properties provide a powerful way of linking different RDF resources

resources

 ““Nuggets” of information.Nuggets” of information.

 For example, a publication is a resource that can be For example, a publication is a resource that can be

described by RDF described by RDF

• Author, publication date, URL are all metadata property Author, publication date, URL are all metadata property values.

values.

• But publications have references that are just other But publications have references that are just other publications

publications

• DC’s “hasReference” can be used to point from one publication DC’s “hasReference” can be used to point from one publication to another.

to another.

 Publication also have authors Publication also have authors

• An author is more than a nameAn author is more than a name

• Also an RDF resource with collections of propertiesAlso an RDF resource with collections of properties

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Graph Model Depicting vCard and

DC Linking

http://.../CMCS/Entry/1

dc:title

H20

http://.../People/DrY

dc:creator

vcard:N

[email protected]

vcard:EMAIL

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What Else Does RDF Do?



Collections: typically used as the object of an RDF

statement

• Bag: unordered collection of resources or literals.Bag: unordered collection of resources or literals.

• Sequence: ordered collection or resources or literals.Sequence: ordered collection or resources or literals. • Alternative: collection of resources or literals, from Alternative: collection of resources or literals, from

which only one value may be chosen which only one value may be chosen



And that’s about it. RDF does not define

properties, it just tells you where to put them.

• Definitions are done by specific groups for specific fields Definitions are done by specific groups for specific fields (Dublin Core Metadata Initiative, for example).

(Dublin Core Metadata Initiative, for example).

• RDF Schema provides the rules for defining specific RDF Schema provides the rules for defining specific resources classes and properties.

resources classes and properties.



But the graph model has opened some doors

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RDF Schema



RDF Schema is a rules system for building RDF

languages.

• RDF and RDFS are defined in terms of RDFSRDF and RDFS are defined in terms of RDFS • DAML+OIL and OWL are defined by RDFS.DAML+OIL and OWL are defined by RDFS.



Take our Dublin Core RDF encoding as an

example:

• Can we formalize this process, defining a consistent set Can we formalize this process, defining a consistent set of rules?

of rules?

 Previous example was valid RDF but how do I formalize the Previous example was valid RDF but how do I formalize the

process of writing sentences about creators of entries?

• Can we place restrictions and use inheritance to define Can we place restrictions and use inheritance to define resources?

resources?

 What really is the value of “creator”? Can I derive it from What really is the value of “creator”? Can I derive it from

another class, like “person”?

• Can we provide restrictions and rules for properties?Can we provide restrictions and rules for properties?  How can I express the fact that “title” should only appear How can I express the fact that “title” should only appear

once?

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Some RDFS Classes (Subjects and Values)

RDFS: Resource

The RDFS root element. All The RDFS root element. All other tags derive from

other tags derive from Resource

Resource

RDFS: Class

The Class class. Literals and The Class class. Literals and Datatypes are example Datatypes are example classes. Classes consist of classes. Classes consist of entities that share entities that share properties. properties.

RDFS: Literal

The class for holding Strings The class for holding Strings and integers. Literals are and integers. Literals are dead ends in RDF graphs. dead ends in RDF graphs.

RDFS: Datatype

A type of data, a member of A type of data, a member of the Literal class.

the Literal class.

RDFS: XMLLiteral

A datatype for holding XML A datatype for holding XML data.

data.

RDFS:Property

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Some RDFS Properties

subClassOf

Indicates the subject is a Indicates the subject is a subclass of the object in a subclass of the object in a statement.

statement.

subPropertyOf

The subject is a subProperty The subject is a subProperty of the property

of the property

(masquerading as an (masquerading as an object).

object).

Domain

Restricts a property to only Restricts a property to only apply to certain classes of apply to certain classes of subjects

subjects

Range

Restricts the values of a Restricts the values of a property to be members of property to be members of an indicated class or one of an indicated class or one of its subclasses.

its subclasses.

type

Denotes an instance of a Denotes an instance of a particular class. Actually particular class. Actually from RDF, not RDFS.

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Sample RDFS: Defining <Property>

 This is the definition of <property>, taken from the RDF This is the definition of <property>, taken from the RDF

schema. schema.

 The “about” attribute labels names this nugget.The “about” attribute labels names this nugget.  <property> has several properties<property> has several properties

• <label>,<comment> are self explanatory.<label>,<comment> are self explanatory.

• <subClassOf> means <property> is a subclass of <resource><subClassOf> means <property> is a subclass of <resource>

• <isDefinedBy> points to the human-readable documentation.<isDefinedBy> points to the human-readable documentation.

<rdfs:Class rdf:ID=“Property">

<rdfs:isDefinedBy rdf:resource="http://.../some/uri"/>

<rdfs:label>Property</rdfs:label>

<rdfs:comment>The class of RDF

properties.</rdfs:comment>

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Property Relationships and Simple

Reasoning



subClassOf:

• Carole is a member of the class <Professor>

Carole is a member of the class <Professor>

• <Professor> is a subclass of

<Professor> is a subclass of

<UniversityEmployee>

• So Carole works for a university.

So Carole works for a university.



subPropertityOf:

• Marlon hasSibling Susan

_{Marlon hasSibling Susan}

• hasSibling is a subclass of hasRelative

hasSibling is a subclass of hasRelative

• So Marlon and Susan are related.

_{So Marlon and Susan are related.}



Domain and Range:

• hasSibling applies to animal subjects and

hasSibling applies to animal subjects and

animal objects, so Marlon is a member of the

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Web Ontology Language

(OWL)

Eeyore: W-O-L. That spells owl.

Owl: Bless my soul! So it does!

(Many Slides Courtesy of Sean

Bechhofer)

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What’s an Ontology?



English definitions tend to be vague to

non-specialists

• “

“

A formal, explicit specification of a shared

conceptionalization”



Clearer definition: an ontology is a

taxonomy combined with inference rules

• T. Berners-Lee, J. Hendler, O. Lassila

T. Berners-Lee, J. Hendler, O. Lassila



But really, if you sit down to describe a

subject in terms of its classes and their

relationships, you are creating an

Ontology.

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RDFS Limitations



RDFS

too weak

to describe resources in

sufficient detail

• No No localised range and domainlocalised range and domain constraints constraints

 Can’t say that the range of hasChild is person when applied Can’t say that the range of hasChild is person when applied

to persons and elephant when applied to elephants

• No No existence/cardinalityexistence/cardinality constraints constraints

 Can’t say that all Can’t say that all instancesinstances of person have a mother that is of person have a mother that is

also a person, or that persons have exactly 2 parents

• No No transitive, inverse transitive, inverse oror symmetrical symmetrical properties properties

 Can’t say that isPartOf is a transitive property, that hasPart Can’t say that isPartOf is a transitive property, that hasPart

is the inverse of isPartOf or that touches is symmetrical



Difficult to provide

reasoning support

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OWL Semantic Layering

Full

DL

Lite

 Three language “layers”:Three language “layers”:

• OWL OWL LiteLite

 A subset of OWL useful for expressing A subset of OWL useful for expressing

classifications and simple relationships

• OWL OWL DL DL (Description Logic)(Description Logic)

 Contains all OWL constructions but with limitations Contains all OWL constructions but with limitations

that guarantee computational completeness and

decidability.

• OWL OWL FullFull

 All OWL constructs with no restrictions but no All OWL constructs with no restrictions but no

guaranteed processibility.

guaranteed processibility.  Syntactic LayeringSyntactic Layering

 Semantic LayeringSemantic Layering

• Layers should agree on semantics.Layers should agree on semantics.

• All legal Lite ontologies are legal DL ontologies.All legal Lite ontologies are legal DL ontologies.

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OWL Lite Synopsis



Built on RDFS, with usual RDFS classes

(see previous table in these slides).

• Includes a special class, <

Includes a special class, <

Thing

>, that is the

superclass of all OWL classes.

• Built in class <

Built in class <

Nothing

> that is the most

specific class (has no instances or subclasses).

• Built-in class <

Built-in class <

Individual

> for instances of

classes.

 In OWL, properties may apply to either individuals or In OWL, properties may apply to either individuals or

to all members of a class. to all members of a class.

 So <worksForIU> applies to Marlon but not Dave.So <worksForIU> applies to Marlon but not Dave. 

Expresses concepts such as equivalent

classes, synonymous properties.



Allows you to assert that properties can be

inverse, transitive, and symmetric.

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Some OWL DL and OWL Full

Extensions



Class Axioms:

• oneOf: a class can be defined by its

oneOf: a class can be defined by its

members (ex: daysOfWeek defined by

members)



An Enumeration class

• disjointWith

disjointWith



More Boolean Relationships:

• unionOf, complementOf, intersectionOf

unionOf, complementOf, intersectionOf



Unrestricted cardinality

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Differences Between DL and Full

 Both DL and Full use the same OWL vocabularyBoth DL and Full use the same OWL vocabulary

• See previous slide.See previous slide.

 Difference #1: DL classes and properties cannot also be Difference #1: DL classes and properties cannot also be

individuals (instances), and vice versa. individuals (instances), and vice versa.

• That is, there is a strict separation between That is, there is a strict separation between type type and and

subClassOf. subClassOf.

• So if you use <Merlot> as <rdf:type> of <Wine>, you can’t So if you use <Merlot> as <rdf:type> of <Wine>, you can’t subclass <Merlot> to add additional properties in OWL DL.

subclass <Merlot> to add additional properties in OWL DL.

• ““subClass versus instance” decisions should be made based on subClass versus instance” decisions should be made based on the intended use of the ontology.

the intended use of the ontology.

 Don’t make Merlot an instance if you are developing an ontology to Don’t make Merlot an instance if you are developing an ontology to

describe your wine collection, which consists of many bottles of

Merlot (instances), and you want to use OWL DL

 Difference #2: All DL properties are required to be eitherDifference #2: All DL properties are required to be either

• owl:ObjectProperty:owl:ObjectProperty: used to connect instances of two used to connect instances of two classes.

classes.

• owl:DataTypePropertyowl:DataTypeProperty: used to connect class instances with : used to connect class instances with XML schema types and RDF literal strings.

XML schema types and RDF literal strings.

• (OWL Full allows us to tag DataTypeProperties as (OWL Full allows us to tag DataTypeProperties as

owl:InverseFunctionalProperty,

owl:InverseFunctionalProperty, so we can create a string so we can create a string literal instance that uniquely identifies a class instance.

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An OWL Example

An Earth Systems Grid

example

(Courtesy of Line Pouchard)

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An Example Ontology: Climate

Data



The example shows how to construct a really

simple ontology and instance.



We don’t use it to encode all data but rather to

encode metadata about data files.

• Where is the data file (URI) that has the temperature Where is the data file (URI) that has the temperature associated with this dataset?

associated with this dataset?



Two classes:

• datasetdataset • ParameterParameter



One property:

• hasParameterhasParameter



Several parameters: cloud_medium,

bounds_latitude, temperature



Line Pouchard (ORNL) created this for ESG using

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Let’s Begin



Front matters: OWL ontologies begin with the

<Ontology> header.

• A useful place to put metadata about the document.A useful place to put metadata about the document. • Line uses the Dublin Core to establish authorship.Line uses the Dublin Core to establish authorship.



Next, define two classes: dataset and parameter.

• Class definitions are almost trivial.Class definitions are almost trivial.

• We really state what something is by its properties.We really state what something is by its properties.  Deep philosophical arguments here, I’m sure.Deep philosophical arguments here, I’m sure.



Most of the work will go into defining the

property, hasParameter.

• Begins on bottom of next slideBegins on bottom of next slide

• But the full extent of the definition requires a separate But the full extent of the definition requires a separate slide.

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Class Definitions

Ontology header

With Dublin Core

Parameters.

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Defining hasParameter



hasParameter domain: it applies to the dataset

class.



hasParameter range: it applies to a list of 3 OWL

Things

• Cloud_medium, bounds_latitude, and temperature.Cloud_medium, bounds_latitude, and temperature. • This is done using the awkward RDF list structure. This is done using the awkward RDF list structure.

 ““Give me the first of the rest recursively until I get to nil”Give me the first of the rest recursively until I get to nil”



These three OWL Things are then defined.

• They are each of type “parameter” They are each of type “parameter”

 That is, members of the parameter class.That is, members of the parameter class.

• Each may also be further defined by additional Each may also be further defined by additional properties and classes.

properties and classes.

 Temperature has units, for example, bounds_latitude needs Temperature has units, for example, bounds_latitude needs

starting and stopping values in decimal degrees,etc.

• Or it may be out of scope. I may just need to know that Or it may be out of scope. I may just need to know that the bounds_latitude for particular dataset is located in the bounds_latitude for particular dataset is located in

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Parameter:

Cloud_medium

Parameter:

temperature

Parameter:

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Finally, Apply It to Something



What is the file PCM.B06.10.dataset1?

• It’s a member of the dataset class, which we

have defined.



What properties does it have?

• bounds_latitude and cloud_medium, as all

such members do.



Where can I get the bounds_latitude for

this data set?

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OWL Enriched RDF

Metadata about

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Is It Lite, DL, or Full?



Our ontology example is (at least)

DL because we include the oneOf

property.

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OWL Equivalence and Inheritance

<owl:Class rdf:ID=”user”> <owl:Class rdf:ID=”user”> <owl:equivalentClass <owl:equivalentClass rdf:resource=”person”> rdf:resource=”person”> <owl:Class> <owl:Class> <owl:Class <owl:Class rdf:about=”#magneticSpe rdf:about=”#magneticSpe ctrometer”> ctrometer”> <rdfs:subClassOf> <rdfs:subClassOf> <owl:Restriction> <owl:Restriction> <owl:onProperty <owl:onProperty rdf:resource=”#hasMagnet rdf:resource=”#hasMagnet s”> s”> <owl:allValuesFrom <owl:allValuesFrom rdf:resource=”#Spectrome rdf:resource=”#Spectrome ter”> ter”> </owl:Restriction></owl:Restriction> </rdfs: subClassOf> </rdfs: subClassOf> </owl:Class> </owl:Class>

Other logical relationships

that can be asserted:

•inverseOf,

•TransitveProperty,

•SymmetricProperty,

•FunctionalProperty,

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Querying Semantic Data

The Data Access Working

Group (DAWG)

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What Is Semantic Querying?



Don’t confuse

querying with

inference.



Querying just means

retrieving data from

Semantic data

models.

• Post a query to the Post a query to the

world of distributed RDF world of distributed RDF

data nuggets. data nuggets.



For RDF-like

structures, this

amounts to querying

triples



Examples

• Finding an Email Finding an Email

address from a person’s address from a person’s

vCard. vCard.

• Searching across Searching across

subgraphs: get me the subgraphs: get me the

email of the author of email of the author of this document (Dublin this document (Dublin

Core + vCard). Core + vCard).

• Persistent/scheduled Persistent/scheduled queries on updates to queries on updates to

several multimedia several multimedia

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The DAWG Working Group



Unfortunately, there are no standards for

querying RDF, etc.

• There are solutions, like RDQL/SquishQL

There are solutions, like RDQL/SquishQL

• These are just not “official”

_{These are just not “official”}



The W3C Data Access Working Group

DAWG is filling the query gap.

• Formed Feb 2004.

Formed Feb 2004.



This is a work in progress:

• Use Cases and Requirements:

Use Cases and Requirements:

http://www.w3.org/TR/rdf-dawg-uc/

• BRQL Query Language:

_{BRQL Query Language:}

http://www.w3.org/2001/sw/DataAccess/rq23/

(48)

A Simple Query



Consider the following RDF triple

• <http://example.org/book/book1>

<http://example.org/book/book1>

<http://purl.org/dc/elements/1.1/title> "BRQL

Tutorial“

• Recall this is equivalent to the sentence “book1

Recall this is equivalent to the sentence “book1

[has] title ‘BRQL Tutorial’”

• We may have a large set of such triples in our

We may have a large set of such triples in our

data store.



We want to make a query on this data like

this: “What is the title of book1?”

(49)

The Query and the Results



We can construct queries on any of the

parts of the triple, such as

SELECT ?title

WHERE { <http://example.org/book/book1>

<http://purl.org/dc/elements/1.1/title> ?title .

}



Thus just means “what is the title of

book1?”

?title = "BRQL Tutorial“

(50)

So What?



This was a trivial example in which we

posed a query on the triple’s object, which

was a string.



But the object of the triple may be a URI

(an RDF resource), not just a literal.

• Or we may construct queries against subjects

Or we may construct queries against subjects

or verbs of triples.



For complicated graphs, this means that

the query returns a “pointer” to another

section of the graph.



This means that we can make linked

queries that allow us to navigate graphs.

(51)

Linked Queries Across Graph

Sections

http://.../CMCS/Entry/1

dc:title

H20

http://.../People/DrY dc:creator

vcard:N

[email protected]

vcard:EMAIL

vcard:Given vcard:Family

(52)

What If You Can’t Wait?



BRQL is still a work in progress.



If you need something now, there is

Jena’s RDQL.



RDQL allows you to pose triplet

queries similar BRQL

• Jena has a programming interface that

Jena has a programming interface that

allows you to construct and execute

these queries against RDF.

(53)

Tools for Playing with Things



Jena Toolkit: Java packages from HPLabs

for building Semantic Web applications.

• http://www.hpl.hp.com/semweb/

http://www.hpl.hp.com/semweb/

• Both IsaViz and Protégé use this.

Both IsaViz and Protégé use this.



IsaViz: A nice authoring/graphing tool

• http://www.w3.org/2001/11/IsaViz/

http://www.w3.org/2001/11/IsaViz/



Protégé: Another ontology authoring tool

• http://protege.stanford.edu/

http://protege.stanford.edu/



SiRPAC

• Allows you to parse RDF, convert RDF/XML into

Allows you to parse RDF, convert RDF/XML into

graphs and triplets.

(54)

Original Semantic Grid GGF tutorial

material is here:

• http://www.semanticgrid.org/presentations/

http://www.semanticgrid.org/presentations/

ontologies-tutorial/



Beginner and Advanced OWL tutorials are

here:

• http://www.co-ode.org/resources/

http://www.co-ode.org/resources/

• Lectures cover working examples (pizza

Lectures cover working examples (pizza

ontology) built with Protégé.

• http://www.semanticgrid.org/presentations/

http://www.semanticgrid.org/presentations/

ontologies-tutorial/

(55)

Advanced OWL Tutorial

Courtesy of Sean Bechhofer

(56)

OWL Syntaxes



Abstract Syntax

• Used in the definition of the language and the

Used in the definition of the language and the

DL/Lite semantics



OWL as

RDF triples

(and thus as, e.g.

RDF/XML or N3)

• the “official” concrete syntax

the “official” concrete syntax

• mapping rules describe how to translate from

mapping rules describe how to translate from

abstract syntax to triples.



XML Presentation

Syntax

(57)

OWL Ontologies



An OWL ontology consists of a number of Classes,

Properties and Individuals

• All identified via All identified via URIURIs.s.



Classes

• Have “definitions” providing their characteristicsHave “definitions” providing their characteristics



Properties

• Characteristics such as transitivity or functionalityCharacteristics such as transitivity or functionality • Domains and RangesDomains and Ranges



Individuals

• Class membershipClass membership

(58)

XML Datatypes in OWL



OWL supports

XML Schema

primitive datatypes



Clean

separation

between ”object” classes and

datatypes



Philosophical reasons:

• Datatypes structured by Datatypes structured by built-in predicatesbuilt-in predicates

• Not appropriate to form new datatypes using ontology Not appropriate to form new datatypes using ontology language

language



Practical reasons:

• Ontology language remains Ontology language remains simple and compactsimple and compact

• ImplementabilityImplementability not compromised – can use hybrid not compromised – can use hybrid reasoner

(59)

OWL Class constructors



OWL has a number of

operators

for

constructing class expressions.



Boolean

operators

• and, or, not

and, or, not



Restrictions

• slot fillers with explicit quantification

slot fillers with explicit quantification



Enumerated

Classes

.

• explicit enumerations of the class

explicit enumerations of the class

members

(60)

OWL Class Constructors

Constructor

Constructor ExampleExample

Classes

Classes HumanHuman intersectionOf

intersectionOf (and)

(and) intersectionOf(Human Male)intersectionOf(Human Male) unionOf (or)

unionOf (or) unionOf(Doctor Lawyer)unionOf(Doctor Lawyer) complementOf

complementOf (not)

(not) complementOf(Male)complementOf(Male) oneOf

oneOf oneOf(john mary)oneOf(john mary) someValuesFrom

someValuesFrom restriction(hasChild someValuesFrom restriction(hasChild someValuesFrom Lawyer)

Lawyer) allValuesFrom

allValuesFrom restriction(hasChild allValuesFrom Doctor)restriction(hasChild allValuesFrom Doctor) minCardinality

minCardinality restriction(hasChild minCardinality (2))restriction(hasChild minCardinality (2)) maxCardinality

(61)

OWL Class constructors



The operators have an

associated

semantics

• Given in terms of a domain:

Given in terms of a domain:





• and an

and an

interpretation

function

I



I

:

concepts

_!



(



)



I

:

properties

_!



(



_£



)



I

:

individuals

_!



(62)

OWL Constructor Semantics

Construc

tor

Example

Semantics

Classes

Human

I(Human)

intersectio

nOf

intersectionOf(Huma

n Male)

intersectionOf(Huma

n Male)

I(Human)

I(Male)

I(Human)

I(Male)

Å

unionOf

unionOf(Doctor

Lawyer)

I(Doctor)

_[

I(Doctor)

_[

I(Lawyer)

compleme

ntOf

complementOf(Male)



n

I(Male)

oneOf

oneOf(john mary)

{

I(john)

,

I(mary)

(63)

OWL Constructor Semantics

Constructor

Constructor ExampleExample SemanticsSemantics

someValuesFr someValuesFr om

om restriction(hasChildrestriction(hasChild someValuesFrom someValuesFrom Lawyer)

Lawyer)

{x

{x_j9_j9y.y._h_hx,yx,y_i2_i2I(hasChild)I(hasChild)

Æ

y

y₂₂I(Lawyer)I(Lawyer)}}

allValuesFrom

allValuesFrom restriction(hasChilrestriction(hasChil d d allValuesFrom allValuesFrom Doctor) Doctor) {x

{x_j8_j8y.y._h_hx,yx,y_i2_i2I(hasChild)I(hasChild)

)

) y

y₂₂I(Doctor)I(Doctor)}}

minCardinalit minCardinalit y

y restriction(hasChildrestriction(hasChild minCardinality minCardinality (2))

(2))

{x

{x|# |# _h_hx,yx,y_i2_i2I(hasChild)I(hasChild)

¸

¸ 2}2}

maxCardinalit maxCardinalit y

y restriction(hasChildrestriction(hasChild maxCardinality maxCardinality (2))

(2))

{x

{x|# |# _h_hx,yx,y_i2_i2I(hasChild)I(hasChild)

·

(64)

OWL Axioms



Axioms

allow us to add further statements about

arbitrary concept expressions and properties

• Disjointness, equivalence, transitivity of properties etc.Disjointness, equivalence, transitivity of properties etc.



An interpretation is then a model of the axioms iff

it satisfies

every

axiom in the ontology.

Axiom

Axiom ExampleExample SemanticsSemantics

EquivalentClass

es

es EquivalentClass(Man_{intersectionOf(Human}EquivalentClass(Man_{intersectionOf(Human}

Male))

I(Man)

I(Man) = = I(Human)I(Human) ÅÅ

I(Male) I(Male)

DisjointClasses

DisjointClasses DisjointClasses(Animal DisjointClasses(Animal Plant)

Plant) I(Animal)I(Animal) ÅÅ I(Plant)I(Plant) = = ;;

SameIndividual

As

As SameIndividualAs(GeorgeWBush SameIndividualAs(GeorgeWBush PresidentBush)

PresidentBush)

I(GeorgeWBush) I(GeorgeWBush) = =

(65)

Basic Inference Tasks



Inference can now be defined w.r.t.

interpretations/models.

• C C subsumessubsumes D w.r.t. K iff for D w.r.t. K iff for everyevery model model I of I of _K_K, , I(D)

I(D) _µ_µ I(C) I(C)

• C is C is equivalentequivalent to D w.r.t. K iff for to D w.r.t. K iff for everyevery model model I of I of K, I (

K, I (C)C) = I (D) = I (D)

• C is C is satisfiablesatisfiable w.r.t. K iff there exists w.r.t. K iff there exists somesome model model I I of K s.t.

of K s.t. I (C) I (C)  _;_;



Querying

knowledge

• x is an x is an instanceinstance of C w.r.t. K iff for of C w.r.t. K iff for everyevery model model I of I of K, I(x)

K, I(x) ₂₂ I(C) I(C)

•

h

hx,yx,yii is an is an instanceinstance of R w.r.t. K iff for, of R w.r.t. K iff for, everyevery model model I I

of of _K_K, ,

(I(x),I(y))

(66)

Why Reasoning?

 Why do we want it?Why do we want it?

• Semantic Web aims at “machine understanding”Semantic Web aims at “machine understanding”

• UnderstandingUnderstanding closely related to closely related to reasoningreasoning

 Given key role of ontologies in the Semantic Web, it will be Given key role of ontologies in the Semantic Web, it will be

essential to provide

essential to provide toolstools and and servicesservices to help users: to help users:

• Design and maintain high quality ontologies, e.g.:Design and maintain high quality ontologies, e.g.:

 MeaningfulMeaningful —— all named classes can have instances all named classes can have instances  CorrectCorrect —— captured intuitions of domain experts captured intuitions of domain experts  Minimally redundantMinimally redundant —— no unintended synonyms no unintended synonyms

 Richly axiomatisedRichly axiomatised —— (sufficiently) detailed descriptions (sufficiently) detailed descriptions

• Answer Answer queriesqueries over ontology classes and instances, e.g.: over ontology classes and instances, e.g.:

 Find more general/specific classesFind more general/specific classes

(67)

Why

Decidable

_Decidable

Reasoning?

_Reasoning?

 OWL DL constructors/axioms restricted so reasoning is OWL DL constructors/axioms restricted so reasoning is

decidable

 Consistent with Semantic Web's Consistent with Semantic Web's layered architecturelayered architecture

• XML provides syntax XML provides syntax transport layertransport layer

• RDF(S) provides basic RDF(S) provides basic relational languagerelational language and simple and simple ontological primitives

ontological primitives

• OWL DL provides powerful but still decidable OWL DL provides powerful but still decidable ontology ontology language

language

• Further layers may (will) extend OWLFurther layers may (will) extend OWL

 Will almost certainly be undecidableWill almost certainly be undecidable

 Facilitates provision of Facilitates provision of reasoning servicesreasoning services

• Known “practical” Known “practical” algorithmsalgorithms • Several implemented Several implemented systemssystems

• Evidence of Evidence of empirical tractabilityempirical tractability

 Understanding dependent on Understanding dependent on reliable & consistentreliable & consistent

(68)

(69)

XML Primer

General characteristics of XML

(70)

Basic XML

 XML consists of human XML consists of human

readable tags readable tags

 Schemas define rules for a Schemas define rules for a

particular dialect. particular dialect.

 XML Schema is the root, XML Schema is the root,

defines the rules for defines the rules for

making other XML making other XML

schemas. schemas.

 Tree structure: tags must Tree structure: tags must

be closed in reverse order be closed in reverse order

that they are opened. that they are opened.

 Tags can be modified by Tags can be modified by

attributes attributes

• name, minOccursname, minOccurs

 Tags enclose either strings Tags enclose either strings

or structured XML or structured XML

<element name="FaultName" <element name="FaultName"

type="xsd:string" /> type="xsd:string" />

minOccurs="0" />

</choice></choice>

</sequence></sequence>

(71)

Namespaces and URIs

 XML documents can be XML documents can be composed of several

composed of several

different schemas.

 Namespaces are used to Namespaces are used to identify the source schema

identify the source schema

for a particular tag.

• Resolves name conflictsResolves name conflicts —”full path”

—”full path”

 Values of namespaces are Values of namespaces are URIs.

URIs.

• URI are just structured URI are just structured names.

names.

 May point to May point to

something not something not electronically electronically retrievable retrievable

• URLs are special cases.URLs are special cases.

<

xsd:schema xsd:schema

xmlns:xsd="http://www.w xmlns:xsd="http://www.w 3.org/2001/XMLSchema" 3.org/2001/XMLSchema" xmlns:gem="http://comm xmlns:gem="http://comm grids.indiana.edu/GCWS/S grids.indiana.edu/GCWS/S chema/GEMCodes/Faults”