This document discusses RDFS (Resource Description Framework Schema), which is a standard ontology language for the Semantic Web. RDFS introduces predefined meanings for resources through axioms and allows for basic inferences over RDF data through mechanisms like type propagation between classes and properties. The document provides examples of how RDFS can be used to classify resources in an RDF graph and automatically infer additional types for resources based on their properties and class memberships.

1. +
RDFS
A little semantics goes a
long way
Mariano Rodriguez-Muro,
Free University of Bozen-Bolzano

2. +
Disclaimer

License


A few examples from these slides has been taken from


This work is licensed under a
Creative Commons Attribution-Share Alike 3.0 License
(http://creativecommons.org/licenses/by-sa/3.0/)
Semantic Web for the working Ontologist. Chapter 6.
Some of the slides on the use of taxonomies are based on:

http://info.earley.com/webinar-replay-business-value-taxonomy-aug2012

3. +
Reading material

Semantic Web for the working Ontologist. Chapter 6
http://proquest.safaribooksonline.com/book/-/9780123859655

4. +
Motivation

Ontologies

RDFS ontologies

Overview

Annotations

5. +
Motivation

6. +
Motivation

Motivations for semantic
technology

Making the web machine
understandable

Expressing knowledge


However, points 2 and 3 are not
possible with the technologies
seen so far

RDF doesn’t define
vocabularies, and

Different datasets may use
different URI’s to represent the
same kind of data
Reasoning with knowledge

7. +
Motivation

Agreement in RDF graphs concerns only the data model and the use
of URI as identifiers

No semantics!

8. +
Ontologies and Ontology
Languages

9. +
What is an ontology language?

Specification of valid “axioms”

Specifications of vocabularies with “predefined” meaning in axioms

Informal: Topic Maps, UML diagrams

Formal examples: Predicate Logic, First Order Logic

Semantic Web examples:



RDFS
SWRL,
OWL

Different languages have different expressive power

Axioms allow to produce “inferences”

The more expressive power, more complex and costly the inferences

10. +
What is an ontology?

Collections of “axioms”

Describe the meaning of the vocabulary of a domain (e.g., an
area of expertise)

Expressed in an Ontology Language

Valuable on their own as knowledge repositories

In combination with data valuable to implement complex
behavior with little or no coding

11. +
Example: Schema.org

Schema.org IS a simple ontology

Organizes terms in hierarchies with
predefined meaning

The language is a variation of RDFS

12. +
RDFS
Introduction by example

13. +
RDFS

W3C standard for an ontology language

RDFS introduces resources (URIs) with a predefined meaning

Inference engines that support RDFS allow to take that
meaning into account

RDFS inferences extend the RDF graph by means of inference
and hence, affect query answering

RDFS is very simple compared to SWRL or OWL, however, it
is very useful in many context, allowing for increased
productivity, easy data integration and interesting AI
applications

14. +
Building blocks

New namespace rdfs:
<http://www.w3.org/2000/01/rdf-schema#>

New categories:
Commonly,
Class names
are nouns

Classes, resources that share something in common, allow us to
group things together. For example, Employee, Company.
Resources that identify classes have rdf:type rdfs:Class

Instances, resources that are “members” of a class

15. +
Building blocks
Resources can belong to multiple classes

16. +
Building blocks (cont.)

Properties: Resources used as a predicate in statements
Commonly, Property names are
multiple words, expressing direction
and in camel-casing

17. +
RDFS Ontologies

RDFS Axioms

Are RDF triples!

RDFS ontology is an RDF graph!

An RDF graph may have a subgraph expressed in RDFS

We call the RDFS axioms/triples the Tbox of the ontology
(terminological information, predefined meaning)

The rest is the Abox of the ontology (plain data, no predefined
meaning)

18. +
Type propagation

RDFS vocabulary:
rdfs:subClassOf

Key notions

sub class (on the left)

super class (on the right)

Intuitive meaning, if :mariano is
an instance of subclass it is
also an instance of superclass

Formal meaning: subsets

Inference: type propagation
Similar to inheritance
in Object Oriented
formalisms

19. +
Type propagation

RDFS vocabulary:
rdfs:subClassOf

Key notions

sub class (on the left)

super class (on the right)

Intuitive meaning, if :mariano is
an instance of subclass it is
also an instance of superclass

Formal meaning: subsets

Inference: type propagation
Similar to inheritance
in Object Oriented
formalisms

20. +
Relation propagation

RDFS vocabulary:
rdfs:subPropertyOf

Key notions
 sub property(on the left)
 super property(on the right)

Intuitive meaning, if (x,y) are connected with subproperty
they are also connected with superproperty

Formal meaning: subsets (of binary tuples)

Inference: relationship propagation

21. +
Relation propagation

RDFS vocabulary:
rdfs:subPropertyOf

Key notions
 sub property(on the left)
 super property(on the right)

Intuitive meaning, if (x,y) are connected with subproperty
they are also connected with superproperty

Formal meaning: subsets (of binary tuples)

Inference: relationship propagation

22. +
Types by usage

RDFS vocabulary:
rdfs:domain, rdfs:range

Key notions
 domain of a triple:
the subject
 range of a triple:
the object

:p rdfs:domain :C > the domain of any
triple where :p is the predicate is an
instance of :C
(similar for rdfs:range)

Formal meaning:
if (x,y) in P, then x in :C

Inference: type assignment by property
usage

23. +
Types by usage

RDFS vocabulary:
rdfs:domain, rdfs:range

Key notions
 domain of a triple:
the subject
 range of a triple:
the object

:p rdfs:domain :C > the domain of any
triple where :p is the predicate is an
instance of :C
(similar for rdfs:range)

Formal meaning:
if (x,y) in P, then x in :C

Inference: type assignment by property
usage

24. +
Interactions

All inferences interact to allow
complex behavior

25. +
Interactions

All inferences interact to allow
complex behavior

26. +
Set intersection

Proper set intersection is not
possible in RDFS

However, expressing necessary
membership to multiple classes
is possible, i.e., A subset B AND
C
A rdfs:subClassOf B
A rdfs:subClassOf C
consider
x rdf:type A

27. +
Set intersection

Proper set intersection is not
possible in RDFS

However, expressing necessary
membership to multiple classes
is possible, i.e., A subset B AND
C
A rdfs:subClassOf B
A rdfs:subClassOf C
consider
x rdf:type A

28. +
Set intersection

Proper set intersection is not
possible in RDFS

However, expressing necessary
membership to multiple classes
is possible, i.e., A subset B AND
C
A rdfs:subClassOf B
A rdfs:subClassOf C
consider
x rdf:type A
One direction
only!

29. +
Set intersection

Similar for roles

30. +
Set intersection

Similar for roles

31. +
Set union

Proper set union is not possible
in RDFS

However, A OR B subsetOf C
B rdfs:subClassOf A
C rdfs:subClassOf A
consider
x rdf:type B
or
x rdf:type C

32. +
Set union

Proper set union is not possible
in RDFS

However, A OR B subsetOf C
B rdfs:subClassOf A
C rdfs:subClassOf A
consider
x rdf:type B
or
x rdf:type C

33. +
Set union

For roles. Aligning to a global
vocabulary

34. +
Set union

For roles. Aligning to a global
vocabulary

35. +
Equivalence

Merging vocabularies

To account for same use of
different terms (classes or
properties)

For classes or proeperties

36. +
Equivalence

Merging vocabularies

To account for same use of
different terms (classes or
properties)

For classes or proeperties

37. +
Last notes on RDFS axioms

Main new vocabulary:

rdfs:subClassOf

rdfs:subPropertyOf

rdfs:domain

rdfs:range

Different from CONSTRAINTS, missing triples are NOT a
violation

Allow to infer new information

Allows to implement system behavior!

38. +
Open lists revisited

RDFS also facilitates access to Lists

Elements of lists are a possibly
infinite set of elements of the form
rdf:_1, rdf:_2, etc
RDFS facilitates this by enforcing that:
if x rdfs:_1 y
then x rdfs:member b

Access difficult in practice

39. +
Open lists revisited

RDFS also facilitates access to Lists

Elements of lists are a possibly
infinite set of elements of the form
rdf:_1, rdf:_2, etc

Access difficult in practice
RDFS facilitates this by enforcing that:
if x rdfs:_1 y
then x rdfs:member b
More detail on this on the lecture about
RDFS semantics

40. +
Axiomatic triples

RDFS enforces certain facts to be always true

These facts are statements (triples)

Referred as Axiomatic triples

Listed in http://www.w3.org/TR/rdf-mt/
More detail on this on the lecture about
RDFS semantics

41. +
RDFS Semantic Conditions

Every resource x
x rdf:type rdfs:Resource

Every literal x
x rdf:type rdfs:Literal

… etc
More detail on this on the lecture about
RDFS semantics

42. +
Last notes on RDFS axioms

Main new vocabulary (not the only one):

rdfs:subClassOf

rdfs:subPropertyOf

rdfs:domain

rdfs:range

Different from CONSTRAINTS, missing triples are NOT a
violation

Allow to infer new information

Allows to implement system behavior!

43. +
Hands on examples
From Semantic Web for the Working Ontologist

44. +
Automatic classification of
employees (part 1)

Transform into an RDF representation

Automatically catalog objects as Employees, and as Active
employees, Suspended employees and Ex-employees
using a minimal set of “axioms”
<ID>
Project
Assignment
Absent
Until
Termination Date
22
24
-
-
34
24
Dec 23, 2012
-
73
-
-
Jun 4, 2010
Employee table. Primary key: 10
Active employees are assigned to projects

45. +
Automatic classification of
employees (part 2)

Transform into an RDF representation

Automatically catalog objects as Employees as managers
<ID>
Project Name
<Manager>
24
Project-x
34
25
Project Mayhem
22
Project table. Primary key: ID
Foreign key <Manager> to Employee table

46. + Align vocabularies
• Align corresponding properties
using RDFS
• Align with FOAF vocabulary
(when possible) using RDFS (use
foaf:name, foaf:homepage)

47. +
Annotations

48. +
Annotations

URI’s are not readable

Readable information (comments, names, etc.) can be stored
using properties, but

Property names are not standard, however, we could like some
standard names for “human oriented information”

RDFS defines:

rdfs:label
A readable name for a resource

rdfs:comment
Human focused comments
These are properties
So, subPropertyOf can be used
with them

49. +
Redirection

Redirecting to location of documents (RDF) with additional
information about a subject

No formal semantics

RDFS provides:

rdfs:seeAlso. Additional information

rdfs:definedBy. Authority information, primary source.
Recall the semantic web
idea, linked databases
These are properties
So, subPropertyOf can be used
with them