SWT Lecture Session 5 - RDFS
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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 relationships. The document provides examples of how RDFS can be used to classify resources in an RDF graph and automatically infer additional types and relationships through the use of RDFS properties like rdfs:subClassOf and rdfs:domain.
SWT Lecture Session 5 - RDFS
- 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
- 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!
- 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
- 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
Editor's Notes
- #45: Exercise 1