1 Berendt: Advanced databases, 1st semester 2012/2013, berendt/teaching/ 1 Advanced databases –...

1Berendt: Advanced databases, 1st semester 2012/2013, http://www.cs.kuleuven.be/~berendt/teaching/

1

Advanced databases –

Inference on

the Semantic Web

Bettina Berendt

Katholieke Universiteit Leuven, Department of Computer Science

http://people.cs.kuleuven.be/~bettina.berendt/teaching/

Last update: 17 October 2012


2

Agenda

Introduction / motivation; kinds of reasoning

Properties of Properties (cf. the Pizza Tutorial)

Class descriptions, cardinality, & value constraints

Does this type of knowledge exist in LOD?

Common problems in using OWL reasoning


3

Recall: Task from the previous week

Given

your knowledge of logic

and the presence of interconnected data sources such as those shown on p. 63:

What inferences would you want to draw (that go beyond data retrieval)?

Name 3 examples. Be as concrete or as abstract as you want.

(Recall: retrieval is just getting the data – a standard SELECT statement with some selections and projections would be a typical example of retrieval in the SQL world

Inference is concluding more from this – it starts with operators such as COUNT or MAX in SELECT statements and then goes as far as logic or other ways of data processing take you)


4

Motivation; deductive and inductive reasoning (ex.s)

< Example shown in Protégé >

Approach in this lecture: „Data++“ or: understanding OWL as a conceptual modelling tool à la EER or UML class diagrams plus logic

Deductive reasoning All swans are white.

Tilly is a swan.

Tilly is white.

Truth-preserving!

Inductive reasoning Tilly and Edda and Edwin and … are swans.

Tilly and Edda and Edwin and … are white.

All swans are white.

„Bringing new knowledge into the world“


5

Agenda







6

OWL Properties (Object and/or Datatype ~) can be …

Functional

Inverse functional (or: Inverse of another relation)

Transitive

Symmetric

Asymmetric

Reflexive

Irreflexive

… and this allows for inferences on individuals (see Pizza Tutorial)


7

Agenda







8

Please note

The language elements shown on the following slides are not available in all of OWL‘s versions (Lite, DL, Full) and/or are restricted in different ways in these versions. Also, OWL2 is a different matter altogether.

We concentrate on OWL DL, i.e. the version that Protégé uses.

For all OWL snippets shown on the following slides, we‘ll ask:

What does it mean? (Paraphrase in natural language)

What does it imply? (= What will a reasoner infer?)

Please note that the 2 sets of examples have a slightly different syntax, inspired by OWL XML notation or Protégé


9

Class descriptions

Classes can be described/defined as the

UnionOf

complementOf

IntersectionOf

other classes, or as the

enumeration of instances (via oneOf )


10

Cardinality constraints

0/1

≥ 0

MinCardinality

MaxCardinality


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Value constraints

allValuesFrom

someValuesFrom

hasValue


12

Examples: Class inferences (1)

Class(a:bus_driver complete intersectionOf(a:person

restriction(a:drives someValuesFrom (a:bus))))

Class(a:driver complete intersectionOf(a:person

restriction(a:drives someValuesFrom (a:vehicle))))

Class(a:bus partial a:vehicle)

Note: a is the namespace used throughout these examples


13


Class(a:cat_owner complete intersectionOf(a:person

restriction(a:has_pet someValuesFrom (a:cat))))

SubPropertyOf(a:has_pet a:likes)

Class(a:cat_liker complete intersectionOf(a:person

restriction(a:likes someValuesFrom (a:cat))))


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Class(a:driver complete intersectionOf(a:person

restriction(a:drives someValuesFrom (a:vehicle))))

Class(a:driver partial a:adult)

Class(a:grownup complete intersectionOf(a:adult a:person))


15


Class(a:sheep partial

restriction(a:eats allValuesFrom (a:grass)) a:animal)

Class(a:grass partial a:plant)

DisjointClasses(unionOf(restriction(a:part_of someValuesFrom (a:animal)) a:animal)

unionOf(a:plant restriction(a:part_of someValuesFrom (a:plant))))

Class(a:vegetarian complete intersectionOf(

restriction(a:eats allValuesFrom (complementOf(restriction(a:part_of someValuesFrom (a:animal)))))

restriction(a:eats allValuesFrom (complementOf(a:animal))) a:animal))


16


Class(a:giraffe partial a:animal

restriction(a:eats allValuesFrom (a:leaf)))

Class(a:leaf partial restriction(a:part_of someValuesFrom (a:tree)))

Class(a:tree partial a:plant)

DisjointClasses(unionOf(restriction(a:part_of someValuesFrom (a:animal)) a:animal)

unionOf(a:plant restriction(a:part_of someValuesFrom (a:plant))))





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Class(a:old_lady complete

intersectionOf(a:person a:female a:elderly))

Class(a:old_lady partial intersectionOf(

restriction(a:has_pet allValuesFrom (a:cat))

restriction(a:has_pet someValuesFrom (a:animal))))

Class(a:cat_owner complete intersectionOf(a:person

restriction(a:has_pet someValuesFrom (a:cat))))


18


Class(a:cow partial a:vegetarian)

DisjointClasses(unionOf(restriction(a:part_of someValuesFrom (a:animal)) a:animal) unionOf(a:plant restriction(a:part_of someValuesFrom (a:plant))))




Class(a:mad_cow complete intersectionOf(a:cow

restriction(a:eats someValuesFrom (intersectionOf(restriction(a:part_of someValuesFrom (a:sheep)) a:brain)))))

Class(a:sheep partial a:animal restriction(a:eats allValuesFrom (a:grass)))


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Examples: Instance inferences (1)

Individual(a:Daily_Mirror type(owl:Thing))

Individual(a:Nick type(a:male)

value(a:drives a:Q123_ABC)

value(a:reads a:Daily_Mirror))

Individual(a:Q123_ABC type(a:van) type(a:white_thing))

Class(a:white_van_man complete

intersectionOf(a:man restriction(a:drives someValuesFrom (intersectionOf(a:van a:white_thing)))))

Class(a:white_van_man partial restriction(a:reads allValuesFrom (a:tabloid)))


20


Individual(a:Spike type(owl:Thing)

value(a:is_pet_of a:Pete))

Individual(a:Pete

type(owl:Thing))

ObjectProperty(a:has_pet domain(a:person) range(a:animal))

ObjectProperty(a:is_pet_of inverseOf(a:has_pet))


21


Individual(a:Walt type(a:person)

value(a:has_pet a:Huey)

value(a:has_pet a:Louie)

value(a:has_pet a:Dewey))

Individual(a:Huey type(a:duck))

Individual(a:Dewey type(a:duck))

Individual(a:Louie type(a:duck))

DifferentIndividuals(a:Huey a:Dewey a:Louie)

Class(a:animal_lover complete intersectionOf(a:person restriction(a:has_pet minCardinality(3))))


22


Individual(a:Minnie type(a:female) type(a:elderly) value(a:has_pet a:Tom))

Individual(a:Tom type(owl:Thing))

ObjectProperty(a:has_pet domain(a:person) range(a:animal))

Class(a:old_lady complete

intersectionOf(a:person a:female a:elderly))

Class(a:old_lady partial intersectionOf(

restriction(a:has_pet allValuesFrom (a:cat))

restriction(a:has_pet someValuesFrom (a:animal))))


23

Agenda







24A recent empirical investigation of the occurrence of ontology concepts in LOD (Glimm, Hogan, Krötzsch, Polleres, Proc. LDOW 2012)

Note: the y axis is scaled logarithmically


25

(table is longer in the paper)


26

Agenda







27

Properties and existential restrictions


28

Primitive and defined classes


29

Open world reasoning (1)


30

Open world reasoning (2): Is this a Margherita Pizza?


31

Open world reasoning (3): closure restrictions/axioms


32

Domain and range restrictions are axioms


33

Does „only“ (allValuesFrom) imply „some“ (someValuesFrom)?


34

„and“ and „or“ in logics vs. in natural language


35

„some not …“ vs. „not some …“


36

Task for the next week

Find 3 ontological statements on the Semantic Web, for example using Sindice.

Paraphrase what they mean.

Find 1 statement involving owl:EquivalentClass . What problems are likely to arise when statements made about this class (with its two names) come from different knowledge sources?


37

Outlook






Combining SW data: Schema/ontology matching


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Used sources

p. 8: OWL specification at

http://www.w3.org/TR/owl-ref/ resp. http://www.w3.org/TR/owl2-overview/

Difference between OWL Lite, DL, and Full by Ritesh Agrawal (2007) at http://ragrawal.wordpress.com/2007/02/20/difference-between-owl-lite-dl-and-full/

pp. 12-21: Bechhofer, S. (2003). OWL Reasoning Examples. http://owl.man.ac.uk/2003/why/20031203

pp. 24f: Glimm, B., Hogan, A., Krötzsch, M., & Polleres, A. (2012). OWL: Yet to arrive on the Web of Data? In the Proceedings of the Linked Data on the Web WWW2012 Workshop (LDOW 2012). Available at http://arxiv.org/abs/1202.0984

pp. 27-35: Alan L. Rector, Nick Drummond, Matthew Horridge, Jeremy Rogers, Holger Knublauch, Robert Stevens, Hai Wang, Chris Wroe: OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns. EKAW 2004: 63-81.

http://www.co-ode.org/resources/papers/ekaw2004.pdf

Picture credits: see PPT „comments“ field

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