Coastal Atlas Interoperability - Ontologies

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22 Οκτ 2013 (πριν από 3 χρόνια και 9 μήνες)

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Coastal Atlas Interoperability
-

Ontologies

(Advanced topics that we did not get to in detail)

Luis Bermudez

Stephanie Watson

Marine Metadata Interoperability Initiative

1

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

2

3

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

4

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

4

5

Mapping ala SKOS


import skos.owl


it defines 3 convenient properties to relate
instances

6

Import the
2
atlas ontologies

that were created by the
2
groups

7


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 skos:relation (broad, narrow,
exact match) to a topic from one of the atlases.


Need to add the
skos:property

in the
Resource Form

8

Adding SKOS Property(ies) in Resource Form

Drag and drop

9


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

10

Categorization by properties

or

the world of restrictions

or

defining classes using Description
Logics (DL)


11

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.

12

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.

13

SuperAtlas Ontology

14

Process


Import SuperAtlas Ontology


Create a class “PersonRecreationalFeature” which
is a sub (or sub
-
sub) class of
your:PersonConcept



make it subclass of superatlas:RecreationalFeature

15

Create features

(e.g. places that could appear in
an atlas)

16

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

17

You should have 4 instances similar to these:

18

Defining Classes using
Description Logics


19

Defining a Class in OWL DL

Example: Define
EuropeanRegion

= All regions that are part of Europe.

More formally:

Equivalent Restrictions

European Region

Classifies UnitedKingdom

run inference

If it is known that an individual is a
European Region
, it can
be inferred that it isPartOf Europe and it’s 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

Subclass Restrictions

European Town

Classifies EuropeanTown

If it is known that an individual is a
European Town
, it can
be inferred that isPartOf a European Region and it’s 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

run inference

22

Restriction Keywords

23

Restriction Keywords (cont.)

24

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.



25

Restrictions Exercise

Create a WebCategory class with these subclasses:


-

AmericanRegion

-

SwimmingPlacesInAmerica

.....

BREAK 10:30
-
10:45

78

SPARQL AND RULES

78

SPARQL


Query language for RDF (similar to SQL)


Think
-

triple triple triple

78

How many triple matches the pattern:


x

rdfs:type
y


superAtlas:Swimming
x y


superAtlas:Swimming rdf:type

x






SPARQL Examples

PREFIX table:
<
http://www.daml.org/2003/01/periodictable/Per
iodicTable#
>

SELECT ?name ?symbol ?number ?color

FROM
<
http://www.daml.org/2003/01/periodictable/Per
iodicTable.owl
>

WHERE

{


?element table:name ?name.


?element table:symbol ?symbol.


?element table:atomicNumber ?number.


OPTIONAL { ?element table:color ?color. }

}

79

30

Examples

SELECT

?subject

WHERE

{ ?subject rdfs:subClassOf superatlas:Feature }


Find all the subclasses of superatlas:Feature

SELECT

?feature

WHERE

{


?feature rdf:type superatlas:Feature.


?feature superatlas:hasActivity ?activity.


?activity rdf:type superatlas:Sports.


}


Find all the features that have an activity of type
Sports

31

Create your own queries


...

Using Rules


OWL is limited in expressiveness.


can’t combine properties (e.g., uncle is a
composition of brother and parent)


can’t 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

33

Rules

Rule is simple:
If A then B
or
A
-
> B

Semantic Web Rule Language (SWRL)

swrl:body
-
> swrl:head


or

using JENA rules
-

very similar syntax

35

Rules Exercise


Import jena.owl

36

Configure Inferencing

1

2

3

4

5

6

37

Example


Create a rule to infer all american sports


Create a class under WebCategories and add a
jena:Rule property (drag it)


e.g. AmericanSports


38

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

39

Ontology
Engineering

40

Ontology
Engineering

41

42

Engineering Lifecycle

From help system TobBraid Composer tutorial

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

44

Slides acknowledgments



Robert Laurini INSA

Lyon

http://lisi.insa
-
lyon.fr/~laurini




TopBraid tutorial