AAG 2014 Talk on Ontology Views, Reusue, Alignment

LINKED SPATIOTEMPORAL DATA ONTOLOGIES/VOCABULARIES VIEWS
SEMANTIC SHORTCUTS AND VIEWS:
BRIDGING THE GAP BETWEEN
ONTOLOGIES AND LINKED DATA
Krzysztof Janowicz, Pascal Hitzler, and Adila Krisnadhi
STKO Lab, University of California, Santa Barbara, USA
DaSe Lab, Wright State University, USA
AAG Meeting 2014
SEMANTIC SHORTCUTS AND VIEWS JANOWICZ, HITZLER, KRISNADHI

LINKED DATA MOTIVATION
LINKING DATA AS NEXT-GENERATION INFRASTRUCTURE
Data Silos
Web services
Databases
Web pages
hinder ad-hoc combination
enforce data models
limit re-usability

FROM LINKED DOCUMENTS TO LINKED DATA
Use Uniform Resource Identiﬁers (URI) to identify entities, link them to other
entities, encode information about these entities using the
machine-understandable RDF, and make them available on the Web.

BERNERS-LEE’S LINKED DATA PRINCIPLES AND STARS
Four Rules for Linked Data
Use URIs as names for things
Use HTTP URIs so that people can look up those names.
When someone looks up a URI, provide useful information, using the standards
(RDF*, SPARQL)
Include links to other URIs. so that they can discover more things.
Is your Linked Open Data 5 Star?
Available on the web (whatever format) but with an open licence, to be Open Data
Available as machine-readable structured data (e.g. excel instead of image
scan of a table)
as (2) plus non-proprietary format (e.g. CSV instead of excel)
All the above plus, Use open standards from W3C (RDF and SPARQL) to
identify things, so that people can point at your stuff
All the above, plus: Link your data to other people’s data to provide
context
See http://www.w3.org/DesignIssues/LinkedData.html

EXPLORING AND QUERYING LINKED DATA
EXPLORING LINKED DATA ABOUT PLEACES, PEOPLE, EVENTS
Follow-your-nose: Explore information using Linked Data (DBpedia).

EXPLORING AND QUERYING LINKED DATA
HOW TO QUERY LINKED DATA (OVER MULTIPLE SOURCES)?
Integration by searching equivalent classes or/and same features
in data sets. This requires ontologies/vocabularies, their alignment,
and/or ontology reuse.

VOCABULARY STAR RATING
ONTOLOGIES TO MAKE YOUR DATA MORE USABLE
Five Stars of Linked Data Vocabulary Use
Linked Data without any vocabulary.
There is dereferencable human-readable information about the used
vocabulary.
The information is available as machine-readable explicit
axiomatization of the vocabulary.
The vocabulary is linked to other vocabularies
Metadata about the vocabulary is available (in a dereferencable
and machine-readable form).
The vocabulary is linked to by other vocabularies.
See http://semantic-web-journal.net/content/
five-stars-linked-data-vocabulary-use

VOCABULARY REUSE
VOCABULARY/ONTOLOGY REUSE
A typical statement:
’Reuse external vocabulary whenever possible.’
<http://dbpedia.org/resource/Copernicus_(lunar_crater)>
...
geo:lat
"9.7"^^xsd:decimal;
geo:long
"20.0"^^xsd:decimal;
...
a
dbpedia-owl:Crater,
...
ns5:Place,
...
Concerns:
Most ontologies are under-speciﬁc, how are they maintained,
versioning /evolution strategies are unclear, contact persons, are
they community-driven, legal issues, proper documentation,...?

VOCABULARY REUSE
REUSE DIFFICULTIES EXAMPLE
The Fluidops interface renders the DBpedia RDF data from the
Copernicus crater and places it on the Surface of the Earth instead of
realizing that the given coordinates are selenographic coordinates.

VOCABULARY ALIGNMENT
VOCABULARY/ONTOLOGY ALIGNMENT
Alternative statement:
’Align your vocabulary to other vocabulary whenever possible.’
dbpedia − owl : Crater ADL: Crater (1)
dbpedia − owl : Person ≡ FOAF : Person (?) (2)
Concerns:
Most ontologies are under-speciﬁc, requires reasoning, simple
alignments may not be sufﬁcient (despite improving tool
support),...?

VOCABULARY ALIGNMENT
VOCABULARY/ONTOLOGY ALIGNMENT DIFFICULTIES
a:flowsInto a:IsConnected (1)
a:IrrigationCanal a:Canal (2)
∃a:flowsInto.a:AgriculturalField a:IrrigationCanal (3)
a:Waterbody a:Land ⊥ (4)
a:AgriculturalField a:Land (5)
b:flowsInto b:IsConnected (6)
b:Canal (≥2 b:IsConnected.b:Waterbody) (7)
b:IrrigationCanal ≡ (=1 b:isConnected.b:Waterbody)
(=1 b:flowsInto.b:AgriculturalField) (8)

WHAT/HOW TO MODEL?
FRAGMENT OF A MAP LEGEND ONTOLOGY DESIGN PATTERN
Ontological commitments
Should Geographic
Feature Types be classes
or instances?
Do we want to explicitly
deﬁne the depictedBy
relation
Is stating that a Legend
consists of LegendItems
redundant?
. . .

INSTANCES VS. CLASSES
MODELING DIFFERENCES: INSTANCES VS. CLASSES
As illustrated before alignments and mappings can be difﬁcult
However, often, even major modeling differences can be aligned/mapped
Instances vs. classes
Florence rdf : type City (1)
Florence xyz : hasType ”City”@en (2)
Mapping between those cases
Classname ∃hasType.{classname} (3)
∃hasType.{classname} Classname (4)

ROLE CHAINS
FRAGMENT OF THE MAP LEGEND ONTOLOGY
NC = {LegendItem, Symbol, Label, FeatureType} (1)
NR = {consistsOf, isLabelFor, isLabelOf, depictedBy} (2)
¬∃N. (3)
LegendItem ∃consistsOf.Symbol ∃consistsOf.LegendItem (4)
Label ∃SymbolizedBy.Symbol ∀SymbolizedBy.Symbol (5)
≤ 1isLabelFor. (6)
≤ 1isLabelOf. (7)
≤ 1SymbolizedBy. (8)
Label ∃isLabelFor.FeatureType (9)
Label Symbol ⊥ (also for Symbol, Label, FeatureType, LegendItem) (10)
isLabelOf−
◦ isLabelFor depictedBy−
(11)
¬∃consistsOf−
Legend (12)
. . . (13)

ANOTHER SIMPLE VIEW EXAMPLE
SIMPLE VIEW FOR THE AGENT ONTOLOGY PATTERN STUB
Guarded domain and range restrictions of performsAgentRole
∃performsAgentRole.AgentRole Agent (1)
Agent ∀performsAgentRole.AgentRole (2)
Pairwise-disjointness axiom
Agent AgentRole ⊥ (3)
This axiom provides the role isPerformedBy as a view for the pattern.
performsAgentRole−
isPerformedBy (4)

AAG 2014 Talk on Ontology Views, Reusue, Alignment

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AAG 2014 Talk on Ontology Views, Reusue, Alignment