Principles for knowledge engineering on the Web

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Principles for knowledge
engineering on the Web
Guus Schreiber
VU University Amsterdam
Computer Science, Web & Media

Overview of this talk
• Semantic Web: the digital heritage case
• Knowledge-engineering principles
• Challenges for Web KE

My journey
knowledge engineering
• design patterns for
problem solving
• methodology for
knowledge systems
• models of dom...

My journey
access to digital heritage

My journey
Web standards
• Web metadata: RDF
• OWL Web Ontology Language
• SKOS model for publishing vocabularies
on the W...

SEMANTIC WEB: THE
DIGITAL-HERITAGE CASE

The Web:
resources and links
URL URL
Web link

The Semantic Web:
typed resources and links
URL URL
Web link
ULAN
Henri Matisse
Dublin Core
creator
Painting
“Woman with h...

Vocabulary interoperability: SKOS

Vocabulary representations
• SKOS has been a major success
• Easy to understand and create
• LCSH publication set importan...

The myth of a unified vocabulary
• In large virtual collections there are always multiple
vocabularies
– In multiple langu...

Example use of vocabulary
alignment
“Tokugawa”
SVCN period
Edo
SVCN is local in-house
ethnology thesaurus
AAT style/period...

Enriching metadata with
concepts

Learning vocabulary
alignments
• Example: learning relations between art
styles and artists through NLP of art
historic te...

Semantic search: result clustering
based on retrieval path

Research issues
• Information retrieval as graph search
– more semantics => more paths
– finding optimal graph patterns
• ...

Personalized Rijksmuseum
• Interactive user
modeling
•Recommendations of
artworks and art topics

Mobile museum tour

KNOWLEDGE ENGINEERING
PRINCIPLES
Lessons I learned

Principle 1: Be modest!
• Ontology engineers should refrain from
developing their own idiosyncratic
ontologies
• Instead, ...

Principle 2: Think large!
"Once you have a truly massive amount of
information integrated as knowledge, then the
human-sof...

Principle 3: Develop and use
patterns!
• Don’t try to be (too) creative
• Ontology engineering should not be an
art but a ...

Principle 4: Don’t recreate, but
enrich and align
• Techniques:
– Learning ontology relations/mappings
– Semantic analysis...

Principle 5: Beware of ontological
over-commitment!

Principle 6: writing in an ontology
language doesn’t make it an ontology!
• Ontology is vehicle for sharing
• Papers about...

Principle 7: Required level of formal
semantics depends on the domain!
• In our semantic search we use three
OWL construct...

CHALLENGES FOR WEB KE

Challenge: Linked Open Data

Availability of government data:
http://data.gov.uk

The fight for “standard” semantics
Schema.org

Challenge: vocabulary
alignment methodology
• Multitude of alignment techniques
available
– Direct syntactic match
– Lexic...

Limitations of categorical
thinking
• The set theory on which ontology languages are
built is inadequate for modelling how...

Challenge: new types of search
exploiting semantics

Relation search:
Picasso, Matisse & Braque

Challenge: combining professional
annotations with public “tags”

Challenge: data trust issues
• How can a museum trust annotations of
outsiders?
• Need to adapt techniques from closed
wor...

Challenge: event-centred approach
=> people like narratives

Extracting piracy events
from piracy reports & Web sources

Visualising piracy events

Large-scale
experimentation!

TOWARDS WEB SCIENCE

We need to study the Web as a
phenomenon
• Web dynamics
• Collective intelligence
• Privacy, trust and
security
• Linked o...

Web for
Social
Development
48

Acknowledgements
• Long list of people
• Projects: MIA, MultiemdiaN E-Culture,
CHOICE, MunCH, CHIP, Agora,
PrestoPrime, No...

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