5. 5ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 5
Kennisnet supports
schools with IT.
Provides a basic IT-
infrastructure and
shares knowledge.
Maintains several
standards for
information exchange.
6. 6ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 6
Publication office for
the Dutch
government
organisations.
Maintains value lists
that have a legal
status, e.g., the list of
municipalities.
7. 7ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 7
Wolters Kluwer Legal &
Regulatory offers
information, software and
tools for legal
professionals.
Business vocabularies for
knowledge management
and search.
8. 8ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 8
Alliander is an energy
network company. We are
bringing an open and
sustainable energy market
closer to the consumer.
Maintains several large
business vocabularies and
large amounts of
technical documents.
9. 9ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 9
The Netherlands Institute
for Sound and Vision is a
cultural-historical
organization. It collects,
preserves and opens the
audiovisual heritage.
Maintains several large
thesauri.
10. 10ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 10
The Netherlands’
Cadastre, Land Registry
and Mapping Agency – in
short Kadaster – collects
and registers
administrative and spatial
data on property and the
rights involved.
Publishes Linked Data on
a large scale.
11. 11ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• Wolters Kluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 11
The Dutch police uses
Linked Data-technologies
to collate data from
disparate sources.
12. 12ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• WoltersKluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 12
CROW is a non-profit
knowledge partner in
road construction.
CROW maintains thesauri
and a large knowledge
base.
13. 13ggg
Our LD-Portfolio: A Snapshot
• Kennisnet
• KOOP
• WoltersKluwer NL
• Alliander
• Beeld en Geluid
• Kadaster
• National Police
• CROW
• OntoPharma
SEMANTiCS 2017 13
OntoPharma, a spin-off of
Taxonic, delivers solutions
for a Data First-approach in
the pharma sector.
Solutions include
automated data extraction,
management of reference
data and product data, and
structured authoring.
16. 16ggg
Use Cases
SEMANTiCS 2017 16
Business vocabularies
Reference Data
Management
Collating business concepts across vocabularies
Vocabulary-
oriented
Data-oriented
Documents and
data
17. 17ggg
Use Cases
SEMANTiCS 2017 17
Business vocabularies
Reference Data
Management
Collating business concepts across vocabularies
Vocabulary-
oriented
Data-oriented
Documents and
data
Publishing interoperable data
Publishing datamodels Managing datasets
18. 18ggg
Use Cases
SEMANTiCS 2017 18
Business vocabularies
Reference Data
Management
Collating business concepts across vocabularies
Vocabulary-
oriented
Data-oriented
Documents and
data
Publishing interoperable data
Publishing datamodels Managing datasets
Semantic ECM
Tagging
Extraction
Indexing
Content
Classification
Structured Authoring
20. 20ggg
Business vocabularies
Publishing interoperable data
Managing datasets
Managing metadata sets
Semantic ECM
Reference Data Management
Collating business concepts across vocabularies
Publishing datamodels
Relative contribution 2017
SEMANTiCS 2017 20
21. 21ggg
Business vocabularies
Publishing interoperable data
Managing datasets
Managing metadata sets
Semantic ECM
Reference Data Management
Collating business concepts across vocabularies
Publishing datamodels
Expectations of Relative Growth
SEMANTiCS 2017 21
22. 22ggg
Collating concepts across vocabularies
Kennisnet
• Develops standards for
information exchange in the field
of education
• Overlapping semantics
• Same concepts in different models
• Specialized tooling
• TopQuadrant Enterprise Vocabulary
Network
• Custom concept browsers for
visualizing semantic overlap
24. 24ggg
> The browser shows info about the term “Samengestelde groep”
> This term is defined in EDEXML, a data exchange standard
25. 25ggg
> The browser shows info about the term “Samengestelde groep”
> This term is defined in EDEXML, a data exchange standard
> Also occurs in UWRL and ECKID
> The browser shows a detailed comparison
> Similarities and differences made visible
> High level of automation
26. 26ggg
The potential for Semantic ECM
Data First
• From documents to data
• Regulatory requirements
• Data extraction as a service
• Future outlook: create data
and documents in concert
27. 27ggg
Advanced algorithms for extracting data
Extracting
concepts not
literally
mentioned in
the text
Source Text
The tablets shall be taken with
liquid, and should not be crushed or
chewed. Ontopharmanax may be
taken with or without food
Extracted data
RoutesOfAdministration
{
“routes”: [“OralUse”]
}
Source Text
Ontopharmanax is for
subcutaneous injection only and
shall not be used for intramuscular
injection.
Extracted data
RoutesOfAdministration
{
“routes”: [
“SubcutaneousInjection”
]}
Dealing with
negations.
28. 28ggg
The potential for Semantic ECM
Serve information in the field
• Operatives need specific
information
• Buried in documents
• Semantic Search
• Auto-tagging, extraction,
indexation
• Future outlook: template-
based authoring
29. 29ggg
Semantic ECM
• Semantic ECM is transformational
• Affects many processes in many ways
• Authoring
• Redacting
• Retrieval
• Difficulty is structurally underestimated
• Complexity
• Need for solid know-how and the right tools
• Many projects start and then fail miserably
• Still much evangelizing needed!
SEMANTiCS 2017 29
32. 32ggg
• Open Source
• Created by Taxonic, with Kadaster
• RML standard for mapping &
transformation
• From relational to RDF
• From any format to RDF
• First release now available from
Github!
• https://carml.gitlab.io/plain-html/
