The document discusses the three layers of a knowledge graph: the ontology, taxonomies, and knowledge. It explains that the ontology contains the core business concepts, taxonomies contain controlled vocabularies, and knowledge contains the network of products. It then covers authorship, storage, governance, and data quality considerations for each layer. Authorship can be centralized or decentralized, storage options include triple stores and property graphs, governance involves peer and expert reviews, and data quality is ensured through validation and enabling use cases across layers.

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Systems
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The Three Layers of a
Knowledge Graph
Katariina Kari
Inter IKEA Systems B.V.

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ThreeLayersof a
KnowledgeGraph
and what it means for
authoring,
storage,
governance and
data quality.

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Agenda
Overview of the Knowledge Graph
A Game of 20 Questions
Authorship
Storage
Governance
Data Quality

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Overview
Knowledge Graph

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A new infrastructure combining business concepts
with actual data in a connected network-like form.
This allows for richer insights around products
interior design!
What the knowledge
graph is... and why I
like them!

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Business concepts
central to IKEA
(schema)
The controlled
vocabulary
(instances)
All products in
network
structure
(also instances)

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Business concepts
central to IKEA
= ontology
The controlled
vocabulary
= taxonomies
All products in
network
structure
= knowledge

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A Gameof 20
Questions
Try it at home: Create a Google Form for a game of 20
questions to answer what furniture a player is thinking
of.

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Ontology

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Knowledge

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Authorship

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Centralised and
owned by the
ontology team
Decentralised
and owned by
expert teams.
Automatically
generated from
a data source.
Ownership is at
the source.

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Storage

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RDF file,
TTL syntax
in a Git repo
RDF file,
TTL syntax
in a Git repo
Triple Store for
Browsing and Faceted
Search
Labelled Property
Graph for path
queries.

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Governance

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Review by ontologist peers
and negotiation with domain
experts
Final say by domain expert
teams.
No governance, since
it is generated.

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Data Quality

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Usability of queries,
reasoning capabilities,
enabling use cases.
Reusability for use cases
across.
SHACL validation.

19. Semantic and Transparent ETL Pipelines - Katariina Kari, Lead Ontologist, Inter IKEA Systems B.V.
Questions?
© Inter IKEA Systems B.V. 2022

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IKEA
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Thankyou!
Katariina Kari
@katsi111
/in/katsi/