The document discusses the role of knowledge graphs in data management and governance, highlighting their ability to represent knowledge as interconnected graphs rather than traditional tables. It addresses challenges in data governance and proposes knowledge graphs as a solution to integrate diverse data sources and enhance compliance with regulations like GDPR. Additionally, it outlines how knowledge graphs facilitate better decision-making by enriching data and supporting common searches across business and regulatory contexts.

1. Knowledge Graphs –A Strategic NoSQL Approach for
Data Management and Governance
IRENE POLIKOFF, CEO, TOPQUADRANT
RALPH HODGSON, CTO,TOPQUARANT
March 19, 2019

2. © Copyright 2019 TopQuadrant Inc. Slide 2
 The history of knowledge graphs in 90 seconds
 What are today’s key challenges in data governance
 What is a knowledge graph, how does it work
 How do knowledge graphs support data governance
 Demonstrating the use of knowledge graphs for data
governance
TODAY’S AGENDA
Ralph Hodgson
Irene Polikoff

3. FOUNDATION
 TopQuadrant was founded in 2001
 Strong commitment to standards-based approaches to data semantics
MISSION
 Empower people and drive results — by making enterprise information
meaningful
FOCUS
 Provide comprehensive data governance solutions
CUSTOMERS
 Over 120 active customer organizations
WHO WE ARE

4. KNOWLEDGE GRAPHS

5. KNOWLEDGE GRAPHS
Tim Berners Lee
2001
Tim Berners-Lee

6. KNOWLEDGE GRAPHS
Tim Berners Lee
2012
Google
2001
Tim Berners-Lee

7. KNOWLEDGE GRAPHS
Tim Berners Lee
2012
Google
2019
Knowledge Graphs in the
news
> Google on AI and
knowledge graphs in ZDNET
> Data governance 2.0 on
Dataversity
> Conferences & workshops
> Technology trends 2019
> Forbes article by Kurt Cagle
2001
Tim Berners-Lee

8. © Copyright 2019 TopQuadrant Inc. Slide 8
Data governance
> Data represent value
> Usage of data is subject to regulation
> Bookkeeping of data as assets is necessary
“… organizing people, processes, and information technology required
to create a consistent and proper handling of an organization's data
across the business enterprise.” … Wikipedia

9. © Copyright 2019 TopQuadrant Inc. Slide 9
HOW IS IT DONE?
 Ad hoc
 Documents, spreadsheets,
proprietary systems
 Examples:
• GDPR, CCPA
• Data quality
• Data lineage

10. © Copyright 2019 TopQuadrant Inc. Slide 10
The challenges of
data governance
> Galaxies of data
> Diversity of perspectives
> Business
> Technical
> Regulatory
> Diversity of representation
Solution
> Create a knowledge graph representing
data sources
> Link to other relevant enterprise
information e.g., systems, policies,
infrastructure, activities
> Enrich, discover, connect
> Use to guide business decisions

11. © Copyright 2019 TopQuadrant Inc. Slide 11
WHAT IS A KNOWLEDGE GRAPH?
 A Knowledge Graph represents a knowledge domain
 It represents knowledge as a graph
– A network of nodes and links
– Not tables of rows and columns
 It represents facts (data) and models (metadata) in the same way
– Rich rules and inferencing
 It is based on open standards, from top to bottom
– Readily connects to knowledge in private and public clouds

12. © Copyright 2019 TopQuadrant Inc. Slide 12

13. © Copyright 2019 TopQuadrant Inc. Slide 13
mi6:JamesBond mi6:worksFor mi6:MI6 .
mi6:JamesBond rdf:type schema:Person .
mi6:MI6 rdf:type schema:Organisation .

14. © Copyright 2019 TopQuadrant Inc. Slide 14
mi6:JamesBond mi6:worksFor mi6:MI6 .
mi6:JamesBond rdf:type schema:Person .
mi6:MI6 rdf:type schema:Organisation .
SUBJECT PREDICATE OBJECT

15. © Copyright 2019 TopQuadrant Inc. Slide 15
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
mi6:JamesBond mi6:worksFor mi6:MI6 .
mi6:JamesBond rdf:type schema:Person .
mi6:MI6 rdf:type schema:Organisation .

16. © Copyright 2019 TopQuadrant Inc. Slide 16
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
DATA (INSTANCES) GRAPH

17. © Copyright 2019 TopQuadrant Inc. Slide 17
mi6:JamesBond mi6:MI6
schema:Organisationschema:Person
rdf:typerdf:type
SCHEMA (MODEL) GRAPH
mi6:worksFor
schema:Organisationschema:Person
sh:class
sh:path
sh:property
“1”
sh:minCount

18. © Copyright 2019 TopQuadrant Inc. Slide 18
mi6:JamesBond mi6:MI6
schema:Organisationschema:Person
rdf:typerdf:type
KNOWLEDGE GRAPH
schema:Organisationschema:Person
mi6:worksFor
sh:class
sh:path
sh:property
“1”
sh:minCount

19. © Copyright 2019 TopQuadrant Inc. Slide 19
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
mi6:worksFor
schema:Organisationschema:Person
mi6:Q
mi6:worksFor
sh:class
sh:path
sh:property
“1”
sh:minCount

20. © Copyright 2019 TopQuadrant Inc. Slide 20
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
mi6:worksFor
schema:Organisationschema:Person
mi6:Q
mi6:worksFor
mi6:AndrewBond
mi6:VickersDefenseSystems
mi6:father
mi6:worksFor
rdf:type
sh:class
sh:path
sh:property
“1”
sh:minCount

21. © Copyright 2019 TopQuadrant Inc. Slide 21
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
mi6:worksFor
schema:Organisationschema:Person
mi6:Q
mi6:worksFor
mi6:AndrewBond
mi6:VickersDefenseSystems
mi6:father
mi6:worksFor
rdf:type
dbpedia:birthDate
”1920-11-11”
sh:class
sh:path
sh:property
“1”
sh:minCount

22. © Copyright 2019 TopQuadrant Inc. Slide 22
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
mi6:worksFor
schema:Organisationschema:Person
mi6:Q
mi6:worksFor
mi6:AndrewBond
mi6:VickersDefenseSystems
mi6:father
mi6:worksFor
rdf:type
”1920-11-11”
dbpedia:birthDate
dbpedia:Glen_Coe
dbpedia:birthPlace
sh:class
sh:path
sh:property
“1”
sh:minCount

23. © Copyright 2019 TopQuadrant Inc. Slide 23
mi6:JamesBond mi6:MI6
mi6:worksFor
schema:Organisationschema:Person
rdf:typerdf:type
mi6:worksFor
schema:Organisationschema:Person
mi6:Q
mi6:worksFor
mi6:AndrewBond
mi6:VickersDefenseSystems
mi6:father
mi6:worksFor
rdf:type
”1920-11-11”
dbpedia:birthDate
dbpedia:Glen_Coe
dbpedia:birthPlace
dbpedia:Scotland
dbpedia:locatedInArea
dbpedia:Country_of_the_United_Kingdom
dbpedia:status
dbpedia:Edinburgh
dbpedia:capital
sh:class
sh:path
sh:property
“1”
sh:minCount

24. © Copyright 2019 TopQuadrant Inc. Slide 24
KG RULE:
{?x dbpedia:brithPlace ?place.
?place dbpedia:locatedInArea+ ?area .
?area dbpedia:status dbpedia:Country_of_the_United_Kingdom .}
 ?x example:bornIn example:UK
EXECUTE INFERENCE:
If your birth place is in Scotland, you are born in the UK
QUERY:
Select all persons working for MI6 that are born in the UK
L O C A L K N O W L E D G E G R A P H
QUERYING AND INFERENCING
DBPEDIA,
WIKIDATA,
…
COALESCED KNOWLEDGE GRAPH

25. © Copyright 2019 TopQuadrant Inc. Slide 25
AbcAbcAbcAbcAbc
AbcAbcAbcAbcAbc
AbcAbcAbcAbc
§§
AbcAbcAbcAbc
§§
E N T E R P R I S E K N O W L E D G E G R A P H
Real time access Feature extraction Reusable modelsModel ingestion
ENTERPRISE DATA GOVERNANCE

26. © Copyright 2019 TopQuadrant Inc. Slide 26
GDPRSYSTEM X
Regulatory Compliance Ontology
ENTERPRISE KNOWLEDGE GRAPH
RECO
SYSTEM Y

27. © Copyright 2019 TopQuadrant Inc. Slide 27
GDPRSYSTEM X
Regulatory Compliance Ontology
ENTERPRISE KNOWLEDGE GRAPH
RECO
SYSTEM Y
Right
Instances
Obligation
Instances
Action
Instances
RESPONSEDELIVERY
EVENT SITUATIONCAPTURE
POLICY ATTRIBUTION

28. © Copyright 2019 TopQuadrant Inc. Slide 28
 Providing common search for all types of stakeholders
 Connecting business terms to data elements
 Supporting regulatory compliance by tracing data lineage
 Representing regulations as knowledge graphs
– generally (RECO) and specifically (GDPR)
 Inferring rules from data in knowledge graphs
 Connecting public and private knowledge graphs
 Creating enriched knowledge resources
 APIs for knowledge graphs – benefits of GraphQL
DATA GOVERNANCE CHALLENGES 
KNOWLEDGE GRAPH CAPABILITIES
Knowledge Graphs Support
Integrated Data Governance –
top-down, bottom-up and middle-out

29. Enterprise Information Management Landscape
Different Types of
Knowledge Graphs

30. © Copyright 2019 TopQuadrant Inc. Slide 30
DIFFERENT TYPES OF GRAPHS – COMMON SEARCH

31. © Copyright 2019 TopQuadrant Inc. Slide 31
AUTO-DERIVED FACETS – BASED ON THE SEARCH RESULTS

32. © Copyright 2019 TopQuadrant Inc. Slide 32
NAVIGATING ACROSS CONNECTED GLOSSARIES TO
DATA ELEMENTS
Investment services
client from the SEC
Glossary
General term
“client” from the
ITIL Glossary
Same term name, but different identity. Each
term is uniquely identified by its own URI.

33. © Copyright 2019 TopQuadrant Inc. Slide 33
DRILLING INTO THE DATA ELEMENT INFORMATION

34. © Copyright 2019 TopQuadrant Inc. Slide 34
DRILLING INTO THE DATA ELEMENT INFORMATION
Mapped to the “client” term from the SEC
Glossary

35. © Copyright 2019 TopQuadrant Inc. Slide 35
DRILLING INTO THE DATA ELEMENT INFORMATION

36. © Copyright 2019 TopQuadrant Inc. Slide 36
DRILLING INTO THE DATA ELEMENT INFORMATION

37. © Copyright 2019 TopQuadrant Inc. Slide 37
USE CASE SPECIFIC GRAPH EXPLORATION – TO UNDERSTAND
LINEAGE OF DATA IN A REGULATORY REQUIRED REPORT

38. © Copyright 2019 TopQuadrant Inc. Slide 38
MORE THAN ONE
TYPE OF LINEAGE
CAN BE TRACED AND
PRESENTED:
LINK TYPES IN THE
LINEAGE DIAGRAMS

39. © Copyright 2019 TopQuadrant Inc. Slide 39
SYSTEM Y
DRILLING IN TO UNDERSTAND DETAILS BEHIND THE INFERRED
CONNECTION: FROM A HIGH LEVEL TO A DETAILED VIEW

40. © Copyright 2019 TopQuadrant Inc. Slide 40
WHAT IS MEANT BY “CONSENT IMPLIED BY CONTRACT”
GDPR

41. © Copyright 2019 TopQuadrant Inc. Slide 41
GDPR
KNOWLEDGE GRAPH OF GDPR REGULATION

42. © Copyright 2019 TopQuadrant Inc. Slide 42
Regulatory Compliance Ontology
RECO
KNOWLEDGE GRAPH OF RECO – MODEL FOR DESCRIBING
REGULATIONS

43. © Copyright 2019 TopQuadrant Inc. Slide 43
GDPRSYSTEM X
Regulatory Compliance Ontology
ENTERPRISE KNOWLEDGE GRAPH
RECO
SYSTEM Y
Right
Instances
Obligation
Instances
Action
Instances
RESPONSEDELIVERY
EVENT SITUATIONCAPTURE
FROM DATA SOURCE TO THE OBLIGATION
AND ITS MEANING

44. © Copyright 2019 TopQuadrant Inc. Slide 44
 Common Search for all types of stakeholders
 Connecting business terms to data elements
 How data lineage supports regulatory compliance
 Representing regulations as knowledge graphs
– generally (RECO) and specifically (GDPR)
 Inferring rules from data in knowledge graphs
 Connecting public and private knowledge graphs
 Creating enriched knowledge resources
 APIs for knowledge graphs – benefits of GraphQL
KNOWLEDGE GRAPHS IN ACTION

45. © Copyright 2019 TopQuadrant Inc. Slide 45
Enriched KG of the
Data Source
Data Source
KG of the Data Source
MACHINE
LEARNING
FROM: RULES IMPLICIT IN DATA
TO: RULES EXPLICIT IN A KNOWLEDGE GRAPH
METADATA
Data Source
DATA SAMPLE
RULES

46. © Copyright 2019 TopQuadrant Inc. Slide 46
MAKING RULES IMPLICITLY PRESENT IN DATA,
BE EXPLICITLY REPRESENTED IN A KNOWLEDGE GRAPH
For example, based on the data, what rules can
we learn about who can get a loan?
Should have high credit rating, income-to-loan
ratio above a certain number, etc.
LEARNED FACTS, EXPRESSED
AS RULES, ARE:
• REVIEWED FOR THE
INCLUSION IN THE
KNOWLEDGE GRAPH
• ONCE INCLUDED, USED IN
FURTHER PROCESSING

47. © Copyright 2019 TopQuadrant Inc. Slide 47
 Common Search for all types of stakeholders
 Connecting business terms to data elements
 How data lineage supports regulatory compliance
 Representing regulations as knowledge graphs
– generally (RECO) and specifically (GDPR)
 Inferring rules from data in knowledge graphs
 Connecting public and private knowledge graphs
 Creating enriched knowledge resources
 APIs for knowledge graphs – benefits of GraphQL
KNOWLEDGE GRAPHS IN ACTION

48. © Copyright 2019 TopQuadrant Inc. Slide 48
STANDARDS BASED KNOWLEDGE GRAPHS CONNECT
PUBLIC AND PRIVATE KNOWLEDGE

49. © Copyright 2019 TopQuadrant Inc. Slide 49
STANDARDS BASED KNOWLEDGE GRAPHS CONNECT
PUBLIC AND PRIVATE KNOWLEDGE

50. © Copyright 2019 TopQuadrant Inc. Slide 50
CREATING ENRICHED KNOWLEDGE RESOURCES

51. © Copyright 2019 TopQuadrant Inc. Slide 51
 Common Search for all types of stakeholders
 Connecting business terms to data elements
 How data lineage supports regulatory compliance
 Representing regulations as knowledge graphs
– generally (RECO) and specifically (GDPR)
 Inferring rules from data in knowledge graphs
 Connecting public and private knowledge graphs
 Creating enriched knowledge resources
 APIs for knowledge graphs – benefits of GraphQL
KNOWLEDGE GRAPHS IN ACTION

52. © Copyright 2019 TopQuadrant Inc. Slide 52
WHAT IS GRAPHQL
 GraphQL is an application layer query language.
– Meaning that GraphQL is designed to interpret a string from a server
or client and return that data in an understandable, stable, and
predictable format.
 Developed by Facebook for internal use
 Open sourced in 2016
 Rapidly growing in popularity, replacing REST style APIs
“Describe your data, ask for what you want, get predictable results.”
https://graphql.org/

53. © Copyright 2019 TopQuadrant Inc. Slide 53
KNOWLEDGE GRAPH APIs
GRAPHQL
ACCESS with
INTROSPECTION

54. © Copyright 2019 TopQuadrant Inc. Slide 54
Connecting
Cataloging
Curating
GOVERNANCE OF ENTERPRISE
DATA ASSETS REQUIRES:
 Collaborating
Governance Workflows, Roles and Metrics as Knowledge Graphs

55. © Copyright 2019 TopQuadrant Inc. Slide 55
 Flexible and extensible based on standards
 Integrates reasoning and machine learning
 Enables people (UI) and software (APIs/web
services) to view, follow and query
 Bridges data and metadata “silos” for a
seamless data governance
 Delivers Knowledge-driven data governance
BENEFITS OF A KNOWLEDGE GRAPH BASED PLATFORM
FOR SUPPORTING DATA GOVERNANCE 2.0

56. © Copyright 2019 TopQuadrant Inc. Slide 56
… Questions?
VISIT US AT BOOTH #44
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