An introduction to Knowledge Graphs for FDA Department of Regulatory Science Technology Forum 2020-08-17. Includes SPARQL querying, SHACL, 3D visualization.

1. A Conversation with PHUSE,
Stardog, and FDA DRSI
Knowledge Graphs: Changing
How We Think About Data.

2. Presenters
Tim Williams
• Knowledge Graph Project Lead, PHUSE
• Lead Statistical Solutions Analyst, UCB Biosciences
Laura Firey
• Product Manager, Stardog
2

3. • Knowledge Graphs [ ~20 min]
• Cross Industry Perspective [~10min]
• Open Discussion [~30min]
Outline
Most important: “A Conversation...”
3

4. PHUSE Linked Data Projects
• CDISC Foundational Standards in RDF
• CDISC Conformance Checks
• Reusing Medical Summaries for Enabling Clinical Research
• Regulatory Guidance in RDF
• Clinical Program Design in RDF
• CDISC Protocol Representation Model in RDF
• Analysis Results & Metadata
• RDF Data Cubes for clinical trial results
• Clinical Trials Data as RDF
• Study Data Tabulation Model as Linked Data
• Going Translational with Linked Data
• Study Data Validation and Submission Conformance
• Pre-clinical data + submission metadata
4

5. PHUSE Linked Data Workshop
5

6. Thinking About Data
6

7. Knowledge Graph Data-Centric Model
• Use-case neutral
• Real-world processes,
entities, relationships
Person 1
Hookah
Person 2
• Knowledge Graph as Resource
Description Framework (RDF)
e-Cigarette
smokes
e-Cigarette
smokes smokes smokes
The whiteboard model you draw is the data.
7

8. • Shared Definitions and Understanding
– What is a Tobacco Product?
– Who is a Tobacco User?
• Coding of
– Medical Conditions
– Adverse Events
– Products, Manufacturers
• Data Classification, Rules, Validation..
• Ontology Driven/Supported
Knowledge Graphs Facilitate Standards
8

9. • Dictionary
– terms and their definitions
• Taxonomy
– class hierarchy
• Thesaurus
– relationships between terms
Ontology-based Knowledge Graph Standards
• Rules and Restrictions
– Group membership, exclusions, types
– Employ reasoner, infer values, relations
A Data Engineer’s Guide to Semantic Modelling
Ilaria Maresi (June 2020)
http://blog.thehyve.nl/news/ebook-semantic-model
What is an Ontology?
9

10. Standards: Identifier Examples
1,2,3-TrihydroxypropaneGlycerolGlycerin
http://dbpedia.org/page/GlycerolGlycerin
• Common terminology • Link to other Knowledge Graphs
• Manufacturers• Devices
• Products • Ingredients
RDF
• Uniform Resource Identifier (URI)
• Internationalized Resource Identifier (IRI)
10

11. • What ingredient may have
contributed to Pam having
COPD while Ray does not?
Knowledge Graph: Easy Answers to Complex Questions
COPD
11

12. Ray_GillettePam_Poovey
COPD
Hookah smokes
smokes
smokes
smokes
e-Cigarette e-Cigarette
:man_v241kz
Hookah_Me_Up!
Tobacco
:ing_a6766s
Dried_Mint
:ing_2we3q4
Honey Glycerin
:ing_xr7234:ing_3j6g2i
manufacturer:pro_81fq21
contains
ingredient
Mint_Shisha
Mint_Flavor
:ing_hjk66g
Nicotine
:ing_q77e3u:man_5ez82i
e-CignatureMango_Flavor
:ing_4fg421
Nicotine
:ing_q77e3u
contains contains
: pro_0wq01h:pro_a60e2b
ingredientingredient manufacturer
Mango_Flavor_Pod Mint_Flavor_Pod
:dev_zr10q2
:dev_u18lsd :dev_aq174h
:per_452h78:per_xp52kl
sex
age
wt
sex
age
wt
12

13. Exposure Data View the interactive
visualization at:
https://bit.ly/PamAndRay
Data error
Person
Demographics
Entity Type
Device
Ingredients
Product
Manufacturer
13

14. This seems complicated!
“People think RDF is a pain because it
is complicated. The truth is even
worse. RDF is painfully simplistic, but
it allows you to work with real-world
data and problems that are horribly
complicated.”
- attributed to Dan Brickley and Libby Miller
14

15. Data
https://bit.ly/PamAndRayTTL
View the data file at:
15

16. Pam’s Unique Exposure Ingredient?
PamUniqueIngred.rq
16

17. • Who is a TobaccoUser ?
Ontology Revisited
• uses
• smokes
• consumes
• chews ...
User Tobacco
• What is a TobaccoProduct?
Tobacco
Hookah
Cigar
e-Cigarette
Cigarette
contains
contains
contains
? ?
Mint_Shisha
Corojo
Virginia
Mango_Flavor_Pod
contains
ingredient
ingredient
ingredient
ingredient
contains ingredient
:Person
:Device
:Device :Product :Ingredient
:Product
:Ingredient
17

18. Ray_Gillette
:per_452h78
Pam_Poovey
:per_xp52kl
:dev_zr10q2
:man_v241kz
:dev_u18lsd
Hookah_Me_Up!
:dev_aq174h
Hookah
Tobacco
:ing_a6766s
Dried_Mint
:ing_2we3q4
Honey Glycerin
:ing_xr7234:ing_3j6g2i
smokes
contains contains
manufacturer
: pro_0wq01h:pro_a60e2b
smokes
smokes
smokes
:pro_81fq21
contains
e-Cigarette e-Cigarette
Mint_Shisha
Mango_Flavor_Pod Mint_Flavor_Pod
sex
age
wt
sex
age
wt
ingredient
Tobacco Smoker: The path between Person and Ingredient
:Ingredient
:Product
:Device:Person :Person
18

19. Query: Tobacco Users
TobaccoUsers.rq
19

20. Tobacco Smoker: Ontology Definition & Query
TobaccoSmoker-Infer.rq
20

21. Data Validation
Validating Ray’s Demographics data
21

22. SHApes Constraint Language (SHACL)
“Person Shape”
(Validation Constraints) Person Data
Data Has Shape. Validation has Shape.
22

23. SEX AGE
M
SHACL
Person Shape
WEIGHT
Demographics
sex: M
age: 43
wt: 165
Validating Ray’s Demographics
Ray Gillette
Data Entry
M/F/U
165
403
> 0
< 800
> 0
< 120
Violation!
23

24. Validating Age with SHACL
https://bit.ly/RayDemogAndSHACL
View the interactive
visualization at:
Instance Data SHACL Shape
24

25. Demographics, Constraints, Report
https://bit.ly/RaySHACLResult
View the interactive
visualization at:
Instance Data
SHACL Shape
Validation Result
25

26. Metadata is Part of the Graph
Ray_Gillette
M
165
sex
age
wt
2020-08-01
Duke U. Clinic
Dr. A. Krieger
enteredBy
site
entryDate
:per_g367k1
403:per_452h78
26

27. FAIR Data
https://www.go-fair.org/fair-principles/
• Ontologies Mapping
https://www.pistoiaalliance.org/projects/current-projects/ontologies-mapping/
• FAIR Implementation Project & Toolkit
https://www.pistoiaalliance.org/projects/current-projects/fair-implementation/
Findable Accessible Interoperable Reusable
FAIR Data is Linked Data is a Knowledge Graph
27

28. Knowledge Graphs :
Now for a cross-industry perspective
28

29. Additional Reading
General / Introductory
• A Data Engineer’s Guide to Semantic Modeling - Maresi . Free e-book download.
• The Data Centric Revolution - McComb
Technical
• Semantic Web for the Working Ontologist (3rd Ed, 2020) – Hendler, Gandon, Allemang
• Demystifying OWL for the Enterprise – Uschold, Ding, Groth
• Validating RDF Data – Gayo, Prud’hommeaux, Boneva . Comparison of SHEX and SHACL.
• Learning SPARQL - DuCharme . Learn RDF by querying the data.
• 3D-force-graph Network graph visualizations in this presentation.
https://bit.ly/PamAndRay
https://bit.ly/RayDemogAndSHACL
https://bit.ly/RaySHACLResult https://bit.ly/PamAndRayTTL
Pam and Ray Exposure Data
29

30. Reference Slides
30

31. The Roofshot / Moonshot Manifesto
Concept & Image Attribution: https://rework.withgoogle.com/blog/the-roofshot-manifesto/
Examples
1. Unique Identifiers
2. Validation Rules in SHACL
3. Open Ontology Development for your domain
Invent and apply state-
of-the-art
Roofshot
Incremental impacts
in production
Moonshot
• Enterprise and Industry
Knowledge Graphs
• Across the Data Life Cycle
31

32. Industry Knowledge Graphs
Demonstrations
Results Data as RDF
Enterprise Knowledge Graphs
Prototype
Industry Standards & Models
Terminology and Coding
The Stairway
to the Stars
Manifesto
32
Unique Identifiers for Pharma
Validation Rules in SHACL
Study Design
Study Protocol