LET'S MAKE A KNOWLEDGE GRAPH! A HANDS-ON, INTERACTIVE, LINKED DATA - - PowerPoint PPT Presentation

let s make a knowledge graph a hands on interactive
SMART_READER_LITE
LIVE PREVIEW

LET'S MAKE A KNOWLEDGE GRAPH! A HANDS-ON, INTERACTIVE, LINKED DATA - - PowerPoint PPT Presentation

LET'S MAKE A KNOWLEDGE GRAPH! A HANDS-ON, INTERACTIVE, LINKED DATA WORKSHOP PHUSE CSS 2019 Silver Spring, MD 2019-06-09 1 INSTRUCTOR Tim Williams Principal Statistical Solutions Analyst UCB BioSciences tim.williams@PhUSE.eu Assisted by:


slide-1
SLIDE 1

LET'S MAKE A KNOWLEDGE GRAPH! A HANDS-ON, INTERACTIVE, LINKED DATA WORKSHOP

PHUSE CSS 2019

Silver Spring, MD 2019-06-09

1

slide-2
SLIDE 2

INSTRUCTOR

Tim Williams Principal Statistical Solutions Analyst UCB BioSciences Assisted by: Nolan Nichols (Genentech) Content from: Johannes Ulander (S-Cubed) tim.williams@PhUSE.eu

2

slide-3
SLIDE 3

PREPARATION Your laptop [Power up!] Copy of:

  • 1. Exercises
  • 2. Graph Editor

Introduction

  • 3. Info sheet
  • 4. SPARQL reference

Log in to Cloud Server

3

slide-4
SLIDE 4

Workshop Files, Presentation PDF: (for later) https://github.com/phuse-org/LinkedDataWorkshop/CSS2019

4

slide-5
SLIDE 5

OUTLINE

  • 0. What is a Knowledge Graph?
  • 1. Create Your Study Graph
  • 2. Query Your Graph
  • 3. Extend to Other Graphs (Federated

Query)

  • 4. Ontology and Inference
  • 5. Merge Studies
  • 6. Discussion

5

slide-6
SLIDE 6

WHAT IS A KNOWLEDGE GRAPH?

An interconnected network of information consisting of meaningful relationships that are understandable by both people and computers. Built on Linked Data

6

slide-7
SLIDE 7

WHAT IS LINKED DATA?

Data that has meaningful (semantic) relationships Resource Description Framework (RDF)

7

slide-8
SLIDE 8

RDF TRIPLE DESCRIBING PERSON 1

8

slide-9
SLIDE 9

PERSON 1 NAME AND AGE

9

slide-10
SLIDE 10

10

slide-11
SLIDE 11

11

slide-12
SLIDE 12

"THINGS" NEED UNIQUE IDENTIFIERS

IRI: INTERNATIONALIZED RESOURCE IDENTIFIER

Unique Identier Uses HTTP://xx.xx.xx/xxxx

12

slide-13
SLIDE 13

WORKSHOP PREFIXES

Prexes shorten IRIs for readability

@prefix eg: <http://example.org/LDWorkshop#> . @prefix ncit: <http://ncicb.nci.nih.gov/xml/owl/EVS/Thesaurus.owl#> . @prefix schema: <http://schema.org/> .

13

slide-14
SLIDE 14

LITERALS

string

number

integer (INT)

date No links from a literal

14

slide-15
SLIDE 15

OUTLINE

  • 0. What is a Knowledge Graph?
  • 1. Create Your Study Graph
  • 2. Query Your Graph
  • 3. Extend to Other Graphs (Federated

Query)

  • 4. Ontology and Inference
  • 5. Merge Studies
  • 6. Discussion

15

slide-16
SLIDE 16

16

slide-17
SLIDE 17

INTRODUCTION TO THE GRAPH EDITOR

See your handout Reference: .../doc/Graph Editor Introduction.pdf

17

slide-18
SLIDE 18

EXERCISE

  • 1. Create Your Study Graph
  • 2. Query Your Graph

18

slide-19
SLIDE 19

OUTLINE

  • 0. What is a Knowledge Graph?
  • 1. Create Your Study Graph
  • 2. Query Your Graph
  • 3. Extend to Other Graphs (Federated

Query)

  • 4. Ontology and Inference
  • 5. Merge Studies
  • 6. Discussion

19

slide-20
SLIDE 20

20

slide-21
SLIDE 21

EXERCISE

  • 1. Link to ClinicalTrials.gov
  • 2. Link to DBPedia

21

slide-22
SLIDE 22

OUTLINE

  • 0. What is a Knowledge Graph?
  • 1. Create Your Study Graph
  • 2. Query Your Graph
  • 3. Extend to Other Graphs (Federated

Query)

  • 4. Ontology and Inference
  • 5. Merge Studies
  • 6. Discussion

22

slide-23
SLIDE 23

Ontology and Inference

Ontology

A vocabulary of things and how they relate to each other ...just more nodes and links Tools: Protege, TopBraid

Reasoner

An engine that applies the ontology to the graph and infers values and relationships not in your original data.

23

slide-24
SLIDE 24

THINK ABOUT THAT AGAIN:

Ontologies and Reasoning create values and relations not in your original data! StudyOntology.TTL

24 . 1

slide-25
SLIDE 25

A SUBSET OF THE STUDY ONTOLOGY FILE

24 . 2

slide-26
SLIDE 26

25

slide-27
SLIDE 27

26

slide-28
SLIDE 28

EXERCISE

  • 3. Ontology and Inference

27

slide-29
SLIDE 29

OUTLINE

  • 0. What is a Knowledge Graph?
  • 1. Create Your Study Graph
  • 2. Query Your Graph
  • 3. Extend to Other Graphs (Federated

Query)

  • 4. Ontology and Inference
  • 5. Merge Studies
  • 6. Discussion

28

slide-30
SLIDE 30

When IRIs are the same, merging is automagic!

29

slide-31
SLIDE 31

WITH RDF, MERGING BE LIKE:

What? How?

30 . 1

slide-32
SLIDE 32

30 . 2

slide-33
SLIDE 33

31

slide-34
SLIDE 34

EXERCISE

  • 4. Merge Studies

32

slide-35
SLIDE 35

ALLSTUDIES DATA POOL

BONUS! Visualize your Data Pool.

AllStudiesPoolVis.R

33

slide-36
SLIDE 36

OUTLINE

  • 0. What is a Knowledge Graph?
  • 1. Create Your Study Graph
  • 2. Query Your Graph
  • 3. Extend to Other Graphs (Federated

Query)

  • 4. Ontology and Inference
  • 5. Merge Studies
  • 6. Discussion...after nal words

34

slide-37
SLIDE 37

ACKNOWLEDGEMENTS

YOU! PhUSE Lauren - Prep Webinars and coordination PhUSE Admin Team Nolan Nichols (Genentech) Johannes Ulander (S-Cubed) Stardog Union Servers, graph database John Bresnahan - server cloning

35

slide-38
SLIDE 38

RESOURCES

Stardog Union

fetch.stardog.com/phuse/ www.stardog.com

36

slide-39
SLIDE 39

RESOURCES

Workshop materials, including the Graph Editor, SPARQL scripts, PDF of this presentation: And watch this space: https://github.com/phuse-org/LinkedDataWorkshop/CSS2019 https://github.com/phuse-

  • rg/LinkedDataEducation

37

slide-40
SLIDE 40

RESOURCES

Linked Data Introduction SPARQL in 11 Minutes https://www.youtube.com/watch?v=4x_xzT5eF5Q https://www.youtube.com/watch?v=FvGndkpa4K0

38

slide-41
SLIDE 41

PHUSE PROJECT BREAKOUT SESSION

"Going Translational With Linked Data" When: Monday 13:00 - 17:00pm Where: Fenton Room

Topics

Terminology mapping MedDRA as RDF Project Endpoint ...Other?

39

slide-42
SLIDE 42

DISCUSSION

40

 