My presentation at this years lab of the future event at the genome campus in November 2019. Updated from the previous one to condense into a 20 minute slot. Talks about the role of ontologies in FAIR data environments and how #cleandata helps AI & deep learning processes. But also how machine learning can help us build more intelligent systems to deal with scientific content.

1. Are Ontologies Relevant In A Machine
Learning World?
Dr. Lee Harland
Chief Scientific Officer, SciBite Limited
Lab Of The Future October 2019
https://scibite.com | https://www.slideshare.net/scibitely/

2. The Promised Data Lake….

3. The Real Data Lake….

4. ….Therefore, we are
confident that the true
cost of not having FAIR
research data is much
higher than the estimated
€10.2bn per year...

5. What it feels like…

6. Computers Don’t Understand Text….

7. Ontologies: The Bedrock Of Good Data Stewardship
“Things Not Strings”
Machine
Understandable
Human Validated
(Consensus/Authority)
Stable Identifiers
Define A Domain
= “Semantic”

8. Transform Search, LIMS, ELN, Regulatory & more:
Synonym Independent Search (Viagra=Sildenafil)
Ontology Search (”Find projects on Kinases”)….
Connection Search (“Drugs that cause inflammation”)
Beautiful Data – build a data integration legacy
Empower Machine Learning
PAXIP1 Potentiates the
Combination of WEE1 …..
SciBite - An Infrastructure Company For This…

9. AZ Ontology-Driven Search At Massive Scale
http://sinequa/com
https://www.sinequa.com/live-
webcast-unlock-wealth-rd-
data/
Ack: Nick Brown, AZ

10. F.A.I.R @ BMS with Smart Semantic Forms
• Public Bioassay
Ontology
• Augmented with
BMS-specific
terms
• Users can suggest
new assays etc.
• Reactive, semantic
form fields
CREDIT: BMS AIMS Team

11. Major examples of ontology-based clean-data AI

12. The good news is
I have discovered
inefficiencies…
…The bad news is
that you are one
of them.
https://timoelliott.com/blog/cartoons/artificial-intelligence-cartoons
AI Is Here

13. Examples: Named Entity Recognition/Ontology Enrichment & Question Answering

14. Expanding models in virtuous circles
Often made as
softer, open-textured
cheeses, the addition
of blue-mould causes
veins to form. Classic
examples are Stilton,
Roquefort &
Gorgonzola. The
British way of making
cheese, where
moisture is driven
out by acidifying milk
gives Cheddar,
Lancashire & red
Leicester.
Often made as
softer, open-textured
cheeses, the addition
of blue-mould causes
veins to form. Classic
examples are Stilton,
Roquefort &
Gorgonzola. The
British way of making
cheese, where
moisture is driven
out by acidifying milk
gives Cheddar,
Lancashire & red
Leicester.
Scientific
Corpus
Identify Known
Ontology
Concepts
Train model
Run
Model
Manual
Evaluation
'false' positives
Add true
positives to
vocabs TERMiteTERMite
New model
Often made as softer,
open-textured cheeses,
the addition of blue-
mould causes veins to
form. Classic examples
are Stilton, Roquefort &
Gorgonzola. The British
way of making cheese,
where moisture is driven
out by acidifying milk
gives Cheddar,
Lancashire & red
Leicester.

15. A Helping Hand For Ontology Building

16. Natural Language Interfaces
Machine
Learning
Toolkit

17. Natural Query as an API

18. • Large numbers of disorganised documents (i.e. CRO documents)
• Need to align these to internal taxonomy of categories (e.g. M4 hierarchy
from FDA)
• Also need to identify key pieces of metadata (e.g. what is the study
compound? Title? Assay… etc )
• Manual process, incredibly time consuming
Pfizer Acquisition Challenge
CREDIT: Pfizer Computational Sciences
http://www.bio-
itworld.com/2018/08/08/a-
new-machine-learning-
approach-to-document-
classification-a-pfizer/scibite-
collaboration.aspx

19. LifeArc Horizon Scanning

20. © 2018 SciBite Limited
Ontologies, FAIR & Machine Learning form a
powerful model for data stewardship

21. Acknowledgements
AZ: R&D Search Team, Integrative
Informatics Team, Sinequa, Nick
Brown
Pfizer: Computational Sciences
CoE, Steve Penn
BMS: Aims Team
LifeArc Team
Many colleagues at SciBite
involved in this work

22. Thanks!
Slides @ https://www.slideshare.net/scibitely
Visit Us At http://scibite.com