Pistoia Alliance Debates: Ontologies mapping webinar 23rd Feb 2017

Ontologies Mapping for more effective data integration and

knowledge management

A Pistoia Alliance Debates Webinar23rd February 2017

Chaired by Ian Harrow

This webinar is being recorded

Poll Question 1:

What is your level of familiarity/involvement with Ontologies?

A. I lead Ontologies work in my organizationB. I contribute to Ontologies work in my

organizationC. I have a basic understanding of OntologiesD. I know very little about Ontologies

Pist

oia

Allia

nce

Chair and Expert Panel

Ontologies Mapping webinarFebruary 23, 2017

Yasmin Alam-Faruque, Scientific Data Specialist at Eagle Genomics Organisation, harmonisation and integration of datasets for the eaglecore knowledge

management platform Previously, biocurator at EMBL-EBI for the renal gene ontology annotation initiative

Simon Jupp, Ontology Project Lead at EMBL-EBI Developed a range of ontologies and ontology services including the Experimental Factor

Ontology and the Ontology Lookup Service Working with ontologies in the life sciences since 2003

Martin Romacker, Principal Scientist at Roche Innovation Center, Basel Data and Information Architect in Pharma Research and Early Development Informatics Focusing on the Knowledge Engineering (Terminologies/ Ontologies) and Scientific Data

Integration using Semantic Technologies

Ian Harrow, Project Manager at Pistoia Alliance (Chair) Consultant services in Bioinformatics and Text Mining Project Manager for the Ontologies Mapping project Previously, Senior Principal Scientist in Bioinformatics at Pfizer

Lee Harland, Founder and COO at SciBite SciBite is a growing company based in Cambridge UK specialising in Text Analytics and

Knowledge Management for life sciences Previously, CTO of the Open PHACTS project and head of the information engineering

group at Pfizer

4

Pist

oia

Allia

nce

5

Agenda

5February 23, 2017 Ontologies Mapping webinar

Panelist Question

Ian Harrow Welcome

Martin Romacker Why are ontologies important for Roche?

What has been achieved by the Ontologies Mapping project?

Yasmin Alam-Faruque What is the value of ontologies to Eagle Genomics?

How has being part of the OM project team helped?

Lee Harland How do ontologies power the SciBite platform?

Simon Jupp What ontology services are available at EMBL-EBI?

Ian Harrow What is the Ontologies Mapping project planning to do next?

Audience Q & A

Why are ontologies important for Roche?

What has been achieved by the project and it’s value to Roche?

Martin Romacker at Roche Innovation Center

Pist

oia

Allia

nce

Changing Perception of Corporate Data Assets

• Pharma Industry is behind other industries(eg Finance, Insurance, Automotive, Wholesale, Retailer – CDO/ CAO)

• Paradigm shift – from lab to data/knowledge?Data is business and business is data – acquisition of data not compounds (Google: data, algorithms, computer)

• Change only happens where the Pharma Industry is forced – why? CDISC, IDMP (heavily relying on ontologies and data standards)

• Pharma Industry accepts an incredible variety of data as input into knowledge-driven business processes (eg CROs, vendor data, cost avoidance)

• Pharma Industry spends huge budgets to generate knowledge - budgets are tight for integration, maintenance and quality assurance

February 23, 2017 Ontologies Mapping webinar 7

Pist

oia

Allia

nce

pREDi Terminology Service (RTS)

• RTS as domain master for terminology management– streamlining terminology management ensuring high data quality– semantic alignment between knowledge repositories lowering barriers

• Faster response to scientific queries (saving time)Less effort for data integration (cost avoidance)

• Support of external collaborations based on data standards (trend CROs)

• Support of well-founded decisions– business or scientific

• Semantic Engineering to define of research/business objects

• USP: Comprehensive semantic model to represent highly-scalable, universal and multi-purpose terminologies


Pist

oia

Allia

nce

pREDi Terminology Service (2015-2016)

MasterTerminos

21 (18)

Applications33 (23)

AppTerminos300 (220)

Concepts110k (95k)

Synonyms300k (265k)

3 3 2 825

pRED21

Pharma (PD/PT)

3

GPS6

Partnering1

Diagnostics2


Pist

oia

Allia

nce

Ontologies & Data Standards:Value Proposition

Source: https://www.crowdflower.com/the-data-behind-todays-data-scientists-an-infographic/https://whatsthebigdata.com/2016/05/01/data-scientists-spend-most-of-their-time-cleaning-data/

• Data-Science-Readiness (Time-to-Value)• Reduced Effort for Data Integration• Improved Data Quality (completeness, correctness, coherence)

Scientific Data Integration


Pist

oia

Allia

nce

Big Data - Semantics as a Key Enabler

Velocity

Volume Veracity

Variety

Value


Pist

oia

Allia

nce

Prime Time for Ontologies

• Executives consider data more and more as a corporate asset• Integration of Real World Data and Health Care Data • Translational and Reverse Translational Data Integration• Collaboration with Contract Research Organisation• But: Missing or competing standards in Research & Development

(eg MeSH, SNOMED, MedDRA, NCIt) Legacy systems using own terminologies/ontologies(terminologies/ontologies are ubiquitous but not managed as such)

• Urgent need for Ontologies Mapping

Roche funding of Pistoia Ontologies Mapping Project Phase 1 & 2Roche are committed to funding the proposed Phase 3


Pist

oia

Allia

nce

Project Phase 1&2: Timeline and Achievements

13

1) Ontologies domain selected

as “test case”

2Q 3Q2015

4Q

4) Evaluate & select existingOntologies Mapping tool(s) 5)

Requirements for an Ontologies Mapping service

6) Understand the demand for anOntologies Mapping service

1Q 2Q2016

4Q3Q

2) Guidelines for minimal standards & best practices

3) Requirements for Ontologies Mapping tool

Funded by GSK, Merck & Co, Novartis, Roche and BIOVIA 3DS

February 23, 2017 Ontologies Mapping webinar

Pist

oia

Allia

nce

Further Achievements

14

• Conformity with the FAIR principles– Findable and Accessible (public wiki)– Interoperable and Re-usable (aligned to OBO etc.)

• Endorsed by external groups:– Interoperable Services at ELIXIR, Molecular Archival Resources at

EMBL-EBI, Ontologies Mapping Project Community of Interest

• Promotion at conferences/workshops:-– EMBL-EBI March 2016, ISMB July 2016, ECCB September 2016,

Industry Semantic Forum at Roche September 2016, OM October 2016 and ISWC October 2016

• Ontology Alignment Evaluation Initiative– Sponsoring of a competition for the best ontologies matching

algorithm (International Workshop on Ontology Matching)


Pist

oia

Allia

nce

OM Project Community

15

Funders• BIOVIA 3DS• GSK• Merck & Co• Novartis• Roche

Pistoia Operations• Richard Holland• John Wise• Carmen Nitsche• Nick Lynch

Project team• Ian Harrow (Pistoia Project Manager)• Martin Romacker (Roche)• Andrea Splendiani (Novartis)• Stefan Negru (Merck & Co)• Peter Woollard (GSK)• Scott Markel (BIOVIA)• Martin Koch (Osthus)• Heiner Oberkampf (Osthus)• Yasmin Alam-Faruque (Eagle Genomics)• Erfan Younesi (Bayer)• Jabe Wilson (Elsevier)• James Malone (FactBio)

Community of Interest (>80 members)February 23, 2017 Ontologies Mapping webinar

Pist

oia

Allia

nce

Ontologies Mapping Project:Value to Roche

• Phase 1 & 2 Achievements are highly relevant:- Guidelines for selection of reference standards Analysis of available tools for ontologies mapping

(RFI: baseline, checklist for tools) Evaluation of ontologies mapping algorithms

(linkage to OM algorithm community)

• Phase 3 Ontologies Mapping Service proposal (later by Ian) Important for mapping requests (e.g. HPO to MeSH) Important application to semantic alignment Shared resources across scientific community


Pist

oia

Allia

nce

Conclusion

• Tremendous change: data are considered as an asset• Urgent need for lowering the barriers for data integration

and data sharing• Demystify knowledge acquisition process

Define as knowledge procurement process• Terminologies/ Ontologies and related Data Standards start

to play a key role but: getting them into business still requires tenacity but: tackle the issue from the value perspective

• Ontologies mapping is a core capability to work efficiently and successfully with corporate data assets This is why Roche consumes and funds the OM project


What is the value of ontologies to Eagle Genomics?

How has being part of the project team helped?

Yasmin Alam-Faruque at Eagle Genomics

Pist

oia

Allia

nce

Supporting the bridge between Data and InsightEagle Genomics provides software solutions bridging the gap between “big data” and “innovative biological insight”

Ontologies are essential - allow disparate data to be harmonised, federated and integrated for various high performance computational analyses (i.e. data processing, statistical analyses and data mining)

-> novel insights 19Ontologies Mapping webinarFebruary 23, 2017

Pist

oia

Allia

nce

20

Data curation• We also play an active role in

curating, organising and federating a variety of customer multi-omics datasets and associated metadata into a knowledge management platform (eaglecore).

• Curation of scientific data involves it’s collection, characterisation, cleaning, contextualization, categorisation and cataloguing, making it more visible and available for searching, sharing and further analyses.

• Hence, using ontologies during curation to semantically enrich and harmonise the datasets becomes essential for data integration and interoperability.


Pist

oia

Allia

nce

Data valuation

21

• Eagle Genomics pioneers measurement of data value (i.e. usefulness and relevance) in the context of specific scientific questions.

• Value modeling requires data harmonisation using ontologies. • We can measure the value of data before the use of

ontologies and after, according to quality metrics and value metrics.

Dataset Catalogue Dataset Catalogue (improved quality)

Quality metricsDescriptive statistics

Dataset Catalogue (improved value)

Improvement Improvement

Value metricsAHP, QFD

Ontologies


Pist

oia

Allia

nce

Data Governance

22

Governance

Validity

Consistency

ProcessesOrganisations

..standardsguidelines

Are we doing the right things?

Are we doing the things right?

ArchitectureData &

contextual models

…semantics

Goals

Governance by design

Measurement

• Emerging as an important activity for biopharma and healthcare industries

• Complex initiative: relates to the validity and consistency throughout the organisation

• Ensuring everyone refers to the same drug or disease across all organisational departments/sites (R&D -> clinical trials -> sale of drug to treat disease) is essential.

• can be initiated by use of ontologies/ controlled vocabularies to tag and link experiments/ datasets


Pist

oia

Allia

nce

How has being part of the project team helped?

23

Allowed visibility - played an active role throughout the project which has projected a serious and professional image among other organisational team members

Provided an overall increase in our expertise, understanding and capability within this important field

Credibility with potential customers/clients as we are heavily involved in this important community project along with other Pistoia member organisations

Opportunity to become aware of the evaluation and selection of the best potential academic/ commercial Ontology mapping tool/ service provider for future customer projects, ahead of the project starting – saving time.

Opportunity to be involved in the development of various documentation:• detailing the functional and non-functional requirements for an

Ontologies Mapping Tool• Ontology mapping guidelines (already comprehensively followed by

some ontologies)


Poll Question 2:

Where do you source mappings between ontologies?

A. Mostly external sources of mappingsB. Mostly internal curation of mappingsC. A mixture of both external and internal

sourcesD. I do not know

How do ontologies power the SciBite platform?

Lee Harland at SciBite

Pist

oia

Allia

nce

Ontologies In The SciBite Platform

26

Lee Harland | @SciBitely | www.scibite.com


Pist

oia

Allia

nce

27

80-90% of all potentially usable business information may originate in unstructured form

https://en.wikipedia.org/wiki/Unstructured_data






Pist

oia

Allia

nce

‘Semantics-as-a-Service’

28

Text ContentDocuments & Databases

Ontologies:Gene/Disease/Drug; Molecular; Chemical; Clinical; Adverse Event; Pharm Sci & Manufacturing; Business & Commercial; Regulatory; Geo-location; University/Company

Structured Data

+SciBite

API


Pist

oia

Allia

nce

Public Ontologies Are Vital

29

What They Are Great For• Providing a open, consistent, stable

identifier for a given “thing”• Developing community consensus as to

what that ”thing” is• Developing community consensus on what

all the things are • Powering Data Integration• Powering Scientific Analytics

Not Designed For Text Analytics/Mining


Pist

oia

Allia

nce

3 Key Issues

30

e.g. Human Phenotype Ontology (HPO) is a gold reference standard for phenotypes and many use cases start with “find all the phenotypes….”

But 6997 synonyms in current HPO over 11375 entities. Similar for many others as not their raison d'etre

1. Synonym Coverage

2. Coding Style 3. Ambiguity


Pist

oia

Allia

nce

Ontology Engineering

31

Raw Ontologies

Public SciBite

Customer

Expert Curation

Training, Testing, & Validation

TERMite

Feedback To Producers

Automated Learning, Enrichment & Curation


Pist

oia

Allia

nce

SciBite Ontology Enrichment*

SciBite

HPO

MeSH

HGNC

Original

* Actual search space many fold larger due to adaptive matching


Pist

oia

Allia

nce

Ontology-Driven Search

33February 23, 2017 Ontologies Mapping webinar

Pist

oia

Allia

nce

Ontology-Driven Search Everywhere!

34

SciBite

Researchers (End User)

Information Management

(Content Awareness)

Informatics(Text Mining)

System Developers (3rd Party Integration)

Pharma’s Internal Apps

Commercial Content/Software

Providers

Competitor IntelligenceLiterature Awareness, Trends & AlertingAlign 3rd Party Content

Disease & Phenotype Networks, PPIs, Pharmacovigilance, Drug-Target/Biomarker MiningPatent MiningMachine Learning/AIDocument Management, Enterprise & Local Search,Ontology-XREFSemantic Auto-completeRDF & Integration

Customer-Provider IntegrationOntology-driven applicationsSmarter Apps!


Pist

oia

Allia

nce

Summary

35

• Text (Databases & Documents) accounts for large amount of corporate “knowledge”

• Public & Internal Ontologies have great potential in structuring this text into minable data

• But these ontologies require significant processing, both human and automated in order to make them “fit for purpose”

• Combine this with a fast, flexible, simple API and you can address a vast array of different use cases in– Software Vendors & Systems Developers– Content Providers– Data Scientists & Text Miners


What ontology services are available at EMBL-EBI?

Simon Jupp at EMBL-EBI

Pist

oia

Allia

nce

Ontologies at EMBL-EBI

Applications

Disease BioAssays

Cell lines

Cell types

Small moleculesEvidence Taxonomy

Drugs

Adverse events

Information Gene function Plant anatomy

Mouse anatomy Phenotype

EVA Expression Atlas

GWAS catalog

Array Express

Biomedical ontologies


Pist

oia

Allia

nce

The challenge - thousands of data attributes…

• Use the data to focus our curation efforts– For experimental data we focus on species, cell types, tissue types, disease state,

phenotypes– Identify gaps in public ontologies

• Different requirements– High quality, manually curated resources e.g. GWAS catalog, OpenTargets – High throughput, automated curation e.g. archival resources like BioSamples


Pist

oia

Allia

nce

We build ontology aware applicationsSmarter searching Data analysis

Data integration

Data visualisation


Pist

oia

Allia

nce

Common questions

• How can I access ontologies?• How do I map data to ontologies? • What about data that doesn’t map?• How can I translate from one ontology to

another?• How can I extend an ontology?• How do I build “ontology aware”

applications? • How should I publish my data?


Pist

oia

Allia

nce

We are building a Ontology Toolkit

Search/Visualise ontologies

Annotate data

Ontology mappings

Create new ontology content

Webulous

Ontology Lookup Service

OxO

Zooma


Pist

oia

Allia

nce

Ontology Lookup Service

• Ontology search engine • Ontology term history tracking• Ontology visualisation • Powerful RESTful API

Repository of over 160 pre-selected biomedical ontologies (4.5 million terms)

http://www.ebi.ac.uk/ols

• Provides unified mechanism to access multiple ontologies

• Large community of users, 10s of millions of hits per month




Pist

oia

Allia

nce

Zooma

• Optimal mappings based on data we have seen previously• Favours precision over recall for use in automated pipelines• Currently contains over 92,000 curated annotations from 7 resources

– ClinVar, Cellular Phenotype Database, ExpressionAtlas, UniProt, GWAS, EBiSC, OpenTargets

– Used to improve and share their mappings across resources

Repository of curated ontology mappingshttp://www.ebi.ac.uk/spot/zooma


http://www.ebi.ac.uk/spot/zooma

http://www.ebi.ac.uk/spot/zooma

Pist

oia

Allia

nce

New for 2017 – Ontology Xrefs• A lot curator effort in building ontology

cross-references• Cross-references are a powerful tool for

integrating data

Data source 1 Data source 2

Human Phenotype Ontology

SNOMED-CTMappings


Pist

oia

Allia

nce

Ontology Mapping Service (OxO)• New curation platform for community built mappings • Seeded with mappings from OLS and other sources (UMLS,

SNOMED)• Normalised CURIE prefixes using identifiers.org

– SNOMED-CT: / SNOMEDCT: / SNOMED: / SNOMEDCT_• Provides a gold standard to support predictive mapping

algorithms http://www.ebi.ac.uk/spot/oxo * * Going live March 2017


http://www.ebi.ac.uk/spot/oxo

http://www.ebi.ac.uk/spot/oxo

Pist

oia

Allia

nce

Webulous – creating new ontology content • Spreadsheet templates for adding new

ontology content– Ontology “aware” for in sheet validation– Generic ontology building technology

• Works with Google sheets

Webulous server

Exposes list of ontology design templates

Populated templates convertedOWL

Webulous exports newly generated ontology

http://www.ebi.ac.uk/efo/webulous




Pist

oia

Allia

nce

Putting it all together

• How can I access ontologies?• How do I map data to ontologies? • What about data that doesn’t map?• How can I translate from one ontology to

another?• How can I extend an ontology?• How do I build “ontology aware”

applications? • How do I publish my annotations?


Pist

oia

Allia

nce

Ontology team

Helen ParkinsonTony Burdett

Sira SarntivijaiOlga Vrousgou Thomas Liener


What is the project planning to do next?

Ian Harrow at Pistoia Alliance

Pist

oia

Allia

nce

Why do we need Ontology Mapping?

50

Data domain Example: Disease and Phenotype

Ontology 1 Ontology 2 Ontology 3

Mapping 1-2 Mapping 2-3

Mapping Tools and Services Higher scalability at reduced cost of maintenance

A better engineering solution for application ontologies

Expandable coverage

+ More…


Pist

oia

Allia

nce

Proposal for an Ontology Mapping Service

OLSOntology Lookup

Service

OXOOntology Cross

References (Mappings)

ZOOMAMapping Tool

Database of curated mappings sourced

from public datasets

162 Ontologies

Mapping free text annotations to ontology

terms based on a curated repository of annotation

knowledge

Pistoia Alliance Prototype Ontologies Mapping Service (OMS):-Develop an OMS to build on the existing Ontology Services at EMBL-EBI

Evaluate value and quality of selected mappings in Disease & Phenotype domain


Pist

oia

Allia

nce

Proposed Deliverables and Timeline

1) Start the prototype service to run for 6 months

4Q

3) Complete prototype service and report performance metrics

Requirements for an Ontologies Mapping service as a standard

2QPhase 3: 2017

3Q

2) 3 month review of service performance metrics

Phase 2: 2016

Promote and publicise prototype service

1QPh3: Preparatory

February 23, 2017 52Ontologies Mapping webinar

Pist

oia

Allia

nce

Benefits and Support for Phase 3

53

Expected Benefits• Evaluate value and quality of mappings between public

disease & phenotype ontologies selected by funders• Evaluate value and quality of public to internal mappings

selected by funders• Build on the database for public ontology mappings• Extendible to any ontology hosted at EMBL-EBI

Call for Support• Roche have committed funds and interest is growing• Please contact [email protected] about

support for the projectNow is a great time to join us!!!


Audience Q&APlease use the Question function in GoToWebinar

Join the Deep LearningHackathon March 25-26 London

Help us show how Deep Learning can impact Life Sciences and Healthcare

Why attend?• Create something that could make a life changing difference to human health.• Job opportunities - meet and find out more about working with the pharma /

healthcare industry. We will bring the companies to you. Your team mate at the event could be your future colleague!

• Win prizes and gain recognition - you can receive your prize at our conference in front of over 100 senior industry experts from R & D and IT.

• We hope you will make new connections from new areas and disciplines, perhaps even see new career directions you never thought possible.

• It’s fun!!!

http://www.pistoiaalliance.org/eventdetails/pistoia-alliance-hackathon







[email protected] @pistoiaalliance www.pistoiaalliance.org

Thank you all, you have been a great audience!