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Pistoia Alliance Debates: Ontologies mapping webinar 23rd Feb 2017
1. Ontologies Mapping for more
effective data integration and
knowledge management
A Pistoia Alliance Debates Webinar
23rd February 2017
Chaired by Ian Harrow
3. Poll Question 1:
What is your level of familiarity/involvement
with Ontologies?
A. I lead Ontologies work in my organization
B. I contribute to Ontologies work in my
organization
C. I have a basic understanding of Ontologies
D. I know very little about Ontologies
4. PistoiaAlliance
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
5. PistoiaAlliance
Agenda
55February 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
6. 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
7. PistoiaAlliance
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
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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
February 23, 2017 Ontologies Mapping webinar 8
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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 DataIntegration
February 23, 2017 Ontologies Mapping webinar 10
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Big Data - Semantics as a Key Enabler
Velocity
Volume Veracity
Variety
Value
February 23, 2017 Ontologies Mapping webinar 11
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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 & 2
Roche are committed to funding the proposed Phase 3
February 23, 2017 Ontologies Mapping webinar 12
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Project Phase 1&2: Timeline and
Achievements
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1) Ontologies
domain selected
as “test case”
2Q 3Q
2015
4Q
4) Evaluate & select existing
Ontologies Mapping tool(s) 5)
Requirements for an
Ontologies Mapping service
6) Understand the demand for an
Ontologies Mapping service
1Q 2Q
2016
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
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Further Achievements
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• 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)
February 23, 2017 Ontologies Mapping webinar
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OM Project Community
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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
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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
February 23, 2017 Ontologies Mapping webinar 16
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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
February 23, 2017 Ontologies Mapping webinar 17
18. What is the value of ontologies to Eagle
Genomics?
How has being part of the project
team helped?
Yasmin Alam-Faruque at Eagle Genomics
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Supporting the bridge between Data and Insight
Eagle 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
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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.
Ontologies Mapping webinarFebruary 23, 2017
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Data valuation
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• 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 metrics
Descriptive statistics
Dataset Catalogue
(improved value)
Improvement Improvement
Value metrics
AHP, QFD
Ontologies
Ontologies Mapping webinarFebruary 23, 2017
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Data Governance
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Governance
Validity
Consistency
Processes
Organisations
..
standards
guidelines
Are we doing
the right things?
Are we doing
the things right?
Architecture
Data &
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
Ontologies Mapping webinarFebruary 23, 2017
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How has being part of the project team helped?
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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)
Ontologies Mapping webinarFebruary 23, 2017
24. Poll Question 2:
Where do you source mappings between
ontologies?
A. Mostly external sources of mappings
B. Mostly internal curation of mappings
C. A mixture of both external and internal
sources
D. I do not know
25. How do ontologies power the SciBite
platform?
Lee Harland at SciBite
26. PistoiaAlliance
Ontologies In The SciBite Platform
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Lee Harland | @SciBitely | www.scibite.com
February 23, 2017 Ontologies Mapping webinar
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80-90% of all potentially usable
business information may
originate in unstructured form
https://en.wikipedia.org/wiki/Unstructured_data
February 23, 2017 Ontologies Mapping webinar
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‘Semantics-as-a-Service’
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Text Content
Documents & Databases
Ontologies:
Gene/Disease/Drug; Molecular;
Chemical; Clinical; Adverse Event;
Pharm Sci & Manufacturing; Business
& Commercial; Regulatory; Geo-
location; University/Company
Structured Data
+
SciBite
API
February 23, 2017 Ontologies Mapping webinar
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Public Ontologies Are Vital
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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
February 23, 2017 Ontologies Mapping webinar
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3 Key Issues
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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
February 23, 2017 Ontologies Mapping webinar
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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
February 23, 2017 Ontologies Mapping webinar
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Ontologies at EMBL-EBI
Applications
Disease BioAssays
Cell lines
Cell types
Small molecules
Evidence
Taxonomy
Drugs
Adverse events
InformationGene function
Plant anatomy
Mouse anatomy
Phenotype
EVA Expression Atlas
GWAS catalog
Array Express
Biomedical ontologies
February 23, 2017 Ontologies Mapping webinar 37
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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
February 23, 2017 Ontologies Mapping webinar 38
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We build ontology aware applications
Smarter searching Data analysis
Data integration
Data visualisation
February 23, 2017 Ontologies Mapping webinar 39
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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?
February 23, 2017 Ontologies Mapping webinar 40
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We are building a Ontology Toolkit
Search/Visualise ontologies
Annotate data
Ontology mappings
Create new ontology content
Webulous
Ontology Lookup Service
OxO
Zooma
February 23, 2017 Ontologies Mapping webinar 41
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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
February 23, 2017 Ontologies Mapping webinar 42
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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 mappings
http://www.ebi.ac.uk/spot/zooma
February 23, 2017 Ontologies Mapping webinar 43
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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
February 23, 2017 Ontologies Mapping webinar 44
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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
February 23, 2017 Ontologies Mapping webinar 45
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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 converted
OWL
Webulous exports newly
generated ontology
http://www.ebi.ac.uk/efo/webulous
February 23, 2017 Ontologies Mapping webinar 46
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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?
February 23, 2017 Ontologies Mapping webinar 47
49. What is the project planning
to do next?
Ian Harrow at Pistoia Alliance
50. PistoiaAlliance
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…
February 23, 2017 Ontologies Mapping webinar
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Proposal for an Ontology Mapping Service
OLS
Ontology Lookup
Service
OXO
Ontology Cross
References
(Mappings)
ZOOMA
Mapping 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
February 23, 2017 Ontologies Mapping webinar 51
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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
2Q
Phase 3: 2017
3Q
2) 3 month review of service
performance metrics
Phase 2: 2016
Promote and publicise
prototype service
1Q
Ph3: Preparatory
February 23, 2017 52Ontologies Mapping webinar
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Benefits and Support for Phase 3
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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 ian.harrow@pistoiaalliance.org about
support for the project
Now is a great time to join us!!!
February 23, 2017 Ontologies Mapping webinar
55. Join the Deep Learning
Hackathon 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
Warm welcome to all of you. My name is Ian Harrow and I am working for the Pistoia Alliance. Thank you for joining us on this Webinar titled…
Please notice that this Webinar will be recorded and made available to all of you for later reference.
Before I introduce the panel of speakers we have today, I would like to ask you with this poll. What is your level of familiarity/ Involvement with Ontologies. This will help the panellists to better understand the audience. A, B,C, D. I will give you another 30 seconds, than Nick Lynch who provides all the support for this Webinar will give us the results. Some interpretation. An interesting mix in the results.
Eagle provides software solutions that bridge between “big data” and “innovative biological insight”.
Ontologies are essential. Why? Because they allow disparate data from a variety of sources to be harmonised, federated and integrated into a resource from which various high performance computational analysis such as data processing, statistical analyses and data mining can be carried out towards novel biological insights.
Curation of scientific data involves the collection, characterisation, cleaning, contextualization, categorisation and cataloguing, …
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.
AHP (analytic hierarchy process) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology.
QFD (Quality Function Deployment) is a structured approach to defining customer needs or requirements and translating them into specific plans to produce products to meet those needs. The “voice of the customer” is the term to describe these stated and unstated customer needs or requirements.
Data Governance is emerging as an important activity within the biopharma and healthcare industries. This is a complex initiative which relates to the validity (such as are we doing the right things) and consistency (are we doing the things right) throughout the organisation. It goes towards 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.
Should be by design not as a “tick box”
Governance can be initiated by use of ontologies/ controlled vocabularies to tag and link experiments/ datasets throughout different departments .
So being a part of the project team has
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
Allowed Credibility with potential customers/clients to say that we are heavily involved in this important community project along with other Pistoia member organisations
It has given us an 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, hence saving precious time.
And also given us an 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)
Here is our second poll for the audience…
EBI makes extensive use of ontologies spanning many domains
Multiple applications that use these ontologies to describe data
The metadata is a mess, we focus and prioritise our curation. Focus on species, cell types, tissues type, disease state, phenotype
Range of applications drivenby ontologies, smarter searching, analysis, data integration, visualisation of data
Zooma and OLS first port of call for mappings
Zooma allows curation for unmapped data, new terms can be minted with webulous
Might find mapping but need cross-refs – then use OxO
Build applciation, extarct applciation ontologies, build search indexes with biosolr
Publish dta and mapping – EBI RDF platform state of the art in semantic publishing
Used by biosamples via biosolr
Refer back to BioSamples, building pipelines
Can’t have DO and HPO, but if I’ve got mappings I’m ok
GWAS need to exports as Mesh instead of OWL
The come from multiple sources
Directly asserted as term annotation inside ontologies
Dedicated mapping resources (UMLS, SNOMED, ICD)
Manually curated mappings (in spreadsheets)
Automated tools for predicting mappings
Identifier formats can vary
URIs, CURIEs (compact URIs e.g. GO:0001234)
Prefixes vary for CURIEs (MSH and MeSH both used for MeSH)
Provenance models and semantics lacking
Hard to know how existing mappings were derived (manual vs automated)
What mapping means (sameAs, cross species, broader)
Zooma and OLS first port of call for mappings
Zooma allows curation for unmapped data, new terms can be minted with webulous
Might find mapping but need cross-refs – then use OxO
Build application, extract application ontologies, build search indexes with biosolr
Publish data and mapping – EBI RDF platform state of the art in semantic publishing
Thanks you Martin and Sergio for these excellent examples how cross pharma collaboration can deliver real value for the community.
A reminder to type your questions into Goto Webinar
Recording of this Webinar will be made available on the Pistoia website. Thank you