Pushing back, standards and standard organizations in a Semantic Web enabled world

“Pushing Back”
Standards and
Standard Organizations
in a Semantic Web Enabled World
Kerstin Forsberg
Informatics Scientist
AstraZeneca
Mölndal, Sweden

Image: Flickr bitpuddle
(Twitter @eric_d_hancock)

Purpose
Encourage standard organisations to
“Use Standards for Standards”

Agenda
• Standards for Data and Semantics
• Exemplas of Standard Organizations
now looking into using Semantic Web
• Provenance/Justification for Mappings

2

Kerstin Forsberg | SWAT4LS, Dec 10th 2013

AZIT | R&D Information

Kerstin Forsberg (@kerfors)
“Information architect, semantic web and linked data enthusiast
caring about clinical trial data.”
• “Volvo Web Wave Project” 1995-1997
W3C conferences 1996 & 1999, Dublin Core, RDF
• “Extensible use of RDF in a business context”
paper presented at the W3C WWW9 conference, 2000,
Amsterdam

• “Advancing translational research with the Semantic Web”
joint W3C HCLS paper in BMC Bioinformatics, 2007
• “Linked data, an opportunity to mitigate complexity in
pharmaceutical research and development”
Summary of experiences from LarKC and W3C HCLS
2011 together with my colleague Bosse Andersson

3



About AstraZeneca

• Alongside our own R&D, we partner
with others, combining skills and
resources to broaden the potential
for successful innovation.
• We believe that only by working together with others
who have a part of play in improving healthcare can real
progress be made.
• We work closely with others in the healthcare
community, including physicians and those who pay for
healthcare, to understand their challenges and how we
can combine skills and resources to achieve a
common goal: improved health.

4



AstraZeneca’s view on “Semantics”
Enabling the hyperconnected enterprise
“We need to build a linked
data architecture enabling us
to ask questions and solve
business problems across a
heterogeneous information
landscape extending beyond
the traditional boundaries of
the enterprise.”

semanticsconnectsusall

5



Standards for Data and Semantics
Different types of standards
• Entity-based Ontologies
• Concept-based Terminologies/Code systems

• Code lists/Value sets/Term sets
• Data exchange (Tabulated data)

• Information Models
6



Standards for Data and Semantics
Examples


7



“Pushing back” – Use standards for standards
1. NCI (National Cancer Institute)Thesaurus


8



AZ Vocabulary Management team shared this with NCI EVS

• The NCI Thesaurus is an extensive medical
vocabulary published by the US National Institutes
of Health: http://ncit.nci.nih.gov/

• It is made available in several downloadable
formats: http://evs.nci.nih.gov/ftp1/NCI_Thesaurus
• In order for use to use the thesaurus in our system,
we need to convert it to RDF, following the SKOS
standard: http://www.w3.org/2004/02/skos/

Jim Morris, Informatics Scientist
AstraZeneca R&D Wilmington, USA

9



2. MedDRA (Medical Dictionary for Regulatory Activities)


10



AZ Vocabulary Management team shared this with MedDRA MSSO
A very simple SKOS-rendering
of MedDRA
• term  skos:Concept
• hierarchy level 
skos:ConceptScheme
• SMQ  skos:Collection
Approach should be augmented with
VoID representation of MedDRA
versions and term properties
distinguishing active from inactive
terms.
Skos:Collection is likely not sufficient
to support SMQ versioning nor
context of terms in an SMQ (e.g.
weight)

11


Courtland Yockey, Informatics Scientist
AstraZeneca R&D Wilmington, USA


3. CDISC (Clinical Data Interchange Consortium)
• Concept-based Terminologies / Code systems


12



Standards for Data Exchange
Clinical Trial Data standardized “containers”

Patient level
Submission standards SDTM
“designed so [FDA] reviewers with
no tools other than perhaps the SAS
Viewer would be able to open a
dataset and browse it easily”.

13


Trial Summary level


Documentation of standardized “containers”

Human readable
documentation in 200+
pages PDF:s, Excel:s (and
some in XML).

14



Data in standardized “containers”

CDISC SDTM
Implementation
Guideline (IG)

Humans can connect data to data
standards.

15



Documentation of Standard fragments
CDISC SDTM
Model

1

2

CDISC SDTM
Implementation
Guideline (IG)

3 CDISC SDTM

Humans can connect data to data
standards and connect the
different standard fragments to
each other.
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Controlled Terminiolgy


Linked Clinical Data Standards
• CDISC2RDF started as a cross-pharma precompetitive project with AstraZeneca, Roche,
W3C et al. to show case Semantic Web
standards and Linked Data principles.
• Become part of the Semantic Technology
project, a FDA/PhUSE working group for
Emerging Technologies, with 30+ repr.
from FDA, CDISC, Pharma:s, CRO:s
and software vendors.
• First phase: Representing existing
“container” standards (SDTM, CDASH,
SEND, ADaM) in RDF.

17




Human readable documentation in
PDF:s, Excel:s (and some in XML)

Machine processable linked
data structured as RDF triples
(160.000+ )

Serializations of RDF triples
in Turtle and XML …
https://github.com/phuse-org/rdf.cdisc.org

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Meta Model Schema (mms)
Based on the core ISO11179 model
(metadata for data elements and
a few CDISC specific classes and properties)

Import files
Human readable documentation in Annotated Excel files from CDISC with
classes and properties from the Schemas
PDF:s, Excel:s (and some in XML)
ready to transform to RDF triples
using a off-the-shelf tool
(TopQuadrant Composer)

Machine processable linked
data structured as RDF triples
(160.000+ )

Serializations of RDF triples
in Turtle and XML …
https://github.com/phuse-org/rdf.cdisc.org

19



Annotating existing standards
Meta Model Schema (mms)
Based on the core ISO11179 model
(metadata for data elements and
a few CDISC specific classes and properties)

This turned out to be a good
way to communicate with
people knowledgeable in
CDISC but new to RDF
schemas to understand the
process of “triplification”.

20

Import files
Annotated Excel files from CDISC with
classes and properties from the Schemas
ready to transform to RDF triples
using a off-the-shelf tool
(TopQuadrant Composer)



CDISC and NCIT
Value sets is an issue

• Concept-based Terminologies / Code systems

mms:PermissibleValue
mms:ValueDomain


mms:Data Element
mms:Dataset
mms:DataCollectionForm

21



Cross standard review and mappings

Data Elements [SDTM, ADaM, CDASH] ”haveSame” Value Domain (CT)
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Provenance/Justification for Mappings
Example from EU project SALUS for Post Market Safety Studies

The example show the hierarchy of cardiac disorders in both the MedDRA and
SNOMED-CT concept schemes, expressed using the skos:broader property. Mappings between
similar concepts in both concept schemes are stated using the skos:exactMatch property.
From: SALUS Harmonized Ontology for Post Market Safety Studies
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Example from EU project SALUS for Post Market Safety Studies

MedDRA:10028596

skos:exactMatch

SNOMEDCT:22298006

The example show the hierarchy of cardiac disorders in both the MedDRA and
SNOMED-CT concept schemes, expressed using the skos:broader property. Mappings between
similar concepts in both concept schemes are stated using the skos:exactMatch property.
From: SALUS Harmonized Ontology for Post Market Safety Studies
24



Alternative: Mappings as LinkSets

The Dataset Descriptions for the Open
Pharmacological Space is a specification for
the metadata to described datasets, and the
LinkSets that relate them.

25



Alternative: Mappings as Nanopublications

MedDRA:10028596

26


skos:exactMatch

SNOMEDCT:22298006


Summary
Encourage standard organisations to
“Use Standards for Standards”
for sustainability and trustability.
Think if …

semanticsconnectsusall

27



Acknowledgements
AZ’s Semantic Web Community of Practice members:
Tom Plasterer (lead), Jim Morris, Courtland Yockey, Sorana
Popa, Rob Hernandez, Mike Westaway, Rajan Desai, Simon
Rakov, Dana Crowley, Ian Dix, Johan Törnqvist
Collaborators and Advisors:
• Charlie Mead – IO Informatics
• Dean Allemang – Working Ontologist
• Frederik Malfait – IMOS consulting / Roche
• Phil Ashworth – TopQuadrant

Thank you! Kerstin.l.forsberg@astrazeneca.com
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Pushing back, standards and standard organizations in a Semantic Web enabled world

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