Interoperability of electronic healthcare information remains an enormous challenge in spite of 100+ available healthcare information standards. This webinar explains the Yosemite Project, whose mission is to achieve semantic interoperability of all structured healthcare information through RDF as a common semantic foundation. It explains the rationale and technical strategy of the Yosemite Project, and describes how RDF and related standards address a two-pronged strategy for semantic interoperability: facilitating collaborative standards convergence whenever possible, and crowd-sourced data translations when necessary.
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Interoperability
1. The Yosemite Project
A Roadmap for
Healthcare Information Interoperability
David Booth, Hawaii Resource Group
Conor Dowling, Caregraf
Michel Dumontier, Stanford University
Josh Mandel, Harvard University
Claude Nanjo, Cognitive Medical Systems
Rafael Richards, Veterans Affairs
Semantic Technology and Business Conference
21-Aug-2014
These slides: http://dbooth.org/2014/yosemite/
http://YosemiteProject.org/
2. 2
Outline
• Mission and strategy
• Semantic interoperability
– Standards
– Translations
• Roadmap for interoperability
• Cost
3. 3
MISSION:
Semantic interoperability
of
all structured healthcare information
4. 4
MISSION:
Semantic interoperability
of
all structured healthcare information
6. 6
Universal information representation
• Q: What does instance data X mean?
• A: Determine its RDF information content
Instance data RDF
<Observation
xmlns="http://hl7.org/fhir">
<system value="http://loinc.org"/>
<code value="37270"/>
<display value="BPsystolic, sitting"/>
<value value="120"/>
<units value="mmHg"/>
</Observation>
7. 7
Why RDF?
• See http://dbooth.org/2014/why-rdf/
"Captures information
content, not syntax"
"Multi-schema friendly"
"Supports inference"
"Good for model
transformation"
"Allows diverse data
to be connected and
harmonized"
"Allows data models and
vocabularies to evolve"
8. 8
Semantic interoperability:
The ability of computer systems
to exchange data
with unambiguous, shared meaning.
– Wikipedia
9. 9
Two ways to achieve interoperability
• Standards:
– Make everyone speak the same language
– I.e., same data models and vocabularies
• Translations:
– Translate between languages
– I.e., translate between data models and
vocabularies
22. 22
How Standards Proliferate
http://xkcd.com/927/
Used by permission
23. 23
Each standard is an island
• Each has its "sweet spot" of use
• Lots of duplication
24. 24
RDF and OWL enable semantic bridges
between standards
• Goal: a cohesive mesh of standards that act
as a single comprehensive standard
25. 25
Needed: Collaborative Standards Hub
SNOMED-CT
FHIR
LOINC
• A cross between BioPortal, GitHub, WikiData, Web Protege,
CIMI repository, HL7 model forge
– Next generation BioPortal?
ICD-11
HL7 v2.5
26. 26
Collaborative Standards Hub
• Repository of healthcare
information standards
• Supports standards
groups and implementers
• Holds RDF/OWL definitions of data
models, vocabularies and terms
• Encourages:
– Semantic linkage
– Standards convergence
SNOMED-CT
FHIR
ICD-11
LOINC
HL7 v2.5
27. 27
SNOMED-CT
FHIR
ICD-11
LOINC
HL7 v2.5
Collaborative Standards Hub
• Suggests related concepts
• Checks and notifies of
inconsistencies – within
and across standards
• Can be accessed by browser or RESTful
API
28. 28
Collaborative Standards Hub
• Can scrape or reference
definitions held elsewhere
• Provides metrics:
SNOMED-CT
FHIR
ICD-11
– Objective (e.g., size, number of views, linkage
degree)
– Subjective (ratings)
• Uses RDF and OWL under the hood
– Users should not need to know RDF or OWL
LOINC
HL7 v2.5
31. 31
How RDF helps translation
• RDF supports inference
– Can be used for translation
• RDF acts as a universal information
representation
• Enables data model and vocabulary
translations to be shared
32. 32
Translating patient data
2.
Translate
from
RDF
1. Lift
to
RDF
• Steps 1 & 3 map between source/target syntax and RDF
• Step 2 translates instance data between data models
and vocabularies (RDF-to-RDF)
– A/k/a semantic alignment, model alignment
Crowd-Sourced
Translation
Rules Hub
Rules
Source Target
v2.5
3. Drop
33. Crowd-Sourced
Translation
Rules Hub
33
How should this translation be done?
2.
Translate
Rules
Source Target
3. Drop
from
RDF
1. Lift
to
RDF
v2.5
• Translation is hard!
• Many different models and vocabularies
• Currently done in proprietary, black-box integration engines
34. 34
Translation strategies
Hub-and-Spoke Point-to-Point
• Point-to-point is easier/faster for each translation
• Hub-and-spoke requires fewer translations: O(n) instead of O(n^2)
• Hub-and-spoke requires a common data model
• Both strategies can be used!
35. 35
Which common data model?
Hub-and-Spoke
• Standardization may choose a common data model:
– Moving target
– Must be able to represent (but not require) the finest granularity needed by any use
case
• Different use cases may use other data models, mapped to/from the
common data model
36. Crowd-Sourced
Translation
Rules Hub
36
Where are these translation rules?
2.
Translate
Rules
Source Target
3. Drop
from
RDF
1. Lift
to
RDF
v2.5
• By manipulating RDF data, rules can be
mixed, matched and shared
37. 37
Needed:
Crowd-Sourced Translation Rules Hub
● Based on GitHub, WikiData, BioPortal, Web Protege or other
● Hosts translation rules
● Agnostic about "rules" language:
● Any executable language that translates RDF-to-RDF (or
between RDF and source/target syntax)
38. 38
Translation rules metadata
• Source and target language / class
• Rules language
– E.g. SPARQL/SPIN, N3, JenaRules, Java, Shell, etc.
• Dependencies
• Test data / validation
• License – or require free and open source license
• Maintainer
• Usage metrics/ratings
– Objective: Number of downloads, Author, Date, etc.
– Subjective: Who/how many like it, reviews, etc.
39. 39
Patient data privacy
2.
Translate
3. Drop
from
RDF
1. Lift
to
RDF
• Download translation rules as needed – plug-and-play
• Run rules locally
– Patient data is not sent to translations hub
Crowd-Sourced
Translation
Rules Hub
Rules
Source Target
v2.5
41. 41
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
42. 42
Semantic
Interoperability
Use RDF as a common semantic
4. Crowd-Sourced
Translation
Rules
Roadmap - 1
6. Collaborative
Standards
Convergence
2. RDF
Mappings
representation
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
43. 43
Semantic
For common healthcare information
representations*, define an RDF
mapping to/from each format, data
model and vocabulary – "lift" and
"drop".
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap - 2
6. Collaborative
Standards
Convergence
2. RDF
Mappings
*Both standard and proprietary
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
44. 44
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap - 3
Define translation rules 6. Collaborative
for
instance data that Standards
is expressed in
RDF representations
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
45. 45
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap - 4
Create a hub for crowd-sourcing
translation rules
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
46. 46
Semantic
Interoperability
Create RDF / OWL definitions of
the data models and vocabularies
defined by healthcare standards
4. Crowd-Sourced
Translation
Rules
Roadmap - 5
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
47. 47
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap - 6
6. Collaborative
Standards
Convergence
Create a collaborative standards
hub for RDF/OWL standards
definitions, 2. RDF
to facilitate standards
convergence
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
48. 48
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap - 7
Adopt policy incentives for
healthcare providers to achieve
semantic interoperability. 6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
49. 49
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap - 7
Adopt policy incentives for
healthcare providers to achieve
semantic interoperability.
6. Collaborative
Standards
Convergence
A healthcare information provider
has no 2. natural RDF
business incentive
to make Mappings
its data interoperable with
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
Why?
competitors.
1. RDF as a Universal
Information
Representation
50. 50
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
51. 51
What will semantic interoperability cost?
Initial Ongoing
My guesses . . .
Standards $40-500M + $30-400M / year
Translations $30-400M + $20-300M / year
Total $60-900M + $50-700M / year
What are yours?
52. 52
Opportunity cost
Lack of
interoperability
$30000 Million
per year*
Interoperability
$60-900M initial
+ $50-700M/year
*Source: http://www.calgaryscientific.com/blog/bid/284224/Interoperability-Could-
Reduce-U-S-Healthcare-Costs-by-Thirty-Billion
55. 55
Upcoming events
• New HL7 work group on "RDF for
Semantic Interoperability"
– Email if interested: david@dbooth.org
• International Conference on Biomedical
Ontologies (ICBO) – Houston Oct. 6-9,
2014
56. 56
Lift and Drop
• Maps between original format, data model
and vocabulary to RDF
Lift
to
RDF
Drop
from
RDF
57. 57
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
58. 58
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
Roadmap
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
between models
& vocabularies
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
1. RDF as a Universal
Information
Representation
59. 59
1. RDF as a Universal
Information
Representation
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
for Standards
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
Roadmap
60. 60
1. RDF as a Universal
Information
Representation
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
for Standards
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
Roadmap
61. 61
Roadmap
1. RDF as a Universal
Information
Representation
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
for Standards
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
62. 62
Roadmap
1. RDF as a Universal
Information
Representation
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
for Standards
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives
63. 63
Roadmap
1. RDF as a Universal
Information
Representation
Semantic
Interoperability
4. Crowd-Sourced
Translation
Rules
6. Collaborative
Standards
Convergence
2. RDF
Mappings
3. Translations
for Standards
5. RDF/OWL
Standards
Definitions
7. Interoperability
Incentives