SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM) Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 1 SSynCAHD Standardising Syndromic Classification in Animal Health Data (SSynCAHD) Fernanda Dórea Flavie Vial Céline Dupuy Ann Lindberg Crawford Revie SSynCAHD WORKSHOP GOALS • What participants can expect – Update on the results of the data inventory and inventory of ontologies – Learning a bit more about ontologies and their practical applications – Participation in the decisions regarding the next steps • What we expect from participants – Active discussion regarding next steps and opportunities for engagement of the VSS community
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SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 1
SSynCAHD
Standardising Syndromic Classification in Animal Health Data (SSynCAHD)
Fernanda DóreaFlavie Vial
Céline DupuyAnn Lindberg
Crawford Revie
SSynCAHD
WORKSHOP GOALS
• What participants can expect
– Update on the results of the data inventory and inventory of ontologies
– Learning a bit more about ontologies and their practical applications
– Participation in the decisions regarding the next steps
• What we expect from participants
– Active discussion regarding next steps and opportunities for engagement of the VSS community
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 2
SSynCAHD
Today’s workshop
20 minutes Quick review of ontologies and their use
40 minutes Project progress so far:• Competency questions• Data inventory• Inventory of existing ontologies
30 minutes Coffee break
30 minutes The road ahead
60 minutes Discussion: plan the next stages
SSynCAHD
Quick review of the idea and progress so far:
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 3
SSynCAHD
Defining the goal
• Promote the use of standards for classification of syndromic data
– NOT reinvent data recording standards already developed
• Promote comparability of methods and results by having standard syndromic classes
– Focus NOT on data recording, but on TRANSLATING data to syndromic groups
• Develop tools for syndromic data classification which do not require recoding of existing data
SSynCAHD
Current SS systems:Knowledge rich
Serological tests for Brucellosis
Histologicalexamination on
sample from uterus
Salmonella serotyping on vaginal swab
Microbial growth on vaginal swab
PCR test for Brucellosis
Syndrome = Reproductive
Syndrome = Reproductive
Syndrome = Reproductive
Syndrome = Reproductive
Syndrome = Reproductive
We don’t need smarter data,
But to get the right data to the right place
So that smart applications can do their work
Consensus and standards for recording the data?
Consensus and standards for USING data (classification)
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 4
SSynCAHD
Controlled vocabularies
• Require data to be manually coded
• Ignore relationships between the terms included in the vocabulary
SSynCAHD
Ontologies
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 5
SSynCAHD
Pluto
Pluto is a dwarf planet. …
The solar system
SSynCAHD
Pluto
Celestial bodies
Dwarf planet
Planet
Is a
Star
B
Rigel
G
Sun
Orbits around
Solar system
Has CenterContains:Is a: PLANETandOrbits around: SUN
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 6
SSynCAHD
” Fundamentally ontology is about reaching agreements on what things means and putting it in a machine-processable form”
SSynCAHD
Organ System
• Reproductive
• Female Genitalia
• Vulva
• Vagina
• Female Internal Reproduct. Organs
• Uterus
• Ovary
• Male External Genitalia
• Male Internal Reproductive Organs
• OTHER SYSTEMS
Clinical Signs
• Reproductive
• Abortion
• Conception failure
• OTHER SYNDROMES...
Threats
• Non-Infectious Threats
• Metabolic Disorders
• Infectious agents
• Brucella sp
• Brucella abortus
• Brucella suis
• Brucella canis
• Neospora caninum
• BVD
• IBR
Lab Test Ordered
• UnspecificEtiology
• BacterialGrowth
• Histology
• SerologicalTests
• Brucellosis
• BVDV
• PathogenIdentification
• Brucellosis
• BVDV
• Salmonella
TestResults
• Serology
• Agent Identification
• Serological Result
Abattoir finding
• Ante-Mortem Inspection
• Post-Mortem Inspection
• Partial Condemnations
• Total condemnations
Ontologies in VSS:
”the boxes” (entities)
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 7
Organ System
•Reproductive
•Female Genitalia
•Vulva
•Vagina
•Female Internal Reproducitive Organs
•Uterus
•Ovary
•Male External Genitalia
•Male Internal Reproductive Organs
•OTHER SYSTEMS
Clinical Signs
•Reproductive
•Abortion
•Conception failure
•OTHER SYNDROMES...
Threats•Non-Infectious Threats
•Metabolic Disorders
•Infectious agents
•Brucella sp
•Brucella abortus
•Brucella suis
•Brucella canis
•Neospora caninum
•BVD
•IBR
LabTest Ordered
•UnspecificEtiology
•BacterialGrowth
•Histology
•SerologicalTests
•Brucellosis
•BVDV
•PathogenIdentification
•Brucellosis
•BVDV
•Salmonella
Test Results
•Serology
•Agent Identification
•Serological Result
Abattoir finding
•Ante-Mortem Inspection
•Post-Mortem Inspection
•Partial Condemnations
•Total condemnations
IdentifiesCauses
Affects
Identifies
Related to
Reflected as Causes
Suspicions Cases
Focus on the “rules” (relationships)
SSynCAHD
Practical applications – why use standards?
–Consensus and comparability: share common understanding of the structure of information among people
–Transparency: make domain assumptions explicit
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 8
SSynCAHD
Added value – why build an ontology for these standards?
• Consensus and comparability: share common understanding of the structure of information among people AND software agents
• Not just the information, but the structure of the information(relationships or “rules”)
• Reuse and analysis of domain knowledge
– Reasoning for consistent and semi-automated growth of the ontology, and automated update of their software applications
• Particular gain to the surveillance community: secondary use of data
SSynCAHD
Why should I be involved?
• The solution needs to be problem oriented, in order to work for all
• Build a body of “community knowledge” that develops from all to all
• Project outcomes: not only the ontology but applications (more on this later)
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 9
SSynCAHD
Practical development
• Step 1– Determine the domain and the scope
• Step 2– Reuse of existing ontologies
• Step 3– Enumerate important terms in the ontology
• Step 4– Define the classes and the class hierarchy
– Top-down x bottom-up x combination
SSynCAHD
Competency questions
• Competency questions:
– Domain: veterinary syndromic surveillance
– To describe the terms and relations necessary to detect the occurrence of animal health events of interest for surveillance though recorded animal health data.
– To allow standardisation of syndromic classification of animal health data without the need for common coding practices, acknowledging the differences in data recording practices across animal health domains, institutions and countries.
– To be freely available
– Built by the veterinary syndromic surveillance community and maintained by a group of curators
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 10
SSynCAHD
Practical development
• Step 1– Determine the domain and the scope
• Step 2– Reuse of existing ontologies
• Step 3– Enumerate important terms in the ontology
• Step 4– Define the classes and the class hierarchy
– Top-down x bottom-up x combination
Inventory of biomedicalontologies
Data inventory
SSynCAHD
DATA INVENTORY
Part I: data description
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
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SSynCAHD
Origin
Belgium 7Canada 2Finland 1France 7
Italy 2Sweden 3
Switzerland 2USA 3Total 27
SSynCAHD
Data types
Abattoir 4Clinical 4
Laboratory 6Market 1
Mortality 3Production-Milk 2
Production-Registry 1Production-
Reproduction 4Rendering 1Syndromic 1
Total 27
SSynCAHD: Notes from the Second workshop – Ghent March 27th, 2015 (SVEPM)
Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 12
SSynCAHD
System implemented
No 18Partially 1Yes 8Total 27
SSynCAHD
Species
Cattle 19Horses 3Poultry 6
Pigs 5Pets 2
Small Ruminants 6
Many/ ”All” 5Single 13
More than one 9Total 27
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Standardising Syndromic Classification in Animal Health Data (SSynCAHD) 13