COLEMAN - Buffalo Ontology Site
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Transcript COLEMAN - Buffalo Ontology Site
Controlled vocabularies
&
Ontologies
- DSS -
MDSS
Malaria Decision Support System
Integration of a number of data sets that
will allow for informed choices, decisions
and policy.
MOZAMBIQUE
MOZAMBIQUE
MOZAMBIQUE
Ingw
Ingwavum
avumaa
Kosi
Kosi Bay
Bay
Ingw
Ingwavum
avumaa
WEEK 2
WEEK 4
WEEK 6
SWAZILAND
SWAZILAND
WEEK 8
Sodw
Sodw
ana
ana Bay
Bay
0
Hlabisa
Hlabisa
Spraying Progress During Round 3
01 October 2003 to 16 January 2004
Zone 2A (Boane)
Malaria Incidence
per 1000 population
St
St Lucia
Lucia
350
to 600
150
to 350
50
to 150
25
to 50
5
to 25
0.01 to 5
Hlabisa
Hlabisa
Hluhluw
Hluhluwee
Malaria Incidence
Per 1000 Population
St
St Lucia
Lucia
50
to 150
25
to 50
0.01 to 25
0
to 0.01
Nature Reserves
Nature Reserves
Water Bodies
Water Bodies
30
15
kilometers
Mkhuze
Mkhuze
80 to 100
60 to 80
40 to 60
20 to 40
0 to 20
0
WEEK 16
Hluhluw
Hluhluwee
WEEK 14
WEEK 12
30
Mkhuze
Mkhuze
15
kilometers
Sodw
Sodw
ana
ana Bay
Bay
Jozini
Jozini
Jozini
Jozini
WEEK 10
SWAZILAND
Kosi
Kosi Bay
Bay
Main Tow ns
Em
Empangeni
pangeni
Richards
Richards Bay
Bay
0
Magisterial Districts
Main Tow ns
Em
Empangeni
pangeni
Richards
Richards Bay
Bay
0
Malaria incidence per 1000 people: July 1999 to June 2000
Magisterial Districts
Sub-District Areas
Sub-District Areas
Malaria incidence per 1000 people: July 2003 to June 2004
Malaria surveillance in southern Africa
NOW – Open Souce -integrated
Early 2000 – SQL - integrated
Mid 90s Ms. Access - fragmented
Early 90s Dbase + EpiInfo - fragmented
50s Eradication - Paper
Software
What it is:
PostgreSQL, is a highly scalable, SQL compliant, open source object-relational
database management system.
Why we decided on using it?
• Free
• Open source
• Easily spatially enabled
What it is:
PHP is a widely-used general-purpose scripting language that is especially suited for
Web development and can be embedded into HTML.
Why we decided on using it?
• Free
• Open source
• What it is:
Is an extension to the PostgreSQL object-relational database system.
• Allows GIS (Geographic Information System) objects to be stored in the database.
Why we decided on using it?
• Free
• Open source
SYSTEM
Health
Information
System
malaria
patient / case
data
MODULE
TYPE
CATEGORY
Passive surveillance
Symptomology, Onset date, Diagnostic
tests, Serotype, Outcome etc
CLINICAL
Dengue virus in vector populations
DENGUE VIRUS
SURVEILLANCE
Active Surveillance
Dengue virus in human population
MALARIA DECISION SUPPORT SYSTEM
Entomology
Surveillance
System
mosquito
population
data
Intervention
Monitoring
System
malaria
control
interventions
Insecticide
Resistance
Indoor Residual
Spraying:
Insecticide Treated
Bed-nets
Other interventions
Fever of Unknown Origin
Dengue cases
Insecticide resistance (larvae, adults)
DISEASE
SURVEILLANCE
(passive or active)
VECTOR
SURVEILLANCE
Vector presence & abundance
(larval, pupal, adult indices)
Immatures: Mechanical source
reduction
Immatures: Biological control
VECTOR CONTROL
Immatures: Chemical control
Adults: Chemical spray control
Adults: Chemical ITM-based control
Indicator
Survey
malaria
prevalence
surveys
Parasitemia &
Anaemia
EDUCATION
Household Indicators
Specific spatial data
Spatial Data
GIS
data
Knowledge, Attitude and Practice
among population
Backdrop spatial data
- Geographical boundaries
- Location of hospitals, health clinics,
schools, cemeteries etc
- Socioeconomic characteristics
- Environmental factors
(climate, elevation, vegetation)
SPATIAL
BACKBONE
DENGUE DECISION SUPPORT SYSTEM
Species identification
and infectivity
Complexity
entomopathogenic
nematodes
MALARIA
MIRO
cold fogs
growth regulator
IDO
circular net
thermal fog
Terms
self supporting net
space spraying
DENGUE
GAZETTEER
Definitions
romanomermis culicivorax
wedge shaped net
Relationships
pathogens
CDC light trap
romanomermis iyengari
residual indoor spraying
ONTOLOGY
CV
long lasting nets
protista
rectangular net
outdoor
Process
Vector surveillance ontology
X
Vector management ontology
.
Process
Interpret
Disseminate
Use
Decision making
Analyze data
Annotate data
Add relationships
Add definitions
Indentify terms
Conceptualize
Implementation
Development
Incorporate into
database schema
FormalizeCV
ontology
Separate
terms
X
CV web assistant
Planning and constructing an ontology is a process that requires participation of
and consensus among the expert community from the start!
Participants will be able to:
1) propose new terms
2) propose modifications to existing
terms and/or their definitions
3) comment on structures and undefined
relationships.
No restrictions will apply to participation
and all contributions will be validated.
MIRO, available for downloading at:http://obo.cvs.sourceforge.net/*checkout*/obo/obo/ontology/phenotype/mosquito_insecticide_resistance.obo
Linkage
of systems
Data sharing
IR base a global
database of insecticide
resistance.
Insecticide resistant
components feeds
IR Base.
IR Base
Insecticide
Resistance
Malaria Control Programme
MDSS
Entomology database
components.
Operational.
Entomology Database
Insecticide
Resistance
Species
Density
Sporozoite
Rate
Linkage
of systems
Global
databases
ITEGRATION OF DATA
WARN
IR Base
MERG
Malaria
Atlas
MDSS
Malaria Control Programme
MARA
Challenges & Opportunities
• Time
• Financial resources
• Priorities/commitment
• Advocacy
• Community Participation
& Contributions
• Roles & Responsibilities
• Ownership
• Sustainability
• Provide opportunity to
contribute
• Initiate collaborative efforts
• Provide standardizationannotation
• Assist software development
process
• Provide better quality data
• Provide improved comparison
of data
• Support contributions to global
warehouses + interoperability
• The use supports better
decisions
• Bigger picture – indirectly save
lives