Data-driven surveillance: Transforming data into ... · datadrivensurveillance.org - Parma summer...

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

DATA-DRIVEN SURVEILLANCE: Transforming data into actionable information in the One-Health health context Fernanda Dórea

Swedish National Veterinary Institute

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Surveillance

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

Data Information Action

Epidemiological data collection is abouttechnology, but effective disease

surveillance is about people

People matter in animal disease surveillance: Challenges

and opportunities for the aquaculture sector

Cecile Brugere

Dennis Mark Onuigbo

Kenton Ll. Morgan

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

Data Information Action

context knowledge insight

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

Data Information Action

context knowledge insight

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

Data Information ActionActionable

information

context knowledge insight

3.5400 positive

samples

3.5%

samples

positive

Prevalence?

DATA vs. INFORMATION

context knowledge

Data analysis

(reproducible)

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

BIG DATA

Volume

Velocity

Variety

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Surveillance

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

One-Health Surveillance

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

One-Health Surveillance

Shar

eK

no

w-h

ow

K

NO

WLE

DG

E

DA

TA

inte

rop

erab

ilit

y

prevalence

cases outbreaks

www.datadrivensurveillance.org/ontology

Investigation

Surv.

system

Surv.

Activity

Outbreak

Sample

disease

host

legislation

Sampling

designReporting

practices

place

Contribut-

ory factors

Place of

exposureFood

vehicle

result assay

material

cases

date

gender

Country

acquisition

Context

Levels of

information

Think of one dataset

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Lab data

Lab B

Interoperable

Lab data

Lab A

Lab data

Lab A

Lab data

Lab A

Epi data

Weather

data

Population

registry

Lab data

Lab DLab data

Lab C Epi data

ANIMALS

Epi data

FOOD

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Syntatic interoperability(harmonize structure)

Terminologies, data standards, dictionaries

Symptom

Diarrhoea

Symptom

Diarréia

Symptom

Diarrea

Minimum information tables

Mappings, data models

Semantic interoperability(align meaning)

Meaning, context

Source

Fecal swab

Source

Farm A

Species

Broilers

Species

Chickens

Target

Campylobacteriosis

Target

Campylobacter

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Machine interpretable

Knowledge model of a domain

Interoperability

Among data sources

Evolving knowledge

Across domains = Reusability

Semantic interoperability - ONTOLOGIES

Organism

Bacterium

Campylobacter

Avium

Gallus gallus

Mammal

Homo sapiens

Disease

Campylobacterio

sis

Production

type

Meat producing

Broiler

Clinical sign

Age

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Diagnostic

pneumonia

Clinical sign

Short of

breath

Respiratory cases

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

One Health

context

knowledge

Federated queries

”Code to data”

models

”Future-proof”

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Traditional data life cycle

Data

productionData USE Results Archive Reuse

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Linked data model

Data

production

Data user 1

Store

DATA +

SCHEMAData user 2

Results

Results

Results

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Linked data model ”Future-proof”

Reuse knowledge

Discover knowledge

Evolve knowledge

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Health Surveillance Ontology

The dataprinciple

Supporting OHS data interoperability,

integration & interpretation

Tools for Linked-Open-Data production and

use

HumansCan understand a dataset if columns

are properly labelled, and if they can

read and understand the concepts.

Semantic ambiguity must be solved

by collaboration, agreement and

documentation

The knowledge that allows humans to

understand concepts and semantic

meaning can be programmed into an

ontology to allow reading of the dataset by

machines

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Surveillance reportchapters

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Surveillance report chapters

ORION – WP3 – data interoperability – www.datadrivensurveillance.org/ontology

Separate data from information

Enrich data with CONTEXT,

not standards

Allow machines to handle

information using

KNOWLEDGE

Treat your data user

like you are used to

treat your computer

Treat your computer

like you are used to

treat your data

users

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

datadrivensurveillance.org - Parma summer school, One-Health, 9-10 June 2020

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