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EFSA Journal
Article . 2019 . Peer-reviewed
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EFSA Journal
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PubMed Central
Other literature type . 2019
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SIGMA Animal Disease Data Model

A comprehensive approach for the collection of standardised data on animal diseases
Authors: Zancanaro, Gabriele; Antoniou, Sotiria Eleni; Bedriova, Marta; Boelaert, Frank; Gonzales Rojas, José; Monguidi, Mario; Roberts, Helen; +2 Authors

SIGMA Animal Disease Data Model

Abstract

The European Commission is routinely asking EFSA for scientific and technical support in the epidemiological analysis of animal disease outbreaks (i.e. African swine fever, lumpy skin disease and avian influenza) and to report or assess surveillance data (i.e. Echinococcus multilocularis and avian influenza). For this purpose, EFSA has over the last years carried out several data collections and gathered specific information on outbreaks, surveillance activities and concerned animal populations (i.e. poultry, domestic pigs, cattle and wildlife such as wild boar). EFSA aims to work together closely with Member States in order to (i) reduce the Member States' manual input of the data to be submitted to EFSA; (ii) avoid double reporting to EFSA; (iii) provide the Member States with tools to produce automatically their own draft national reports on animal health and surveillance in a protected environment to ensure data protection; (iv) increase the quality of the data received from the Member States; and (v) shorten the time to retrieve up-to-date data, relevant for risk assessment purposes. With this purpose, EFSA launched a project called SIGMA. It is important to highlight that the SIGMA - Animal Disease Data Model (σ-ADM) focuses on data which are known to be already collected by several Member States under different legal frameworks and for different purposes. The version presented in this report, will be subject to modifications and updates derived from the feedback during the implementation phase.

Keywords

Scientific Report

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Top 10%
Top 10%
Green
gold