Biodiversity Information Science and Standards :
Conference Abstract
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Corresponding author: Francesca Jaroszynska (francesca.jaroszynska@ofb.gouv.fr)
Received: 01 Sep 2022 | Published: 07 Sep 2022
© 2022 Francesca Jaroszynska, Guillaume Body, Sophie Pamerlon, Anne-Sophie Archambeau
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Jaroszynska F, Body G, Pamerlon S, Archambeau A-S (2022) Implementing Nestedness in Darwin Core: An epidemiology case study. Biodiversity Information Science and Standards 6: e94355. https://doi.org/10.3897/biss.6.94355
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Wildlife diseases have an impact on biodiversity, the economy, and public health. Better knowledge of disease patterns would be to the benefit of conservation measures, livestock production and, thus, ultimately human health. Nevertheless, disease surveillance systems operate mostly at a national scale, with incompatible data structures, inhibiting effective data sharing and thus rapid transnational responses to disease outbreak. As the risk of disease to biodiversity, the economy and to public health increases with climate change, land-use change and trade, the necessity for a common data standard to improve data sharing of surveillance efforts is greater than ever to enable transnational proactive and reactive measures to be taken.
To address these large issues, a consortium for the European Food and Safety Authority (EFSA; the Enetwild consortium) was formed to collect existing data on wildlife host abundance and distribution in Europe. Alongside data on their associated pathogens, the consortium is attempting to develop data models to aggregate the host data according to the Darwin Core*
However, the complexity of zoonotic disease and wildlife distribution data is not easily captured in the current version of the Darwin Core standard, often comprising complex data structures with species interactions and partial information. Firstly, zoonotic disease data consist of observations of both the host and the pathogen, whereby each positive case of a disease is associated with the observation of the host species. Secondly, wildlife host distribution data frequently contain detailed information for only some individuals of a group when multiple individuals of the host species are observed simultaneously, such as life stage and sex. In order to capture these types of interactions and subsetting, we need to be able to handle the hierarchical structuring of these data.
In an attempt to resolve these issues, a data model in line with the Darwin Core standard was initially developed for wildlife host population data (
Hierarchical structuring of the Occurrence extension, accommodating the presence of the host species (Sus scrofa) and the pathogen (African Swine Fever Virus).
occurrenceID | parentOccurrenceID | scientificName | individualCount | occurrenceStatus | lifeStage | sex |
roadkill1 | Sus scrofa | 11 | ||||
roadkill1-1 | roadkill1 | Sus scrofa | 3 | adult | female | |
roadkill1-2 | roadkill1 | Sus scrofa | 5 | adult | male | |
roadkill1-3 | roadkill1 | Sus scrofa | 3 | undetermined | undetermined | |
roadkill1-1-1 | roadkill1-1 | African Swine Fever Virus | present |
Using the Darwin Core standard, we propose a data model that would allow effective harmonisation of zoonotic disease data, demonstrating that harmonisation of disease surveillance data in Europe is possible. Finding solutions to capturing complex hierarchical biotic interactions in Darwin Core is currently underway at GBIF*
wildlife management, nested relationship, zoonotic disease surveillance
Francesca Jaroszynska
TDWG 2022
The authors declare no conflicts of interest.