What is AHSO?
The increasing threat of disease spread in a globalized world has promoted the development of electronic systems capable of screening large amounts of health data in real-time, in order to provide decision-making support around infectious disease control. While the quantity and variety of health data sources is increasing rapidly both in animal and public health, the automated interpretation of these data by computers remains a challenge. The step of data interpretation remains the most time-consuming step in the development of electronic systems for early detection of diseases. Furthermore, when such systems are developed in a country using one specific data source, results are not comparable among systems using different data sources, and are especially hard to compare among countries.
An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them.
The Animal Health Surveillance Ontology (AHSO) was initially developed to facilitate the development of smart systems for veterinary syndromic surveillance and early disease detection that do not rely on the existence of standard coding practices at source.
In 2018, the objectives have been extended to support health surveillance in general, not only for early disease detection. AHSO is now part of teh WP3 in the European funded project ORION (read more here), which aims at establishing and strengthening inter-institutional collaboration and transdisciplinary knowledge transfer in the area of surveillance data integration and interpretation, along the One Health (OH) objective of improving health and well-being. WP3, in particular, is focused on data inetroperability issues. You can read more about ORION's WP3 in the dedicated chapter in this book.
By improving data interoperability, we aim to promote the development of data-driven surveillance frameworks. You can read more about data-driven surveillance here.
What is AHSO useful for?
- Health surveillance data interoperability (system agnostic data interpretation)
- Syndromic harmonisation – across data sources, data types and languages- without the need to recode existing data
- Reuse of existing knowledge in other related fields
- Reuse of knowledge across systems
- Transparent model
- Can be adapted as knowledge changes
- Reasoning and validity checks
Aimed at supporting Animal Health Surveillance, AHSO attempts to provide a data model for the information recorded, actively or passively, during the life of an animal, which can have value for surveillance, whether it is directly related to health or not.
The boxes in the figure above represent different opportunities for observation of animals and recording of data. We do not attempt to model in full a health event, but to provide a data model for the observations _that are made about this health event, so that computers can reason with the data fast and intelligently, to provide information for surveillance. For instance, say an animal in infected with _Mycobacterium bovis . We do not try to model the infection or disease process, how it started, when clinical signs were developed, etc. Our goal is to interpret the multiple _observations _that can be made about the event, and make explicit to humans and computers the medical relationships modelled/assumed:
The sources of data can be seen as independent modules to be addressed by the ontology. See the topic on AHSO modules.
How is AHSO being developed?
AHSO is being developed in a modular, bottom up format. That is, development loops are triggered by data examples or user requirement stories that exemplify one specific type of event to be modelled by the ontology. Successive loops add complementary modules to the ontology. (Anonymised)Data samples or user requirement stories can be submitted to the AHSO team via the Issues section of the GitHub repository, or through the AHSO community discussion forum.You can visit our user requirement stories tracking page to see the requirement stories which have been submitted, the stories which are being integrated into the AHSO ontology as well as previous (closed) submissions.