Information and organization in public health institutes: an ontology-based modeling of the entities in the reception-analysis-report phases

Abstract

BackgroundOntologies are widely used both in the life sciences and in the management of public and private companies. Typically, the different offices in an organization develop their own models and related ontologies to capture specific tasks and goals. Although there might be an overall coordination, the use of distinct ontologies can jeopardize the integration of data across the organization since data sharing and reusability are sensitive to modeling choices.ResultsThe paper provides a study of the entities that are typically found at the reception, analysis and report phases in public institutes in the life science domain. Ontological considerations and techniques are introduced and their implementation exemplified by studying the Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), a public veterinarian institute with different geographical locations and several laboratories. Different modeling issues are discussed like the identification and characterization of the main entities in these phases; the classification of the (types of) data; the clarification of the contexts and the roles of the involved entities. The study is based on a foundational ontology and shows how it can be extended to a comprehensive and coherent framework comprising the different institute’s roles, processes and data. In particular, it shows how to use notions lying at the borderline between ontology and applications, like that of knowledge object. The paper aims to help the modeler to understand the core viewpoint of the organization and to improve data transparency.ConclusionsThe study shows that the entities at play can be analyzed within a single ontological perspective allowing us to isolate a single ontological framework for the whole organization. This facilitates the development of coherent representations of the entities and related data, and fosters the use of integrated software for data management and reasoning across the company.

Data distribution in public veterinary service: health and safety challenges push for context-aware systems

“…These classifications are not affected by the context and are independent from the particular scenario. This means that one can apply the methodologies developed in the applied ontology area to provide guidelines and criteria [ 49 – 51 ].…”

“…While typology and provenance are successfully analyzed via the application of ontological frameworks, see e.g. [ 49 – 51 ], contextualization techniques for the distinct stakeholders need to be better understood. As an example, Livestock Geo-wiki, a platform that aims to develop a global livestock information system, provides innovative visualization and analysis tools addressing specific requirements of different groups of users but it does not consider contextualization techniques focused on users’ need classification [ 52 ].…”

Ontology Enrichment for Multi-Domain Knowledge and Expertise Representation

“…Ontology is now used widely in many domains like in health [4,5,6], engineering [7,8], software [9,10], commerce [11,12,13], law [14,15], etc. Those Ontologies use different Upper Ontology.…”