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

View Article: PubMed Central - PubMed

ABSTRACT

Background: Ontologies 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.

Results: The 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.

Conclusions: The 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.

No MeSH data available.


GUI at the lab’s reception. Graphical user interface (GUI) translated, original in Italian
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Fig1: GUI at the lab’s reception. Graphical user interface (GUI) translated, original in Italian

Mentions: Next, the sample is stored in a ward (storage room, cooler, freezer) to be distributed to the laboratories. The registration data, called “batch”, is added to the IZILAB’s “batch-list” of the ward (a kind of loading/unloading register). The sample is then collected by laboratory personnel or delivered via the IZSVe service. At the laboratory, the administrative and technical staff make a final assessment on the suitability of the sample for the requested analysis: the documents and the compliance of the specimen to the test requirements are verified. Then, the seals are broken and direct inspection of the sample content can be done. The laboratory personnel complete the data via a dedicated interface in IZILAB: the batch code ensures that data are added to the right record as well as the consistency of the sample tracking information. Some fields are shown in the IZILAB lab’s reception GUI - Graphical User Interface -(Fig. 1). The “number of external acceptance” and the “date of external acceptance” are needed to coordinate further tests, if any, run by other IZSVe Laboratories. The flag “delivery charge” activates the fields for delivery charges. The flag “identification of the payer” indicates the party charged for the procedure costs. The “rules for test assignment” provides information on the acquisition of digital data while the “first/sequence” is needed when there are several samples and/or several analyses are done on the same specimen.Fig. 1


Information and organization in public health institutes: an ontology-based modeling of the entities in the reception-analysis-report phases
GUI at the lab’s reception. Graphical user interface (GUI) translated, original in Italian
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5017037&req=5

Fig1: GUI at the lab’s reception. Graphical user interface (GUI) translated, original in Italian
Mentions: Next, the sample is stored in a ward (storage room, cooler, freezer) to be distributed to the laboratories. The registration data, called “batch”, is added to the IZILAB’s “batch-list” of the ward (a kind of loading/unloading register). The sample is then collected by laboratory personnel or delivered via the IZSVe service. At the laboratory, the administrative and technical staff make a final assessment on the suitability of the sample for the requested analysis: the documents and the compliance of the specimen to the test requirements are verified. Then, the seals are broken and direct inspection of the sample content can be done. The laboratory personnel complete the data via a dedicated interface in IZILAB: the batch code ensures that data are added to the right record as well as the consistency of the sample tracking information. Some fields are shown in the IZILAB lab’s reception GUI - Graphical User Interface -(Fig. 1). The “number of external acceptance” and the “date of external acceptance” are needed to coordinate further tests, if any, run by other IZSVe Laboratories. The flag “delivery charge” activates the fields for delivery charges. The flag “identification of the payer” indicates the party charged for the procedure costs. The “rules for test assignment” provides information on the acquisition of digital data while the “first/sequence” is needed when there are several samples and/or several analyses are done on the same specimen.Fig. 1

View Article: PubMed Central - PubMed

ABSTRACT

Background: Ontologies 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.

Results: The 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.

Conclusions: The 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.

No MeSH data available.