Coordinated Evolution of Ontologies of Informed Consent

Informed consent, whether for health or behavioral research or clinical treatment, rests on notions of voluntarism, information disclosure and understanding, and the decisionmaking capacity of the person providing consent. Whether consent is for research or treatment, informed consent serves as a safeguard for trust that permissions given by the research participant or patient are upheld across the informed consent (IC) lifecycle. The IC lifecycle involves not only documentation of the consent when originally obtained, but actions that require clear communication of permissions from the initial acquisition of data and specimens through handoffs to, for example, secondary researchers, allowing them access to data or biospecimens referenced in the terms of the original consent

From Affective Science to Psychiatric Disorder: Ontology as Semantic Bridge

Advances in emotion and affective science have yet to translate routinely into psychiatric research and practice. This is unfortunate since emotion and affect are fundamental components of many psychiatric conditions. Rectifying this lack of interdisciplinary integration could thus be a potential avenue for improving psychiatric diagnosis and treatment. In this contribution, we propose and discuss an ontological framework for explicitly capturing the complex interrelations between affective entities and psychiatric disorders, in order to facilitate mapping and integration between affective science and psychiatric diagnostics. We build on and enhance the categorisation of emotion, affect and mood within the previously developed Emotion Ontology, and that of psychiatric disorders in the Mental Disease Ontology. This effort further draws on developments in formal ontology regarding the distinction between normal and abnormal in order to formalize the interconnections. This operational semantic framework is relevant for applications including clarifying psychiatric diagnostic categories, clinical information systems, and the integration and translation of research results across disciplines

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content

Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for food and nutrition (n = 37), disease and specific population (n = 100), data description (n = 21), research description (n = 35), and supplementary (meta) data description (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology

Alcuni abstract di articoli che trattano argomenti relativi all'eHealth

Non utile per esam

ONS : an ontology for a standardized description of interventions and observational studies in nutrition

Background: The multidisciplinary nature of nutrition research is one of its main strengths. At the same time, however, it presents a major obstacle to integrate data analysis, especially for the terminological and semantic interpretations that specific research fields or communities are used to. To date, a proper ontology to structure and formalize the concepts used for the description of nutritional studies is still lacking. Results: We have developed the Ontology for Nutritional Studies (ONS) by harmonizing selected pre-existing de facto ontologies with novel health and nutritional terminology classifications. The ONS is the result of a scholarly consensus of 51 research centers in nine European countries. The ontology classes and relations are commonly encountered while conducting, storing, harmonizing, integrating, describing, and searching nutritional studies. The ONS facilitates the description and specification of complex nutritional studies as demonstrated with two application scenarios. Conclusions: The ONS is the first systematic effort to provide a solid and extensible formal ontology framework for nutritional studies. Integration of new information can be easily achieved by the addition of extra modules (i.e., nutrigenomics, metabolomics, nutrikinetics, and quality appraisal). The ONS provides a unified and standardized terminology for nutritional studies as a resource for nutrition researchers who might not necessarily be familiar with ontologies and standardization concepts

A Life Cycle Approach to the Development and Validation of an Ontology of the U.S. Common Rule (45 C.F.R. § 46)

Requirements for the protection of human research subjects stem from directly from federal regulation by the Department of Health and Human Services in Title 45 of the Code of Federal Regulations (C.F.R.) part 46. 15 other federal agencies include subpart A of part 46 verbatim in their own body of regulation. Hence 45 C.F.R. part 46 subpart A has come to be called colloquially the ‘Common Rule.’ Overall motivation for this study began as a desire to facilitate the ethical sharing of biospecimen samples from large biospecimen collections by using ontologies. Previous work demonstrated that in general the informed consent process and subsequent decision making about data and specimen release still relies heavily on paper-based informed consent forms and processes. Consequently, well-validated computable models are needed to provide an enhanced foundation for data sharing. This dissertation describes the development and validation of a Common Rule Ontology (CRO), expressed in the OWL-2 Web Ontology Language, and is intended to provide a computable semantic knowledge model for assessing and representing components of the information artifacts of required as part of regulated research under 45 C.F.R. § 46. I examine if the alignment of this ontology with the Basic Formal Ontology and other ontologies from the Open Biomedical Ontology (OBO) Foundry provide a good fit for the regulatory aspects of the Common Rule Ontology. The dissertation also examines and proposes a new method for ongoing evaluation of ontology such as CRO across the ontology development lifecycle and suggest methods to achieve high quality, validated ontologies. While the CRO is not in itself intended to be a complete solution to the data and specimen sharing problems outlined above, it is intended to produce a well-validated computationally grounded framework upon which others can build. This model can be used in future work to build decision support systems to assist Institutional Review Boards (IRBs), regulatory personnel, honest brokers, tissue bank managers, and other individuals in the decision-making process involving biorepository specimen and data sharing