Unintended consequences of existential quantifications in biomedical ontologies

<p>Abstract</p> <p>Background</p> <p>The Open Biomedical Ontologies (OBO) Foundry is a collection of freely available ontologically structured controlled vocabularies in the biomedical domain. Most of them are disseminated via both the OBO Flatfile Format and the semantic web format Web Ontology Language (OWL), which draws upon formal logic. Based on the interpretations underlying OWL description logics (OWL-DL) semantics, we scrutinize the OWL-DL releases of OBO ontologies to assess whether their logical axioms correspond to the meaning intended by their authors.</p> <p>Results</p> <p>We analyzed ontologies and ontology cross products available via the OBO Foundry site <url>http://www.obofoundry.org</url> for existential restrictions (<it>someValuesFrom</it>), from which we examined a random sample of 2,836 clauses.</p> <p>According to a rating done by four experts, 23% of all existential restrictions in OBO Foundry candidate ontologies are suspicious (Cohens' <it>κ </it>= 0.78). We found a smaller proportion of existential restrictions in OBO Foundry cross products are suspicious, but in this case an accurate quantitative judgment is not possible due to a low inter-rater agreement (<it>κ </it>= 0.07). We identified several typical modeling problems, for which satisfactory ontology design patterns based on OWL-DL were proposed. We further describe several usability issues with OBO ontologies, including the lack of ontological commitment for several common terms, and the proliferation of domain-specific relations.</p> <p>Conclusions</p> <p>The current OWL releases of OBO Foundry (and Foundry candidate) ontologies contain numerous assertions which do not properly describe the underlying biological reality, or are ambiguous and difficult to interpret. The solution is a better anchoring in upper ontologies and a restriction to relatively few, well defined relation types with given domain and range constraints.</p

Polynomial-Time Reasoning Support for Design and Maintenance of Large-Scale Biomedical Ontologies

Description Logics (DLs) belong to a successful family of knowledge representation formalisms with two key assets: formally well-defined semantics which allows to represent knowledge in an unambiguous way and automated reasoning which allows to infer implicit knowledge from the one given explicitly. This thesis investigates various reasoning techniques for tractable DLs in the EL family which have been implemented in the CEL system. It suggests that the use of the lightweight DLs, in which reasoning is tractable, is beneficial for ontology design and maintenance both in terms of expressivity and scalability. The claim is supported by a case study on the renown medical ontology SNOMED CT and extensive empirical evaluation on several large-scale biomedical ontologies

A Framework for Interoperability Between Models with Hybrid Tools

Complex system development and maintenance face the challenge of dealing with different types of models due to language affordances, preferences, sizes, and so forth that involve interaction between users with different levels of proficiency. Current conceptual data modelling tools do not fully support these modes of working. It requires that the interaction between multiple models in multiple languages is clearly specified to ensure they keep their intended semantics, which is lacking in extant tools. The key objective is to devise a mechanism to support semantic interoperability in hybrid tools for multi-modal modelling in a plurality of paradigms, all within one system. We propose FaCIL, a framework for such hybrid modelling tools. We design and realise the framework FaCIL, which maps UML, ER and ORM2 into a common metamodel with rules that provide the central point for management among the models and that links to the formalisation and logic-based automated reasoning. FaCIL supports the ability to represent models in different formats while preserving their semantics, and several editing workflows are supported within the framework. It has a clear separation of concerns for typical conceptual modelling activities in an interoperable and extensible way. FaCIL structures and facilitates the interaction between visual and textual conceptual models, their formal specifications, and abstractions as well as tracking and propagating updates across all the representations. FaCIL is compared against the requirements, implemented in crowd 2.0, and assessed with a use case. The proof-of-concept implementation in the web-based modelling tool crowd 2.0 demonstrates its viability. The framework also meets the requirements and fully supports the use case

INVESTIGATING POSSIBILITIES AND PROBABILITIES OF BIOMEDICAL INFORMATICS (BMI): BEYOND BIOLOGY AND INFORMATION

My work focuses on how medicalized minds and bodies are refashioned through the concepts and technologies of Biomedical Informatics (BMI). I attempt to make visible objects of informatics that mark the human as a digital machine operating among and within computerized agencies, artificial intelligence, and what has been termed Big Data correlation. Specifically, the anthropological puzzle that I investigate focuses on the BMI imagination and its implicit and implemented effects upon doctors as operators, patients as sites, and informaticians as technicians of “new” medicine in a world of expanding computerized data that shifts and refashions the human care encounter. I argue that the contemporary of BMI has a far wider organizing effect upon healthcare and medicalized bodies than previous aspirations based on computer technology as mere tools in medicine. Through a rapid development and deployment of intelligent databases and computerized networks, BMI is currently restructuring modes of clinical care. As a set of scientific practices, it is reconstituting earlier medical informatics of the 1970s, 1980’s, 1990’s and pushing these modes of care in different directions. Such restructurings come in contact with non-human operations of medico-scientific systems of knowledge and through programmable expressions that impinge upon doctors’ deliberations through everyday encounters with patients. I approach these puzzles and clinical experiences through the figure of an informatics body that frames emergent arrangements of computerized algorithms, organization, disease, genomics, and therapeutic order. As an informatics body, the human falls under questions embedded in this deeper convergence of medical digitalization. Complex computerizations and algorithmic forms that are designed to bring clinical improvement are giving rise to unanticipated effects that are refashioning the body of the patient and the mind of the physician in ways that have been under-examined. In futures of biomedicine that I investigate, an informatics-based medicine, the figure of the human in the continuum of care is constantly being reengineered and redeployed. Throughout my investigation I ask What acts, human and non-human, possess the possibility of therapeutic improvement and can bring other things to life that do not originate in current therapeutic order? I suggest that systems of machine agency that are targeting and monitoring for disease and health are reconstituting who and what has access to care, as well as access to decision agency among intelligent and computerized care data

Pseudo-contractions as Gentle Repairs

Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas

Enhancing systems biology models through semantic data integration

Studying and modelling biology at a systems level requires a large amount of data of different experimental types. Historically, each of these types is stored in its own distinct format, with its own internal structure for holding the data produced by those experiments. While the use of community data standards can reduce the need for specialised, independent formats by providing a common syntax, standards uptake is not universal and a single standard cannot yet describe all biological data. In the work described in this thesis, a variety of integrative methods have been developed to reuse and restructure already extant systems biology data. SyMBA is a simple Web interface which stores experimental metadata in a published, common format. The creation of accurate quantitative SBML models is a time-intensive manual process. Modellers need to understand both the systems they are modelling and the intricacies of the SBML format. However, the amount of relevant data for even a relatively small and well-scoped model can be overwhelming. Saint is a Web application which accesses a number of external Web services and which provides suggested annotation for SBML and CellML models. MFO was developed to formalise all of the knowledge within the multiple SBML specification documents in a manner which is both human and computationally accessible. Rule-based mediation, a form of semantic data integration, is a useful way of reusing and re-purposing heterogeneous datasets which cannot, or are not, structured according to a common standard. This method of ontology-based integration is generic and can be used in any context, but has been implemented specifically to integrate systems biology data and to enrich systems biology models through the creation of new biological annotations. The work described in this thesis is one step towards the formalisation of biological knowledge useful to systems biology. Experimental metadata has been transformed into common structures, a Web application has been created for the retrieval of data appropriate to the annotation of systems biology models and multiple data models have been formalised and made accessible to semantic integration techniques.EThOS - Electronic Theses Online ServiceBBSRCEPSRCGBUnited Kingdo