Veruska Zamborlini

On the Representation of Temporally Changing Information in OWL

An important challenge in the Knowledge Representation area is on representing and reasoning over temporally changing information. Particularly, a number of authors have been investigating approaches to extend the expressivity beyond what is currently supported by the DL (Description Logics) based languages in order to address this issue, while maintaining compatibility with subclasses of DLs adopted in the Semantic Web. This is mainly due to the increasing popularity of the Semantic Web initiative as well as the role played by DL in that context. In this paper we defend the need of a higher-level foundational framework based on results coming from the discipline of Formal Ontology. We present two complementary proposals for modeling temporally changing information in OWL, based on the most discussed strategy in the literature to address this problem, namely, the use of a perdurantist (or 4D) view of domain entities. Moreover we compare the results with some related work and discuss its limitations and further improvements.

Using a trope-based foundational ontology for bridging different areas of concern in ontology-driven conceptual modeling

In recent years, ontology-driven reference models have gained much attention in the literature due to their potential key role in activities such as complex information modeling and semantic interoperability. The engineering process of these conceptual models should account for different phases addressing different areas of concern. In an initial phase of conceptual domain modeling, the target modeling artifacts should be constructed with the goal of maximizing quality attributes such as expressivity and truthfulness to the represented domain in reality. In a subsequent development phase, the resulting domain models can be used to guide the design decisions in the construction of different implementation artifacts addressing different computational concerns. In this paper, we present a philosophically sound, cognitively-oriented and formally characterized foundational theory of objects and tropes (property-instances). Moreover, we use this theory to bring about engineering contributions to both the aforementioned phases of ontology-driven conceptual modeling. Firstly, we show how this theory has been used to (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML. Furthermore, we provide precise directives on how to map conceptual domain models in this language to their implementation in less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) that partially preserves the modal-temporal semantics of OntoUML. Finally, we discuss computational support for the proposed approach in terms of conceptual model construction, automatic transformation and temporal querying. We present a foundational ontology for conceptual modeling.We present a formal characterization of this ontology.We discuss a conceptual modeling language founded on this ontology (OntoUML).We provide mapping directives bridging OntoUML and the semantic web language OWL.We discuss computational support for model building, transformation and manipulation.

An ontology-based application in heart electrophysiology: representation, reasoning and visualization on the web

Computational technologies have been increasingly explored to make biomedical knowledge and data more accessible for human understanding, comparison, analysis and communication. In this context, ontology has been recognized in the bioinformatics literature as a suitable technique for advancing knowledge and data representations in Biomedicine. Moreover, automated reasoning and visualization mechanisms can favor in providing support for human comprehensibility as well as in dealing with the complexity inherent to this domain. This paper elaborates on the application of ontology for heart electrophysiology representation, reasoning and visualization on the web. The ontology-based application we propose can be used to offer support for interactive learning in heart electrophysiology.

Inferring Recommendation Interactions in Clinical Guidelines: Case-studies on Multimorbidity

The formal representation of clinical knowledge is still an open research topic. Classical representation languages for clinical guidelines are used to produce diagnostic and treatment plans. However, they have important limitations, e.g. when looking for ways to re-use, combine, and reason over existing clinical knowledge. These limitations are especially problematic in the context of multimorbidity; patients that suffer from multiple diseases. To overcome these limitations, this paper proposes a model for clinical guidelines (TMR4I) that allows the re-use and combination of knowledge from multiple guidelines. Semantic Web technology is applied to implement the model, allowing us to automatically infer interactions between recommendations, such as recommending the same drug more than once. It relies on an existing Linked Data set, DrugBank, for identifying drug-drug interactions. We evaluate the model by applying it to two realistic case studies on multimorbidity that combine guidelines for two (Duodenal Ulcer and Transient Ischemic Attack) and three diseases (Osteoarthritis, Hypertension and Diabetes) and compare the results with existing methods.

Towards a Conceptual Model for Enhancing Reasoning About Clinical Guidelines - A Case-Study on Comorbidity.

Computer-Interpretable Guidelines (CIGs) are representations of Clinical Guidelines (CGs) in computer interpretable languages. CIGs have been pointed as an alternative to deal with the various limitations of paper based CGs to support healthcare activities. Although the improvements offered by existing CIG languages, the complexity of the medical domain requires advanced features in order to reuse, share, update, combine or personalize their contents. We propose a conceptual model for representing the content of CGs as a result from an iterative approach that take into account the content of real CGs, CIGs languages and foundational ontologies in order to enhance the reasoning capabilities required to address CIG use-cases. In particular, we apply our approach to the comorbidity use-case and illustrate the model with a realistic case study (Duodenal Ulcer and Transient Ischemic Attack) and compare the results against an existing approach.

A Conceptual Model for Detecting Interactions among Medical Recommendations in Clinical Guidelines

Representation of clinical knowledge is still an open research topic. In particular, classical languages designed for representing clinical guidelines, which were meant for producing diagnostic and treatment plans, present limitations such as for re-using, combining, and reasoning over existing knowledge. In this paper, we address such limitations by proposing an extension of the TMR conceptual model to represent clinical guidelines that allows re-using and combining knowledge from several guidelines to be applied to patients with multimorbidities. We provide means to (semi)automatically detect interactions among recommendations that require some attention from experts, such as recommending more than once the same drug. We evaluate the model by applying it to a realistic case study involving 3 diseases (Osteoarthritis, Hypertension and Diabetes) and compare the results with two other existing methods.

A Common Foundational Theory for Bridging Two Levels in Ontology-Driven Conceptual Modeling

In recent years, there has been a growing interest in the use of Foundational Ontologies, i.e., ontological theories in the philosophical sense to provide real-world semantics and principled modeling guidelines for conceptual domain modeling languages. In this paper, we demonstrate how a philosophically sound and cognitively-oriented ontological theory of objects and moments (property-instances) has been used to: (i) (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML; (ii) derive supporting technology for mapping these conceptual domain models to less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) which addresses the issue of temporally changing information.

Analyzing Recommendations Interactions in Clinical Guidelines - Impact of Action Type Hierarchies and Causation Beliefs.

Accounting for patients with multiple health conditions is a complex task that requires analysing potential interactions among recommendations meant to address each condition. Although some approaches have been proposed to address this issue, important features still require more investigation, such as (re)usability and scalability. To this end, this paper presents an approach that relies on reusable rules for detecting interactions among recommendations coming from various guidelines. It extends previously proposed models by introducing the notions of action type hierarchy and causation beliefs, and provides a systematic analysis of relevant interactions in the context of multimorbidity. Finally, the approach is assessed based on a case-study taken from the literature to highlight the added value of the approach.

Generalizing the Detection of Internal and External Interactions in Clinical Guidelines

This paper presents a method for formally representing Computer-Interpretable Guidelines to deal with multimorbidity. Although some approaches for merging guidelines exist, improvements are still required for combining several sources of information and coping with possibly conflicting pieces of evidence coming from clinical studies. Our main contribution is twofold: (i) we provide general models and rules for representing guidelines that expresses evidence as causation beliefs; (ii) we introduce a mechanism to exploit external medical knowledge acquired from Linked Open Data (Drugbank, Sider, DIKB) to detect potential interactions between recommendations. We apply this framework to merge three guidelines (Osteoarthritis, Diabetes, and Hypertension) in order to illustrate the capability of this approach for detecting potential conflicts between guidelines and eventually propose alternatives.

Using a lightweight ontology of heart electrophysiology in an interactive web application

Biomedical knowledge and data have been increasingly more explored by computer programs in providing support for human visualization of biomedical phenomena. Use scenarios of such graphical simulations range from physicians decision support to aid-learning in medical sciences. The knowledge and data representation often plays a prominent role in such biomedical applications. In this sense, this paper introduces the use of a lightweight ontology of heart electrophysiology in an interactive web application. We reflect on this ontology-based application to highlight some benefits achieved with a representation based on a combination of the semantic web languages OWL DL and SWRL. The application can be used to offer support for interactive learning in heart electrophysiology.