14 research outputs found
Barry Smith an sich
Festschrift in Honor of Barry Smith on the occasion of his 65th Birthday. Published as issue 4:4 of the journal Cosmos + Taxis: Studies in Emergent Order and Organization. Includes contributions by Wolfgang Grassl, Nicola Guarino, John T. Kearns, Rudolf LĂŒthe, Luc Schneider, Peter Simons, Wojciech Ć»eĆaniec, and Jan WoleĆski
OntoCR: A CEN/ISO-13606 clinical repository based on ontologies
Objective: To design a new semantically interoperable clinical repository, based on ontologies, conforming to CEN/ISO 13606 standard. Materials and Methods: The approach followed is to extend OntoCRF, a framework for the development of clinical repositories based on ontologies. The meta-model of OntoCRF has been extended by incorporating an OWL model integrating CEN/ISO 13606, ISO 21090 and SNOMED CT structure. Results: This approach has demonstrated a complete evaluation cycle involving the creation of the meta-model in OWL format, the creation of a simple test application, and the communication of standardized extracts to another organization. Discussion: Using a CEN/ISO 13606 based system, an indefinite number of archetypes can be merged (and reused) to build new applications. Our approach, based on the use of ontologies, maintains data storage independent of content specification. With this approach, relational technology can be used for storage, maintaining extensibility capabilities. Conclusions: The present work demonstrates that it is possible to build a native CEN/ISO 13606 repository for the storage of clinical data. We have demonstrated semantic interoperability of clinical information using CEN/ISO 13606 extracts
Semantic Similarity in Cheminformatics
Similarity in chemistry has been applied to a variety of problems: to predict biochemical properties of molecules, to disambiguate chemical compound references in natural language, to understand the evolution of metabolic pathways, to predict drug-drug interactions, to predict therapeutic substitution of antibiotics, to estimate whether a compound is harmful, etc. While measures of similarity have been created that make use of the structural properties of the molecules, some ontologies (the Chemical Entities of Biological Interest (ChEBI) being one of the most relevant) capture chemistry knowledge in machine-readable formats and can be used to improve our notions of molecular similarity. Ontologies in the biomedical domain have been extensively used to compare entities of biological interest, a technique known as ontology-based semantic similarity. This has been applied to various biologically relevant entities, such as genes, proteins, diseases, and anatomical structures, as well as in the chemical domain. This chapter introduces the fundamental concepts of ontology-based semantic similarity, its application in cheminformatics, its relevance in previous studies, and future potential. It also discusses the existing challenges in this area, tracing a parallel with other domains, particularly genomics, where this technique has been used more often and for longer
Metarel, an ontology facilitating advanced querying of biomedical knowledge
Knowledge management has become indispensible in the Life Sciences for integrating and querying the enormous amounts of detailed knowledge about genes, organisms, diseases, drugs, cells, etc. Such detailed knowledge is continuously generated in bioinformatics via both hardware (e.g. raw data dumps from microâarrays) and software (e.g. computational analysis of data). Wellâknown frameworks for managing knowledge are relational databases and spreadsheets. The doctoral dissertation describes knowledge management in two more recentlyâinvestigated frameworks: ontologies and the Semantic Web. Knowledge statements like âlions live in Africaâ and âgenes are located in a cell nucleusâ are managed with the use of URIs, logics and the ontological distinction between instances and classes. Both theory and practice are described. Metarel, the core subject of the dissertation, is an ontology describing relations that can bridge the mismatch between networkâbased relations that appeal to internet browsing and logicâbased relations that are formally expressed in Description Logic. Another important subject of the dissertation is BioGateway, which is a knowledge base that has integrated biomedical knowledge in the form of hundreds of millions of networkâbased relations in the RDF format. Metarel was used to upgrade the logical meaning of these relations towards Description Logic. This has enabled to build a computer reasoner that could run over the knowledge base and derive new knowledge statements
A foundation for ontology modularisation
There has been great interest in realising the Semantic Web. Ontologies are used to define Semantic Web applications. Ontologies have grown to be large and complex to the point where it causes cognitive overload for humans, in understanding and maintaining, and for machines, in processing and reasoning. Furthermore, building ontologies from scratch is time-consuming and not always necessary. Prospective ontology developers could consider using existing ontologies that are of good quality. However, an entire large ontology is not always required for a particular application, but a subset of the knowledge may be relevant. Modularity deals with simplifying an ontology for a particular context or by structure into smaller ontologies, thereby preserving the contextual knowledge. There are a number of benefits in modularising an ontology including simplified maintenance and machine processing, as well as collaborative efforts whereby work can be shared among experts. Modularity has been successfully applied to a number of different ontologies to improve usability and assist with complexity. However, problems exist for modularity that have not been satisfactorily addressed. Currently, modularity tools generate large modules that do not exclusively represent the context. Partitioning tools, which ought to generate disjoint modules, sometimes create overlapping modules. These problems arise from a number of issues: different module types have not been clearly characterised, it is unclear what the properties of a 'good' module are, and it is unclear which evaluation criteria applies to specific module types. In order to successfully solve the problem, a number of theoretical aspects have to be investigated. It is important to determine which ontology module types are the most widely-used and to characterise each such type by distinguishing properties. One must identify properties that a 'good' or 'usable' module meets. In this thesis, we investigate these problems with modularity systematically. We begin by identifying dimensions for modularity to define its foundation: use-case, technique, type, property, and evaluation metric. Each dimension is populated with sub-dimensions as fine-grained values. The dimensions are used to create an empirically-based framework for modularity by classifying a set of ontologies with them, which results in dependencies among the dimensions. The formal framework can be used to guide the user in modularising an ontology and as a starting point in the modularisation process. To solve the problem with module quality, new and existing metrics were implemented into a novel tool TOMM, and an experimental evaluation with a set of modules was performed resulting in dependencies between the metrics and module types. These dependencies can be used to determine whether a module is of good quality. For the issue with existing modularity techniques, we created five new algorithms to improve the current tools and techniques and experimentally evaluate them. The algorithms of the tool, NOMSA, performs as well as other tools for most performance criteria. For NOMSA's generated modules, two of its algorithms' generated modules are good quality when compared to the expected dependencies of the framework. The remaining three algorithms' modules correspond to some of the expected values for the metrics for the ontology set in question. The success of solving the problems with modularity resulted in a formal foundation for modularity which comprises: an exhaustive set of modularity dimensions with dependencies between them, a framework for guiding the modularisation process and annotating module, a way to measure the quality of modules using the novel TOMM tool which has new and existing evaluation metrics, the SUGOI tool for module management that has been investigated for module interchangeability, and an implementation of new algorithms to fill in the gaps of insufficient tools and techniques
An ontology for formal representation of medication adherence-related knowledge : case study in breast cancer
Indiana University-Purdue University Indianapolis (IUPUI)Medication non-adherence is a major healthcare problem that negatively impacts
the health and productivity of individuals and society as a whole. Reasons for medication
non-adherence are multi-faced, with no clear-cut solution. Adherence to medication
remains a difficult area to study, due to inconsistencies in representing medicationadherence
behavior data that poses a challenge to humans and todayâs computer
technology related to interpreting and synthesizing such complex information.
Developing a consistent conceptual framework to medication adherence is needed to
facilitate domain understanding, sharing, and communicating, as well as enabling
researchers to formally compare the findings of studies in systematic reviews.
The goal of this research is to create a common language that bridges human and
computer technology by developing a controlled structured vocabulary of medication
adherence behaviorââMedication Adherence Behavior Ontologyâ (MAB-Ontology)
using breast cancer as a case study to inform and evaluate the proposed ontology and
demonstrating its application to real-world situation. The intention is for MAB-Ontology
to be developed against the background of a philosophical analysis of terms, such as
belief, and desire to be human, computer-understandable, and interoperable with other
systems that support scientific research.
The design process for MAB-Ontology carried out using the METHONTOLOGY
method incorporated with the Basic Formal Ontology (BFO) principles of best practice.
This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including
adherence assessment, adherence determinants, adherence theories, adherence
taxonomies, and tacit knowledge source types. These sources were analyzed using a
systematic approach that involved some questions applied to all source types to guide
data extraction and inform domain conceptualization. A set of intermediate
representations involving tables and graphs was used to allow for domain evaluation
before implementation. The resulting ontology included 629 classes, 529 individuals, 51
object property, and 2 data property.
The intermediate representation was formalized into OWL using Protégé. The
MAB-Ontology was evaluated through competency questions, use-case scenario, face
validity and was found to satisfy the requirement specification. This study provides a
unified method for developing a computerized-based adherence model that can be
applied among various disease groups and different drug categories
Developing Ontological Background Knowledge for Biomedicine
Biomedicine is an impressively fast developing, interdisciplinary field of
research. To control the growing volumes of biomedical data, ontologies are
increasingly used as common organization structures. Biomedical ontologies
describe domain knowledge in a formal, computationally accessible way. They
serve as controlled vocabularies and background knowledge in applications
dealing with the integration, analysis and retrieval of heterogeneous types
of data. The development of biomedical ontologies, however, is hampered by
specific challenges. They include the lack of quality standards, resulting
in very heterogeneous resources, and the decentralized development of
biomedical ontologies, causing the increasing fragmentation of domain
knowledge across them.
In the first part of this thesis, a life cycle model for biomedical
ontologies is developed, which is intended to cope with these challenges.
It comprises the stages "requirements analysis", "design and
implementation", "evaluation", "documentation and release" and
"maintenance". For each stage, associated subtasks and activities are
specified. To promote quality standards for biomedical ontology
development, an emphasis is set on the evaluation stage. As part of it,
comprehensive evaluation procedures are specified, which allow to assess
the quality of ontologies on various levels. To tackle the issue of
knowledge fragmentation, the life cycle model is extended to also cover
ontology alignments. Ontology alignments specify mappings between related
elements of different ontologies. By making potential overlaps and
similarities between ontologies explicit, they support the integration of
ontologies and help reduce the fragmentation of knowledge.
In the second part of this thesis, the life cycle model for biomedical
ontologies and alignments is validated by means of five case studies. As a
result, they confirm that the model is effective. Four of the case studies
demonstrate that it is able to support the development of useful new
ontologies and alignments. The latter facilitate novel natural language
processing and bioinformatics applications, and in one case constitute the
basis of a task of the "BioNLP shared task 2013", an international
challenge on biomedical information extraction. The fifth case study shows
that the presented evaluation procedures are an effective means to check
and improve the quality of ontology alignments. Hence, they support the
crucial task of quality assurance of alignments, which are themselves
increasingly used as reference standards in evaluations of automatic
ontology alignment systems. Both, the presented life cycle model and the
ontologies and alignments that have resulted from its validation improve
information and knowledge management in biomedicine and thus promote
biomedical research