Towards valid and reusable reference alignments — ten basic quality checks for ontology alignments and their application to three different reference data sets

Identifying relationships between hitherto unrelated entities in different ontologies is the key task of ontology alignment. An alignment is either manually created by domain experts or automatically by an alignment system. In recent years, several alignment systems have been made available, each using its own set of methods for relation detection. To evaluate and compare these systems, typically a manually created alignment is used, the so-called reference alignment. Based on our experience with several of these reference alignments we derived requirements and translated them into simple quality checks to ensure the alignments’ validity and also their reusability. In this article, these quality checks are applied to a standard reference alignment in the biomedical domain, the Ontology Alignment Evaluation Initiative Anatomy track reference alignment, and two more recent data sets covering multiple domains, including but not restricted to anatomy and biology

OMT, an Ontology Matching System

Dissertação de mestrado integrado em Informatics EngineeringIn recent years ontologies have become an integral part of storing information in a structured and formal manner and a way of sharing said information. With this rise in usage, it was only a matter of time before different people tried to use ontologies to represent the same knowledge domain. The area of Ontology Matching was created with the purpose of finding correspondences between different ontologies that represented information in the same domain area. This document reports a Master’s work that started with the study of already existing ontology matching techniques and tools in order to gain knowledge on what techniques exist, as well as understand the advantages and disadvantages of each one. Using the knowledge obtained from the study of the bibliography research, a new web-based tool called OMT was created to automatically merge two given ontologies. The OMT tool processes ontologies written in different ontology representation languages, such as the OWL family or any language written according to the RDF web standards. The OMT tool provides the user with basic information about the submitted ontologies and after the matching occurs, provides the user with a simplified version of the results focusing on the number of objects that were matched and merged. The user can also download a Log File, if he so chooses. This Log File contains a detailed description of the matching process and the reasoning behind the decisions the OMT tool made. The OMT tool was tested throughout its development phase against various different potential inputs to assess its accuracy. Lastly, a web application was developed to host the OMT tool in order to facilitate the access and use of the tool for the users.Nos últimos tempos, ontologias têm-se tornado fundamentais quando os objetivos são armazenar informação de forma formal e estruturada bem como a partilha de tal informação. Com o aumento da procura e utilização de ontologias, tornou-se inevitável que indivíduos diferentes criassem ontologias para representar o mesmo domínio de informação. A área de concordância de ontologias foi criada com o intuito de encontrar correspondências entre ontologias que representem informação no mesmo domínio. Este documento reporta o trabalho de uma tese de Mestrado que começou pelo estudo de técnicas e ferramentas já existentes na área de concordância de ontologias com o objetivo de obter conhecimento nestas mesmas e perceber as suas vantagens e desvantagens. A partir do conhecimento obtido a partir deste estudo, uma nova ferramenta web chamada OMT foi criada para automaticamente alinhar duas ontologias. A ferramenta OMT processa ontologias escritas em diferentes linguagens de representação, tal como a familia de linguages OWL ou qualquer linguagem que respeite o padrão RDF. A ferramenta OMT fornece ao utilizador informação básica sobre as ontologias e após o alinhamento ocorrer, fornece ao utilizador uma versão simplificada dos resultados obtidos, focando no numero de objetos que foram alinhados. O utilizador pode também descarregar um ficheiro Log. Este ficheiro contém uma descrição destalhada do processo de alinhamento e a justificação para as diferentes decisões tomadas pelo ferramenta OMT. A ferramenta OMT foi testada durante todo o processo de desenvolvimento com diferentes tipos de ontologia de entrada para avaliar a sua capacidade de alinhamento. Por último, foi também desenvolvida uma aplicação web para hospedar a ferramenta OMT de forma a facilitar o acesso e uso da ferramenta aos utilizadores

Results of the Ontology Alignment Evaluation Initiative 2007

euzenat2007gInternational audienceWe present the Ontology Alignment Evaluation Initiative 2007 campaign as well as its results. The OAEI campaign aims at comparing ontology matching systems on precisely defined test sets. OAEI-2007 builds over previous campaigns by having 4 tracks with 7 test sets followed by 17 participants. This is a major increase in the number of participants compared to the previous years. Also, the evaluation results demonstrate that more participants are at the forefront. The final and official results of the campaign are those published on the OAEI web site

Evaluating Ontology-Alignment Techniques

Schreiber, A.T. [Promotor

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

Converting and Integrating Vocabularies for the Semantic Web

Schreiber, A.T. [Promotor]Ossenbruggen, J.R. van [Copromotor