6 research outputs found
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
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