Final results of the Ontology Alignment Evaluation Initiative 2011

euzenat2011dInternational audienceOntology matching consists of finding correspondences between entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from simple directories to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2011 builds over previous campaigns by having 4 tracks with 6 test cases followed by 18 participants. Since 2010, the campaign introduces a new evaluation modality in association with the SEALS project. A subset of OAEI test cases is included in this new modality which provides more automation to the evaluation and more direct feedback to the participants. This paper is an overall presentation of the OAEI 2011 campaign

Automated extension of biomedical ontologies

Developing and extending a biomedical ontology is a very demanding process, particularly because biomedical knowledge is diverse, complex and continuously changing and growing. Existing automated and semi-automated techniques are not tailored to handling the issues in extending biomedical ontologies. This thesis advances the state of the art in semi-automated ontology extension by presenting a framework as well as methods and methodologies for automating ontology extension specifically designed to address the features of biomedical ontologies.The overall strategy is based on first predicting the areas of the ontology that are in need of extension and then applying ontology learning and ontology matching techniques to extend them. A novel machine learning approach for predicting these areas based on features of past ontology versions was developed and successfully applied to the Gene Ontology. Methods and techniques were also specifically designed for matching biomedical ontologies and retrieving relevant biomedical concepts from text, which were shown to be successful in several applications.O desenvolvimento e extensão de uma ontologia biomédica é um processo muito exigente, dada a diversidade, complexidade e crescimento contínuo do conhecimento biomédico. As técnicas existentes nesta área não estão preparadas para lidar com os desafios da extensão de uma ontologia biomédica. Esta tese avança o estado da arte na extensão semi-automática de ontologias, apresentando uma framework assim como métodos e metodologias para a automação da extensão de ontologias especificamente desenhados tendo em conta as características das ontologias biomédicas. A estratégia global é baseada em primeiro prever quais as áreas da ontologia que necessitam extensão, e depois usá-las como enfoque para técnicas de alinhamento e aprendizagem de ontologias, com o objectivo de as estender. Uma nova estratégia de aprendizagem automática para prever estas áreas baseada em atributos de antigas versões de ontologias foi desenvolvida e testada com sucesso na Gene Ontology. Foram também especificamente desenvolvidos métodos e técnicas para o alinhamento de ontologias biomédicas e extracção de conceitos relevantes de texto, cujo sucesso foi demonstrado em várias aplicações.Fundação para a Ciência e a Tecnologi

Visualization for biomedical ontologies alignment

Tese de mestrado, Bioinformática e Biologia Computacional (Bioinformática), Universidade de Lisboa, Faculdade de Ciências, 2016Desde o início do século, a investigação biomédica e a prática clínica levaram a uma acumulação de grandes quantidades de informação, por exemplo, os dados resultantes da sequenciação genómica ou os registos médicos. As ontologias fornecem um modelo estruturado com o intuito de representar o conhecimento e têm sido bem sucedidas no domínio biomédico na melhoria da interoperabilidade e partilha. O desenvolvimento desconectado das ontologias biomédicas levou à criação de modelos que apresentam domínios idênticos ou sobrepostos. As técnicas de emparelhamento de ontologias foram desenvolvidas afim de estabelecer ligações significativas entre as classes das ontologias, por outras palavras, para criar alinhamentos. Para alcançar um alinhamento ótimo é, não só importante melhorar as técnicas de emparelhamentos mas também criar as ferramentas necessárias para que possa existir intervenção humana, particularmente na visualização. Apesar da importância da intervenção de utilizadores e da visualização no emparelhamento de ontologias, poucos sistemas o suportam, sobretudo para grandes e complexas ontologias como as do domínio biomédico, concretamente no contexto da revisão de alinhamentos e interpretação de incoerências lógicas. O objetivo central desta tese consistiu na investigação dos principais paradigmas de visualização de ontologias, no contexto do alinhamento de ontologias biomédicas, e desenvolver abordagens de visualização e interação que vão de encontro a estes desafios. O trabalho desenvolvido levou, então, à criação de um novo módulo de visualização para um sistema de emparelhamento do state of the art que suporta a revisão de alinhamentos, e à construção de uma ferramenta online que visa ajudar o utilizador a compreender os conflitos encontrados nos alinhamentos, ambos baseados numa abordagem de visualização de subgrafos. Ambas as contribuições foram avaliadas em pequena escala, por testes a utilizadores que revelaram a relevância da visualização de subgrafos contra a visualização em árvore, mais comum no domínio biomédico.Since the begin of the century, biomedical research and clinical practice have resulted in the accumulation of very large amounts of information, e.g. data from genomic sequencing or medical records. Ontologies provide a structured model to represent knowledge and have been quite successful in the biomedical domain at improving interoperability and sharing. The disconnected development of biomedical ontologies has led to the creation of models that have overlapping or even equal domains. Ontology matching techniques were developed to establish meaningful connections between classes of the ontologies, in other words to create alignments. In order to achieve an optimal alignment, it is not only important to improve the matching techniques but also to create the necessary tools for human intervention, namely in visualization. Despite the importance of user intervention and visualization in ontology matching, few systems support these, especially for large and complex ontologies such as those in the biomedical domain, specifically in the context of the alignment revision and logical incoherence explanation. The central objective of this thesis was to investigate the main ontology visualization paradigms, in the context of biomedical ontology matching, and to develop visualization and interaction approaches addressing those challenges. The work developed lead to the creation of a new visualization module for a state of the art ontology matching system, that supports the alignment review, and to the construction of an online tool that aims to help the user understand the conflicts found in the alignments both based on a subgraph visualization approach. Both contributions were evaluated, in a small-scale, by user tests that revealed the relevance of subgraph visualization versus the more common tree visualization for the biomedical domain

Ontology matching: state of the art and future challenges

shvaiko2013aInternational audienceAfter years of research on ontology matching, it is reasonable to consider several questions: is the field of ontology matching still making progress? Is this progress significant enough to pursue some further research? If so, what are the particularly promising directions? To answer these questions, we review the state of the art of ontology matching and analyze the results of recent ontology matching evaluations. These results show a measurable improvement in the field, the speed of which is albeit slowing down. We conjecture that significant improvements can be obtained only by addressing important challenges for ontology matching. We present such challenges with insights on how to approach them, thereby aiming to direct research into the most promising tracks and to facilitate the progress of the field

Results of the second evaluation of matching tools

meilicke2012bThis deliverable reports on the results of the second SEALS evaluation campaign (for WP12 it is the third evaluation campaign), which has been carried out in coordination with the OAEI 2011.5 campaign. Opposed to OAEI 2010 and 2011 the full set of OAEI tracks has been executed with the help of SEALS technology. 19 systems have participated and five data sets have been used. Two of these data sets are new and have not been used in previous OAEI campaigns. In this deliverable we report on the data sets used in the campaign, the execution of the campaign, and we present and discuss the evaluation results

Proceedings of The Tenth International Workshop on Ontology Matching (OM-2015)

shvaiko2016aInternational audienceno abstrac

The state of semantic technology today - overview of the first SEALS evaluation campaigns

This paper describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning tools, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions

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

Ontology Alignment using Biologically-inspired Optimisation Algorithms

It is investigated how biologically-inspired optimisation methods can be used to compute alignments between ontologies. Independent of particular similarity metrics, the developed techniques demonstrate anytime behaviour and high scalability. Due to the inherent parallelisability of these population-based algorithms it is possible to exploit dynamically scalable cloud infrastructures - a step towards the provisioning of Alignment-as-a-Service solutions for future semantic applications