16 research outputs found

    Ontological Representation of FAIR Principles: A Blueprint for FAIRer Data Sources

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    Guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of datasets, known as FAIR principles, were introduced in 2016 to enable machines to perform automatic actions on a variety of digital objects, including datasets. Since then, the principles have been widely adopted by data creators and users worldwide with the ‘FAIR’ acronym becoming a common part of the vocabulary of data scientists. However, there is still some controversy on how datasets should be interpreted since not all datasets that are claimed to be FAIR, necessarily follow the principles. In this research, we propose the OntoUML FAIR Principles Schema, as an ontological representation of FAIR principles for data practitioners. The work is based on OntoUML, an ontologically well-founded language for Ontology-driven Conceptual Modeling. OntoUML is a proxy for ontological analysis that has proven effective in supporting the explanation of complex domains. Our schema aims to disentangle the intricacies of the FAIR principles’ definition, by resolving aspects that are ambiguous, under-specified, recursively-specified, or implicit. The schema can be considered as a blueprint, or a template to follow when the FAIR classification strategy of a dataset must be designed. To demonstrate the usefulness of the schema, we present a practical example based on genomic data and discuss how the results provided by the OntoUML FAIR Principles Schema contribute to existing data guidelines

    Extending OntoUML Modelling Capabilities on the OpenPonk Platform

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    Tato práce se zaměřuje na rozšíření možností pro vytváření OntoUML modelů na platformě OpenPonk. Toto rozšíření je rozděleno do čtyř částí. Prvním rozšířením je grafické uživatelské rozhraní pro zobrazování výsledků verifikačního frameworku. Druhá část je prezenotvána novým frameworkem, sloužícím k automatické aktualizaci OunoUML verifikací. Třetím rozšířením je automatická detekce OntoUML anit-patternů. Poslední část se sestává z vybudování nové sekce portálu ontouml.org, obsahující dokumentaci k jednotlivým anti-patternům. V závěru práce je detekce anti-patternů demostrována na referenčním modelu.This work focuses on extending OntoUML modelling capabilities on the OpenPonk platform. This is done in four parts. First part of the expansion is graphical user interface for displaying results of the verification framework. Second part is represented by new framework, which is used for automatic updating of OntoUML verifications. Third part of the expansion is automatic detection of OntoUML anti-patterns. Last part consists of new section on portal ontouml.org, dedicated to anti-pattern documentation. End of this thesis focuses on demonstration of the anti-pattern detection using reference model

    JURI SAYS:An Automatic Judgement Prediction System for the European Court of Human Rights

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    In this paper we present the web platform JURI SAYS that automatically predicts decisions of the European Court of Human Rights based on communicated cases, which are published by the court early in the proceedings and are often available many years before the final decision is made. Our system therefore predicts future judgements of the court. The platform is available at jurisays.com and shows the predictions compared to the actual decisions of the court. It is automatically updated every month by including the prediction for the new cases. Additionally, the system highlights the sentences and paragraphs that are most important for the prediction (i.e. violation vs. no violation of human rights)

    On the symbiosis between conceptual modeling and ontology engineering : recommendation-based conceptual modeling

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    Within an enterprise, different conceptual models, such as process, data, and goal models, are created by various stakeholders. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they have a different focus, are represented using different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artefacts (such as documents, software, databases, etc.); therefore, they typically lack consistency and alignment. Another issue is that modelers have different vocabulary selections and different modeling styles. As a result, the enterprise can find itself accumulating a pile of models which cover similar aspects in different manners. Those models are not machine-readable and cannot be processed automatically. Enterprise-Specific Ontologies (ESOs) aim to solve this problem by serving as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models semantically aligned and facilitates model integration. However, managing those ontologies is complicated; an enterprise is an evolving entity, and as it changes, the ESO might become outdated. During the years of research dedicated to this dissertation, the Recommendation-Based Conceptual Modeling and Ontology Evolution (CMOE+) framework was developed. This framework establishes a symbiotic relationship between the Ontology engineering and the Conceptual modeling fields. CMOE+ consists of two cycles: the Ontology Evolution cycle and the Conceptual Modeling cycle. The Ontology Evolution cycle is responsible for setting up the initial version of the ESO and updating it as the knowledge within the enterprise evolves. Additionally, this cycle encapsulates recommendation services to perform ontology look-up and to present the most relevant ESO concepts in support of the modeler. The Conceptual Modeling cycle is responsible for the creation of conceptual models in different modeling languages based on the ESO. This cycle is also concerned with the quality evaluation of the created models. CMOE+ was developed based on requirements identified as a result of a literature review and a case study. The development process follows the Design Science Research Methodology (DSRM). After the initial version of CMOE+ was put forward, our focus was narrowed towards the recommendation-based conceptual modeling part of CMOE+, and we continued to gradually improve the framework in iterations until it reached its current state. The Ontology Evolution Cycle is not fully addressed within the scope of this dissertation. In order to demonstrate the performance and usability of CMOE+, it was exemplified for process modeling using BPMN and goal modeling using i*. This thesis presents a detailed instantiation, and explains steps to be performed in order to instantiate CMOE+ for other modeling languages. In order to evaluate the process modeling instance of CMOE+, a CMOE+BPMN tool was implemented. This tool incorporates a BPMN modeler, facilitates storage and access of the ESO, and includes all algorithms functioning within CMOE+ for the BPMN modeling language (as some of the algorithms are language dependent). Next, CMOE+ was exemplified using the i* goal modeling language. Finally, we demonstrated the ability of CMOE+ to perform alignment between i* and BPMN models, in order to show that CMOE+ is indeed beneficial in achieving interoperability among models created in different modeling languages and covering distinct aspects of the enterprise

    Representation of Multi-Level Domains on The Web

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    Estratégias de modelagem conceitual e representação de conhecimento frequentemente tratam entidades em dois níveis: um nível de classes e um nível de indivíduos que instanciam essas classes. Em vários domínios, porém, as próprias classes podem estar sujeitas a categorização, resultando em classes de classes (ou metaclasses). Ao representar estes domínios, é preciso capturar não apenas as entidades de diferentes níveis de classificação, mas também as suas relações (possivelmente complexas). No domínio de taxonomias biológicas, por exemplo, um dado organismo (por exemplo, o leão Cecil morto em 2015 no Parque Nacional Hwange no Zimbábue) é classificado em diversos táxons (como, por exemplo, Animal, Mamífero, Carnívoro, Leão), e cada um desses táxons é classificado por um ranking taxonômico (por exemplo, Reino, Classe, Ordem, Espécie). Assim, para representar o conhecimento referente a esse domínio, é necessário representar entidades em níveis diferentes de classificação. Por exemplo, Cecil é uma instância de Leão, que é uma instância de Espécie. Espécie, por sua vez, é uma instância de Ranking Taxonômico. Além disso, quando representamos esses domínios, é preciso capturar não somente as entidades diferentes níveis de classificação, mas também suas (possivelmente complicadas) relações. Por exemplo, nós gostaríamos de afirmar que instâncias do gênero Panthera também devem ser instâncias de exatamente uma instância de Espécie (por exemplo, Leão). A necessidade de suporte à representação de domínios que lidam com múltiplos níveis de classificação deu origem a uma área de investigação chamada modelagem multi-nível. Observa-se que a representação de modelos com múltiplos níveis é um desafio em linguagens atuais da Web Semântica, como há pouco apoio para orientar o modelador na produção correta de ontologias multi-nível, especialmente por causa das nuanças de restrições que se aplicam a entidades de diferentes níveis de classificação e suas relações. A fim de lidar com esses desafios de representação, definimos um vocabulário que pode ser usado como base para a definição de ontologias multi-nível em OWL, juntamente com restrições de integridade e regras de derivação. É oferecida uma ferramenta que recebe como entrada um modelo de domínio, verifica conformidade com as restrições de integridade propostas e produz como saída um modelo enriquecido com informações derivadas. Neste processo, é empregada uma teoria axiomática chamada MLT (uma Teoria de Modelagem Multi-Nível). O conteúdo da plataforma Wikidata foi utilizado para demonstrar que o vocabulário poderia evitar inconsistências na representação multi-nível em um cenário real

    Spatial ontologies for architectural heritage

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    Informatics and artificial intelligence have generated new requirements for digital archiving, information, and documentation. Semantic interoperability has become fundamental for the management and sharing of information. The constraints to data interpretation enable both database interoperability, for data and schemas sharing and reuse, and information retrieval in large datasets. Another challenging issue is the exploitation of automated reasoning possibilities. The solution is the use of domain ontologies as a reference for data modelling in information systems. The architectural heritage (AH) domain is considered in this thesis. The documentation in this field, particularly complex and multifaceted, is well-known to be critical for the preservation, knowledge, and promotion of the monuments. For these reasons, digital inventories, also exploiting standards and new semantic technologies, are developed by international organisations (Getty Institute, ONU, European Union). Geometric and geographic information is essential part of a monument. It is composed by a number of aspects (spatial, topological, and mereological relations; accuracy; multi-scale representation; time; etc.). Currently, geomatics permits the obtaining of very accurate and dense 3D models (possibly enriched with textures) and derived products, in both raster and vector format. Many standards were published for the geographic field or in the cultural heritage domain. However, the first ones are limited in the foreseen representation scales (the maximum is achieved by OGC CityGML), and the semantic values do not consider the full semantic richness of AH. The second ones (especially the core ontology CIDOC – CRM, the Conceptual Reference Model of the Documentation Commettee of the International Council of Museums) were employed to document museums’ objects. Even if it was recently extended to standing buildings and a spatial extension was included, the integration of complex 3D models has not yet been achieved. In this thesis, the aspects (especially spatial issues) to consider in the documentation of monuments are analysed. In the light of them, the OGC CityGML is extended for the management of AH complexity. An approach ‘from the landscape to the detail’ is used, for considering the monument in a wider system, which is essential for analysis and reasoning about such complex objects. An implementation test is conducted on a case study, preferring open source applications

    Uma linguagem para formalização de discursos com base em ontologias

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    Tese (doutorado)—Universidade de Brasília, Faculdade de Ciência da Informação, Programa de Pós-Graduação em Ciência da Informação, 2015.Esta pesquisa propõe a arquitetura da informação de uma linguagem formal textual para representar discursos sobre entidades ontológicas e obter deduções a respeito de ontologias de domínio. Por meio do paradigma de metamodelagem, a linguagem permite tratamento de ontologias heterogêneas que podem ser descritas como instâncias de uma ou mais ontologias de fundamentação. A linguagem suporta comportamentos clássicos e modais sustentados por noções de prova baseadas no paradigma de Programação em Lógica (Modal). O arcabouço modal desenvolvido possibilita que diferentes interpretações modais sejam introduzidas às especificações das ontologias, e contempla especialmente sistemas baseados em lógicas de múltiplos agentes. Uma sistematização do fragmento endurante da Unified Foundational Ontology (UFO) é realizada com objetivo de compor parte do marco teórico que fundamenta a proposta e de servir de exemplo de instanciação do arcabouço desenvolvido. Como resultados complementares, destacam-se: uma sistematização de um conjunto ampliado de regras para produção de modelos conceituais e um glossário detalhado de termos e conceitos da UFO-A; protótipos funcionais que implementam os sistemas elaborados; traduções das teorias descritas no arcabouço proposto para linguagens visuais, como extensões da representação gráfica da OntoUML; e discussões a respeito da integração de Arquitetura da Informação, Modelagem Conceitual e Programação em Lógica (Modal) no contexto social aplicado.This research proposes the information architecture of a textual formal language to represent and reason about ontological entities based on foundational ontologies. Through metamodeling, the language is able to deal with heterogeneous ontologies that can be described as instances of one or more foundational ontology. The language provides classic and modal inference mechanisms supported by proof notions based on the (Modal) Logic Programming paradigm. The modalities introduced by the modal framework allow a wide range of interpretations, including multi-agent systems. A systematization of the endurant fragment of the Unified Foundational Ontology (UFO) is produced in order to compose part of the theoretical framework underlying the proposal, and to serve as an example instantiating the developed framework. As complementary results we highlight: a systematization of an extended set of rules for conceptual modeling and a detailed glossary of terms and concepts of UFO-A; functional prototypes implementing the developed systems; translations of the theories described as instances of the framework to diagramatic representations, as extensions of the OntoUML visual language; and discussions regarding the integration of Information Architecture, Conceptual Modeling and Logic Programming within Applied Social Science
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