Informática

URI Permanente desta comunidade

http://repositorio.ufes.br/handle/10/17625
Programa de Pós-Graduação em Informática

Centro: CT
Telefone: (27) 4009 2324 R*5126
URL do programa: http://www.informatica.ufes.br/pt-br/pos-graduacao/PPGI

Navegar

Navegando Informática por Autor "Almeida, Joao Paulo Andrade"

Agora exibindo 1 - 6 de 6
  • Nenhuma Miniatura disponível
    Item
    An Ontology Network to support Knowledge Representation and Semantic Interoperability in the HCI Domain
    (Universidade Federal do Espírito Santo, 2022-07-08) Costa, Simone Dornelas; Barcellos, Monalessa Perini; https://orcid.org/; http://lattes.cnpq.br/8826584877205264; https://orcid.org/; http://lattes.cnpq.br/; Almeida, Joao Paulo Andrade; https://orcid.org/; http://lattes.cnpq.br/4332944687727598; Zaina, Luciana Aparecida Martinez; https://orcid.org/; http://lattes.cnpq.br/; Pereira, Roberto; https://orcid.org/; http://lattes.cnpq.br/; Souza, Vitor Estevao Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577
    abstract
  • Nenhuma Miniatura disponível
    Item
    An Ontology-based Reference Model for the Software Systems Domain with a focus on Requirements Traceability
    (Universidade Federal do Espírito Santo, 2022-04-29) Duarte, Bruno Borlini; Souza, Vitor Estevao Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577; https://orcid.org/; http://lattes.cnpq.br/; Leite, Julio Cesar Sampaio do Prado; https://orcid.org/0000-0002-0355-0265; http://lattes.cnpq.br/6871006250321522; Almeida, Joao Paulo Andrade; https://orcid.org/0000-0002-9819-3781; http://lattes.cnpq.br/4332944687727598; Guerra, Eduardo Martins; https://orcid.org/; http://lattes.cnpq.br/3413978291577451; Barcellos, Monalessa Perini; http://lattes.cnpq.br/8826584877205264
    Software plays an essential role in modern society, as it has become indispensable in many aspects of our lives, such as social, business and even personal. Because of this importance, many researchers are dedicated to study the nature of software, how it is related to us and how it is able to change aspects in our society. It is accepted by the scientific community that software is a complex social artifact. This notion comes from the fact that a modern software system can be understood as the combination of interacting elements that exist inside a computer, such as programs and data, and in our world, such as sensors, other systems or even people, all of which are specifically organized to provide a set of functionalities or services and so, fulfill its purposes. A major concern in the development of modern complex software-based systems, is ensuring that the design of the system is capable of satisfying the current set of requirements. In this context, it is widely accepted in the scientific literature and in international standards that the requirements have an important role in the software process. Because of that, requirements need to be developed, refined, managed and traced to their origins, in a controlled engineering process, to control their changing nature and mitigate risks. In order to support these activities, we argue, based on the conceptual modeling scientific literature, that we can use ontologies to provide a better understanding of the software systems domain, reducing the inherent complexity and improving the requirements engineering process. In this work, we propose an ontology-based requirements traceability theory centered in different types of software systems requirements. Based on that, we developed the Reference Ontology of Software Systems (ROSS) and the Ontology of Software Defects Errors and Failures (OSDEF). ROSS and OSDEF are domain ontologies about the software systems that are intended to be used together and combined with other existing ontologies, as reference models for requirements traceability. Besides, we developed machine- readable operational ontologies, based on the reference versions of ROSS and OSDEF. The operational ontologies are created to support an ontology-based requirements traceability process that is based on the relationships that exist between the concepts in the ontologies.
  • Nenhuma Miniatura disponível
    Item
    Designing a network of reference ontologies for the integration of water quality data
    (Universidade Federal do Espírito Santo, 2019-10-21) Campos, Patricia Marcal Carnelli; Almeida, Joao Paulo Andrade; https://orcid.org/; http://lattes.cnpq.br/4332944687727598; https://orcid.org/0000-0002-9819-3781; http://lattes.cnpq.br/6719413307311916; Campos, Maria Luiza Machado; https://orcid.org/; http://lattes.cnpq.br/0659658820912418; Barcellos, Monalessa Perini; https://orcid.org/0000-0002-6225-9478 ; http://lattes.cnpq.br/8826584877205264
    Data semantic heterogeneity poses a significant challenge to integrated environmental data reuse. This challenge can be addressed with the use of ontologies that can provide a common semantic background for data interpretation, supporting meaning negotiation. However, there are some barriers to build ontologies for data integration in complex domains such as the environmental one. A relevant problem is the development of new ontologies disregarding previous knowledge resources such as reference models and vocabularies. To deal with this problem, in this work, we propose a systematic approach for the identification and selection of reusable knowledge resources for building ontologies with the purpose of scientific research data integration. The approach (dubbed CLeAR) follows some principles of the Systematic Literature Review, supporting the search for knowledge resources in the scientific literature. We apply the approach to the environmental domain, focusing on water quality. A total of 543 publications were surveyed. The results obtained provide a set of 75 knowledge resources for the environmental domain, evaluated according domain coverage and some quality attributes. In the case of water quality data, there is an ample spectrum of subject domains covered (including geographical features, spatial coordinates, environmental quality parameters, measurement activities, sampling activities, involved organizations, etc.). None of the knowledge resources on their own covers all aspects required to address the integration of water quality data. In addition, they are not always explicitly related, which makes them unsuitable for data integration in their current form. Because of this, in this work, we propose the design of a network of reference ontologies for the integration of water quality data, based on some of the identified knowledge resources. The proposed ontology network is grounded in the Unified Foundational Ontology (UFO), which provides basic notions of object, relation, property, event, and others necessary to model the environmental domain, besides allowing the analysis and adaptation of the concepts represented by different knowledge resources, in order to enable their integration into the ontology network.
  • Nenhuma Miniatura disponível
    Item
    EArly-OE: Atividades iniciais de engenharia de ontologias apoiadas em modelos de arquitetura organizacional
    (Universidade Federal do Espírito Santo, 2019-10-25) Detoni, Archimedes Alves; Almeida, Joao Paulo Andrade; https://orcid.org/0000-0002-9819-3781; http://lattes.cnpq.br/4332944687727598; https://orcid.org/0000-0002-5101-8628; http://lattes.cnpq.br/4411878611669387; Carvalho, Victorio Albani de; https://orcid.org/0000-0001-6024-0987; http://lattes.cnpq.br/6035323365313300; Souza, Vitor Estevao Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577; Amorim, Fernanda Araujo Baiao; https://orcid.org/0000-0001-7932-7134; http://lattes.cnpq.br/; Barcellos, Monalessa Perini; http://lattes.cnpq.br/8826584877205264
    Nowadays, public and private organizations are being encouraged to improve the computerized support to their activities. They intend to integrate their Information Systems (ISs) and to use heterogeneous data from different sources in order to produce relevant and reliable information mainly to support their decision activities. This challenge is intensified by the growing complexity of the organizational architectures, which: internally require the orchestration of the interaction between various administrative units, which must act integrated and collaboratively in distinct business processes that cross various functional areas; and externally need to operate seamlessly with other organizations. However, organizational ISs often do not support properly their business processes and are not able to interoperate with external systems. It occurs because those ISs, in many cases, were developed gradually and independently, each with its own scope, data structure, and terminology. Therefore, we can note gaps related to the lack of integration, information sharing and adoption of common semantics between organizational ISs. In such scenarios, the current literature has been indicating the use of ontologies as interlanguage in order to establish a consensual conceptualization to be adopted in a given domain. Thus, enabling interoperability between ISs and the integration of data dispersed over several sources and ISs. For an ontology to fit the purpose of being a conceptual model capable of adequately representing a domain, Ontology Engineering (OE) methods generally indicate the need to select and utilize knowledge resources available in the context of the domain to be modeled. The selected knowledge resources should facilitate the identification of relevant concepts and relationships that must be present in ontology, thereby aiding ontology engineers to understand the problem domain. Focusing on this need, the present work proposes the systematized use of Enterprise Architecture (EA) models as resources in OE knowledge acquisition activities, once they are artifacts that provide a broad view of the elements which compose organizational domains, in particular the actors, processes, ISs and their interrelationships. Besides, EA models have increasingly being used in organizational environments to diagnose and design interoperability solutions. The investigation of this possible synergy between the OE and EA disciplines was started in an exploratory research that addressed a real problem of semantic interoperability into public security domain, whereby EArly-OE approach was developed - Enterprise Architecture-driven Early Ontology Engineering). Early-OE prescribes guidelines for using EA models elements as knowledge resources to support initial OE activities in structured process-rich organizational domains, e.g. definition of intended uses, potential users and requirements of an ontology. After being developed in that exploratory research applied to the public security domain, the approach was evaluated in an empirical study addressing a different domain, that of federal public budget and finances, by a group of participants with varied degrees of experience in developing ontologies
  • Nenhuma Miniatura disponível
    Item
    GORO: uma ontologia sobre requisitos orientados a objetivos.
    (Universidade Federal do Espírito Santo, 2020-03-16) Bernabe, Cesar Henrique; Souza, Vitor Estevao Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577; https://orcid.org/; http://lattes.cnpq.br/; Almeida, Joao Paulo Andrade; https://orcid.org/; http://lattes.cnpq.br/4332944687727598; Goncalves, Enyo Jose Tavares; https://orcid.org/; http://lattes.cnpq.br/
    Correctly specifying requirements ensures that the right software is built to solve the right problem, and prevents errors that, if identified only in the development phase, can cost up to 90% more than if they were identified in earlier phases. Several a
  • Nenhuma Miniatura disponível
    Item
    Transforming ontology-based conceptual models into relational schemas
    (Universidade Federal do Espírito Santo, 2023-03-29) Guidoni, Gustavo Ludovico; Almeida, Joao Paulo Andrade; https://orcid.org/0000-0002-9819-3781; http://lattes.cnpq.br/4332944687727598; https://orcid.org/0009-0009-0932-4769; http://lattes.cnpq.br/6446725385317269; Souza, Vitor Estevao Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577; Campos, Maria Luiza Machado; Amorim, Fernanda Araujo Baião; https://orcid.org/0000-0001-7932-7134; http://lattes.cnpq.br/5068302552861597; Barcellos, Monalessa Perini; http://lattes.cnpq.br/8826584877205264
    Despite the relevant contributions of ontology-based conceptual modeling and the widespread use of relational schemas, the combination of these two technologies has not yet received due attention. Among the conceptual modeling technologies, OntoUML stands out as a language to describe a domain of interest, having as its main niche the formulation and propagation of knowledge. Conceptual models produced with OntoUML can be seen as a “starting point” for other artifacts, such as relational schemas in a database realization. To produce a relational schema from the conceptual model in an automated way, it is necessary to bridge the gap between a series of constructs. The current literature provides some object-relational transformation approaches that could, in principle, be applied to ontology-driven conceptual models, such as those produced in OntoUML. However, there are important constructs that are not covered by such approaches that must be addressed. Most of the existing object-relational transformation approaches fail to support conceptual models that: (i) include overlapping or incomplete generalizations; (ii) support dynamic classication; (iii) have multiple inheritance; and (iv) have orthogonal hierarchies. This is because many of the approaches discussed in the literature assume primitives underlying object-oriented programming languages (instead of conceptual modeling languages). To solve this gap, this work aims to understand the forces that govern classical strategies for transforming class hierarchies into relational schemas, while raising some ontological meta-properties that characterize the classes in these models (like sortality and rigidity). The information obtained is used to guide the transformation of the conceptual model into a relational schema in order to avoid some problems in existing approaches, leading to the novel one table per kind strategy. In addition to automating relational schema generation, we also propose an automated ontology-based data access mapping for the resulting relational schema, in order to provide access data in terms of the original conceptual model, and hence queries can be written at a high level of abstraction (in SPARQL), independently of the transformation strategy selected. Further, we forward engineer additional constraints along with the transformed schema (ultimately implemented as triggers) to guarantee that the semantics of the source model is respected. The proposed approach is contrasted with dominant transformation approaches in the literature from the perspectives of: (i) the supported conceptual modeling primitives; (ii) size of the resulting schema; (iii) query answering performance; and (iv) usability of the resulting schema, for which an empirical study is reported.