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About

About

  • Investigador do CESE - Centro de Engenharia de Sistemas Empresariais, do INESC TEC e Professor Adjunto no Instituto Politécnico do Porto;
  • Doutorado em Engenharia Informática pela Faculdade de Engenharia da Universidade do Porto;
  • A área de especialização foca problemas relacionados com a organização de informação em ambiente colaborativos (redes colaborativas) e a representação de conhecimento de domínio de forma partihada;
  • Participação em vários projetos nacionais e internacionais;
  • Com publicações científicas em atas de conferências e revistas;
  • Os interesses de investigação focam-se no estudo de: 1) métodos e teorias para agilizar a gestão de informação e partilha de conhecimento; 2) mecanismos de representação colaborativa de conhecimento; 3) princípios da semiótica cognitiva na construção de modelos pra estrutturação, organização de informação e visualização de informação em contextos industriais.

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Details

Details

  • Name

    Cristovão Sousa
  • Since

    17th September 2001
004
Publications

2024

Industrial Data Sharing Ecosystems: An Innovative Value Chain Traceability Platform Based in Data Spaces

Authors
Freitas, J; Sousa, C; Pereira, C; Pinto, P; Ferreira, R; Diogo, R;

Publication
GOOD PRACTICES AND NEW PERSPECTIVES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 3, WORLDCIST 2024

Abstract
Considering the great challenge of implementing digital tools to improve collaboration in the value chain and promote the adoption of circularity strategies, as is the case with digital traceability tools and digital product passports. This paper presents an innovative proposal for implementing an industrial data sharing ecosystem, namely an architecture and platform for digital traceability between entities based on Data Spaces. To validate our proposal, a use case scenario was implemented as part of the BioShoes4All project.

2024

Towards a KOS to Manage and Retrieve Legal Data

Authors
Oliveira, B; Sousa, C;

Publication
INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2, WORLDCIST 2023

Abstract
Legislation is a technical domain characterized by highly specialized knowledge forming a large corpus where content is interdependent in nature, but the context is poorly formalized. Typically, the legal domain involves several document types that can be related. Amendments, past judicial interpretations, or new laws can refer to other legal documents to contextualize or support legal formulation. Lengthy and complex texts are frequently unstructured or in some cases semi-structured. Therefore, several problems arise since legal documents, articles, or specific constraints can be cited and referenced differently. Based on legal annotations from a real-world scenario, an architectural approach for modeling a Knowledge Organization System for classifying legal documents and the related legal objects is presented. Data is summarized and classified using a topic modeling approach, with a view toward the improvement of browsing and retrieval of main legal topics and associated terms.

2023

Data spaces based approach for B2B data exchange: A footwear industry case

Authors
Pinto P.; Sousa C.; Cardeiro C.;

Publication
Procedia Computer Science

Abstract
This paper discusses the problem of information sharing and data interoperability in a B2B context. Therefore, this paper presents a case study on the scope of data-sharing in collaborative networks in an industrial cluster. It explores the feasibility of International Data Spaces in the context of the footwear industry cluster. This work also discusses how the adoption of digital processes might contribute to support data-based management to optimize the production planning of a footwear industry. As a result, it is defined and specified the foundations for the development and implementation of an dataspace oriented IIoT architecture, following a fully compliant Industry 4.0 solution for the footwear industry cluster. This paper discusses the problem of information sharing and data interoperability in a B2B context. Therefore, this paper presents a case study on the scope of data-sharing in collaborative networks in an industrial cluster. It explores the feasibility of International Data Spaces in the context of the footwear industry cluster. This work also discusses how the adoption of digital processes might contribute to support data-based management to optimize the production planning of a footwear industry. As a result, it is defined and specified the foundations for the development and implementation of an dataspace oriented IIoT architecture, following a fully compliant Industry 4.0 solution for the footwear industry cluster.

2023

IoT Data Ness: From Streaming to Added Value

Authors
Correia, R; Sousa, C; Carneiro, D;

Publication
Lecture Notes in Networks and Systems

Abstract

2022

Knowledge-based decision intelligence in street lighting management

Authors
Sousa, C; Teixeira, D; Carneiro, D; Nunes, D; Novais, P;

Publication
INTEGRATED COMPUTER-AIDED ENGINEERING

Abstract
As the availability of computational power and communication technologies increases, Humans and systems are able to tackle increasingly challenging decision problems. Taking decisions over incomplete visions of a situation is particularly challenging and calls for a set of intertwined skills that must be put into place under a clear rationale. This work addresses how to deliver autonomous decisions for the management of a public street lighting network, to optimize energy consumption without compromising light quality patterns. Our approach is grounded in an holistic methodology, combining semantic and Artificial Intelligence principles to define methods and artefacts for supporting decisions to be taken in the context of an incomplete domain. That is, a domain with absence of data and of explicit domain assertions.