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Sobre

Sobre

Concluí o Doutoramento em Informática na Universidade Nova de Lisboa em 1994.

Sou atualmente Professor Associado do Departamento de Engenharia Informática da Faculdade de Engenharia da Universidade do Porto, onde leciono na área das bases de dados, armazéns de dados, preservação digital e matemática discreta.

Participei na criação do Programa de Doutoramento em Informática (MAP-i) conjunto das Universidades do Minho, Aveiro e Porto, fazendo parte da Comissão Científica desde 2007. Participei na criação do Mestrado em Gestão da Informação (1997) e da Licenciatura em Ciência da Informação (2001), programas conjuntos das Faculdades de Engenharia e de Letras, e integro as respetivas comissões científicas.

Sou membro do Conselho Científico da Faculdade de Engenharia desde 2010.

Dirigi a equipa de desenvolvimento do SIGARRA (sistema de informação académico da UPorto) entre 1996 e 2010.

Sou investigador do INESC TEC desde 1985, fazendo parte da sua Administração desde 2015. Os meus principais interesses de investigação são nas áreas da gestão de informação, da preservação digital e das bases de dados. Coordenei os projetos FCT DBPreserve, sobre preservação de bases de dados; Gulbenkian APDIC, sobre planos de preservação digital, e EEA Grant SeaBioData. Atualmente integro o projeto FCT TAIL, sobre gestão de dados de investigação.

Participei entre 2000 e 2010 no projeto de Cooperação com a Universidade Nacional de Timor Leste, tendo sido o coordenador do curso de Engenharia Informática entre 2006 e 2010.

Sou membro da Ordem dos Engenheiros onde integrei o Conselho de Admissão e Qualificação, entre 2010 e 2016.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Gabriel David
  • Cluster

    Informática
  • Cargo

    Administrador Executivo
  • Desde

    01 abril 1985
014
Publicações

2021

Institutional support for data management plans: case studies for a systematic approach

Autores
Karimova, Y; Ribeiro, C; David, G;

Publicação
Int. J. Metadata Semant. Ontologies

Abstract
Researchers have to ensure that their projects comply with Research Data Management (RDM) requirements. Consequently, the main funding agencies require Data Management Plans (DMPs) for grant applications. So, institutions are investing in RDM tools and implementing RDM workflows in order to support their researchers. In this context, we propose a collaborative DMP-building method that involves researchers, data stewards and other parties if required. This method was applied as part of an RDM workflow in research groups across several scientific domains. We describe it as a systematic approach and illustrate it through a set of case studies. We also address the DMP monitoring process during the life cycle of projects. The feedback from the researchers highlighted the advantages of creating DMPs and their growing need. So, there is motivation to improve the DMP support process according to the machine-actionable DMPs concept and to the best practices in each scientific community. © 2021 Inderscience Enterprises Ltd.. All rights reserved.

2020

Institutional Support for Data Management Plans: Five Case Studies

Autores
Karimova, Y; Ribeiro, C; David, G;

Publicação
Metadata and Semantic Research - 14th International Conference, MTSR 2020, Madrid, Spain, December 2-4, 2020, Revised Selected Papers

Abstract

2019

Planning and managing data for Smart Cities: An application profile for the UrbanSense project

Autores
Dias, P; Rodrigues, J; Aguiar, A; David, G;

Publicação
2018 IEEE International Smart Cities Conference, ISC2 2018

Abstract
Aiming to improve sustainability and life quality, urban space research is prompting an intensive use of communication and information technologies. With it, researchers are also facing more challenges regarding research data management and therefore seeking clear guidelines and tools for proper data organization, sharing and reuse. In the context of a smart cities research project, UrbanSense, held in the city of Porto, we proposed a data management plan, to support researchers from the moment they start to collect data up to the point of data publication. We also developed an ontology for the description of smart cities data, validated by UrbanSense researchers. Descriptions based on this ontology were evaluated by external parties, after the data was published in an institutional data repository. © 2018 IEEE.

2018

Digital Libraries for Open Knowledge, 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, Porto, Portugal, September 10-13, 2018, Proceedings

Autores
Méndez, E; Crestani, F; Ribeiro, C; David, G; Lopes, JC;

Publicação
TPDL

Abstract

2018

Research Data Management Tools and Workflows: Experimental Work at the University of Porto

Autores
Ribeiro, C; Rocha da Silva, J; Aguiar Castro, J; Carvalho Amorim, R; Correia Lopes, J; David, G;

Publicação
IASSIST Quarterly

Abstract
Research datasets include all kinds of objects, from web pages to sensor data, and originate in every domain. Concerns with data generated in large projects and well-funded research areas are centered on their exploration and analysis. For data in the long tail, the main issues are still how to get data visible, satisfactorily described, preserved, and searchable. Our work aims to promote data publication in research institutions, considering that researchers are the core stakeholders and need straightforward workflows, and that multi-disciplinary tools can be designed and adapted to specific areas with a reasonable effort. For small groups with interesting datasets but not much time or funding for data curation, we have to focus on engaging researchers in the process of preparing data for publication, while providing them with measurable outputs. In larger groups, solutions have to be customized to satisfy the requirements of more specific research contexts. We describe our experience at the University of Porto in two lines of enquiry. For the work with long-tail groups we propose general-purpose tools for data description and the interface to multi-disciplinary data repositories. For areas with larger projects and more specific requirements, namely wind infrastructure, sensor data from concrete structures and marine data, we define specialized workflows. In both cases, we present a preliminary evaluation of results and an estimate of the kind of effort required to keep the proposed infrastructures running.  The tools available to researchers can be decisive for their commitment. We focus on data preparation, namely on dataset organization and metadata creation. For groups in the long tail, we propose Dendro, an open-source research data management platform, and explore automatic metadata creation with LabTablet, an electronic laboratory notebook. For groups demanding a domain-specific approach, our analysis has resulted in the development of models and applications to organize the data and support some of their use cases. Overall, we have adopted ontologies for metadata modeling, keeping in sight metadata dissemination as Linked Open Data.

Teses
supervisionadas

2021

Especificação de Requisitos num Módulo de Contratação Pública no iPortalDoc

Autor
Pedro Daniel Sousa Dantas

Instituição
UP-FEUP

2021

Framework para definição da Continuidade de Negócio - Avaliação Multidisciplinar da Maturidade Organizacional

Autor
Nelson Russo

Instituição
UTAD

2021

Práticas emergentes e modelos de maturidade na adoção institucional do e-learning no ensino superior

Autor
Gonçalo Alexandre Cruz Conde Matos

Instituição
UTAD

2021

ADVANCED PERSISTENT THREATS - ATRIBUIÇÃO

Autor
Pedro Brandão

Instituição
UTAD

2021

Como selecionar produtos de aquacultura - Especificação de uma interface para apoiar no ato da compra

Autor
Verónica Fernanda dos Santos da Silva

Instituição
UP-FEUP