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About

I got a Ph.D. in Informatics, Artificial Intelligence branch, at Universidade Nova de Lisboa, 1994.

I am currently Associate Professor at the Informatics Engineering Department, Engineering Faculty of the University of Porto (FEUP), where I teach in the areas of databases, data warehouses, digital preservation and discrete mathematics.

I have participated in the creation of the joint Doctoral Program in Computer Science (MAP-i) of the Universities of Minho, Aveiro and Porto and I integrate its Scientific Committee since 2007. I participated in the creation of the Information Science Bachelor (2001) and Master (1997) Programs jointly taught by the Engineering and Humanities Faculties and I integrate the corresponding Scientific Committees.

I am a member of the Scientific Council of the Engineering Faculty since 2010.

I have led the development team of SIGARRA, the U.PORTO Academic Information System, from 1996 to 2010.

I am a Researcher at INESC TEC since 1985, integrating its Administration since 2015. My main research interests are in Information Management, Digital Preservation, and Databases. I have been the leader of the projects FCT DBPreserve on preservation of databases, Gulbenkian APDIC on digital preservation plans and EEA Grant SeaBioData. Currently, I integrate the project FCT TAIL on research data management.

I have collaborated between  2000 and 2010 in the project Cooperation with the National University of Timor Leste led by the Foundation of the Portuguese Universities, as coordinator of the Informatics Engineering bachelor (2006-2010).

I am a member of the Engineers Portugal association where I have belonged to the Board of Admission and Qualification from 2010 to 2016.

Interest
Topics
Details

Details

  • Name

    Gabriel David
  • Cluster

    Computer Science
  • Role

    Member of the Executive Board
  • Since

    01st April 1985
014
Publications

2021

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

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

Publication
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

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

Publication
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

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

Publication
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

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

Publication
TPDL

Abstract

2018

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

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

Publication
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.

Supervised
thesis

2021

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

Author
Verónica Fernanda dos Santos da Silva

Institution
UP-FEUP

2021

Validação de requisitos de um Sistema de Apoio à Decisão para gestão intermodal de transportes públicos

Author
João Manuel Bastos Mota

Institution
UP-FEUP

2021

Especificação de Requisitos num Módulo de Contratação Pública no iPortalDoc

Author
Pedro Daniel Sousa Dantas

Institution
UP-FEUP

2021

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

Author
Nelson Russo

Institution
UTAD

2021

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

Author
Gonçalo Alexandre Cruz Conde Matos

Institution
UTAD