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Sobre
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Sobre

João Correia Lopes é Professor Auxiliar em Engenharia Informática na Universidade do Porto e investigador sénior do INESC TEC.
Formou-se em Engenharia Eletrotécnica e de Computadores na Universidade do Porto em 1984 e obteve doutoramento em Ciência da Computação pela Universidade de Glasgow em 1997.
Tem ensinado cursos de graduação e pós-graduação em bases de dados e aplicações web, engenharia de software e programação, linguagens de anotação e web semântica.
Esteve envolvido em projectos de investigação na área de Preservação a longo prazo, em Arquiteturas orientadas a serviços e em e-Ciência.
Atualmente, os seus principais interesses de investigação são a Gestão de dados de investigação, e-Saúde e as infra-estruturas para e-Ciência.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    João Correia Lopes
  • Cluster

    Informática
  • Cargo

    Investigador Sénior
  • Desde

    19 junho 1985
007
Publicações

2019

The Perdigão: Peering into Microscale Details of Mountain Winds

Autores
Fernando, HJS; Mann, J; Palma, JMLM; Lundquist, JK; Barthelmie, RJ; Belo Pereira, M; Brown, WOJ; Chow, FK; Gerz, T; Hocut, CM; Klein, PM; Leo, LS; Matos, JC; Oncley, SP; Pryor, SC; Bariteau, L; Bell, TM; Bodini, N; Carney, MB; Courtney, MS; Creegan, ED; Dimitrova, R; Gomes, S; Hagen, M; Hyde, JO; Kigle, S; Krishnamurthy, R; Lopes, JC; Mazzaro, L; Neher, JMT; Menke, R; Murphy, P; Oswald, L; Otarola Bustos, S; Pattantyus, AK; Veiga Rodrigues, CV; Schady, A; Sirin, N; Spuler, S; Svensson, E; Tomaszewski, J; Turner, DD; van Veen, L; Vasiljevic, N; Vassallo, D; Voss, S; Wildmann, N; Wang, Y;

Publicação
Bulletin of the American Meteorological Society

Abstract

2019

Ranking Dublin Core descriptor lists from user interactions: a case study with Dublin Core Terms using the Dendro platform

Autores
da Silva, JR; Ribeiro, C; Lopes, JC;

Publicação
International Journal on Digital Libraries

Abstract
Dublin Core descriptors capture metadata in most repositories, and this includes recent repositories dedicated to datasets. DC descriptors are generic and are being adapted to the requirements of different communities with the so-called Dublin Core Application Profiles that rely on the agreement within user communities, taking into account their evolving needs. In this paper, we propose an automated process to help curators and users discover the descriptors that best suit the needs of a specific research group in the task of describing and depositing datasets. Our approach is supported on Dendro, a prototype research data management platform, where an experimental method is used to rank and present DC Terms descriptors to the users based on their usage patterns. User interaction is recorded and used to score descriptors. In a controlled experiment, we gathered the interactions of two groups as they used Dendro to describe datasets from selected sources. One of the groups viewed descriptors according to the ranking, while the other had the same list of descriptors throughout the experiment. Preliminary results show that (1) some DC Terms are filled in more often than others, with different distribution in the two groups, (2) descriptors in higher ranks were increasingly accepted by users in detriment of manual selection, (3) users were satisfied with the performance of the platform, and (4) the quality of description was not hindered by descriptor ranking. © 2018 Springer-Verlag GmbH Germany, part of Springer Nature

2019

Empowering Distributed Analysis Across Federated Cohort Data Repositories Adhering to FAIR Principles

Autores
Rocha, A; Ornelas, JP; Lopes, JC; Camacho, R;

Publicação
ERCIM News

Abstract

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

2019

Web platform for monitoring fields trials

Autor
Pedro Daniel Viana Lima

Instituição
UP-FEUP

2019

Management of large volumes of data collected by wind monitoring sensors

Autor
Pedro Filipe Agrela Faria

Instituição
UP-FEUP

2018

Gestão Energética de Edifícios Complexos

Autor
João Manuel Neves Miranda

Instituição
UP-FEUP

2018

Acesso móvel a plataforma de e-Science para Séries temporais

Autor
Bruno Emanuel Cardoso Miranda Gonçalves

Instituição
UP-FEUP

2018

Using SensorThings API to enable a multi-platform IoT environment

Autor
José Alexandre Barreira Santos Teixeira

Instituição
UP-FEUP