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About

About

João Correia Lopes is an Assistant Professor in Informatics Engineering at the Universidade do Porto and a senior researcher at INESC TEC.
He has graduated in Electrical Engineering in the University of Porto in 1984 and holds a PhD in Computing Science by Glasgow University in 1997.
His teaching includes undergraduate and graduate courses in databases and web applications, software engineering and programming, markup languages and semantic web.
He has been involved in research projects in the area of Data Management, Service-oriented architectures, e-health and e-Science.
Currently his main research interests are e-Health, e-Science and Research data management.

Interest
Topics
Details

Details

  • Name

    João Correia Lopes
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    19th June 1985
007
Publications

2019

The Perdigão: Peering into Microscale Details of Mountain Winds

Authors
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;

Publication
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

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

Publication
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

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.

2017

Enriching Mental Health Mobile Assessment and Intervention with Situation Awareness

Authors
Teles, AS; Rocha, A; da Silva e Silva, FJDE; Lopes, JC; O'Sullivan, D; Van de Ven, P; Endler, M;

Publication
SENSORS

Abstract
Current mobile devices allow the execution of sophisticated applications with the capacity for identifying the user situation, which can be helpful in treatments of mental disorders. In this paper, we present SituMan, a solution that provides situation awareness to MoodBuster, an ecological momentary assessment and intervention mobile application used to request self-assessments from patients in depression treatments. SituMan has a fuzzy inference engine to identify patient situations using context data gathered from the sensors embedded in mobile devices. Situations are specified jointly by the patient and mental health professional, and they can represent the patient's daily routine (e.g., "studying", "at work", "working out"). MoodBuster requests mental status self-assessments from patients at adequate moments using situation awareness. In addition, SituMan saves and displays patient situations in a summary, delivering them for consultation by mental health professionals. A first experimental evaluation was performed to assess the user satisfaction with the approaches to define and identify situations. This experiment showed that SituMan was well evaluated in both criteria. A second experiment was performed to assess the accuracy of the fuzzy engine to infer situations. Results from the second experiment showed that the fuzzy inference engine has a good accuracy to identify situations.

Supervised
thesis

2018

Desenvolvimento de Standard Operating Procedure para os testes em fábrica de armazéns automáticos

Author
Gil Miguel Mota Silva

Institution
UP-FEUP

2018

Redução de lead-time e aumento da produtividade na indústria de revestimentos de cortiça

Author
Raquel Dias Jesus

Institution
UP-FEUP

2018

Optimization of Sales Ordering Process – Development of a Customer Segmentation Model

Author
Ricardo Monteiro Marinho

Institution
UP-FEUP

2017

Implementation of a data virtualization layer applied to insurance data

Author
Catarina Raquel da Silva Teixeira

Institution
UP-FEUP

2017

Indicadores de Desempenho de Bases de Dados

Author
Eugenio Andre Leal Ferreira dos Santos

Institution
UP-FEUP