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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
002
Publications

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

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.

2016

Towards Situation-aware Mobile Applications in Mental Health

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

Publication
2016 IEEE 29TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS)

Abstract
This work describes SituMan (Situation Manager), a mobile system that makes use of the sensors commonly included in most mobile platforms and a fuzzy inference engine to attempt to infer user context and environment. Such "situation" information, has been used to enhance the behaviour of MoodBuster, another mobile application used in the scope of the mental health domain to collect Ecological Momentary Assessments (EMA). EMA has been used in psychotherapy to minimize the effects of recall bias in the assessment of patient mood, as well as in the recollection of other experiences and behaviours. SituMan can enhance the user experience in the scope of EMA by prompting users in the desired situation, instead of at random or fixed-times, thus reducing obtrusiveness. It can also provide new insight to mental health professionals by summarizing the situations experienced by the patient, further allowing correlation of situation information with patient mood within the same time frame.

2016

Usage-Driven Dublin Core Descriptor Selection A Case Study Using the Dendro Platform for Research Dataset Description

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

Publication
RESEARCH AND ADVANCED TECHNOLOGY FOR DIGITAL LIBRARIES, TPDL 2016

Abstract
Dublin Core schemas are the core metadata models of most repositories, and this includes recent repositories dedicated to datasets. DC descriptors are generic and are being adapted to the needs of different communities with the so-called Dublin Core Application Profiles. DCAPs rely on the agreement within user communities, in a process mainly driven by their evolving needs. In this paper, we propose a complementary automated process, designed to help curators and users discover the descriptors that better suit the needs of a specific research group. We target the description of datasets, and test our approach using 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. 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 had descriptor ranking on, while the other had the same list of descriptors throughout the whole experiment. Preliminary results show that 1. some DC Terms are filled in more often than others, with different distribution in the two groups, 2. selected descriptors were increasingly accepted by users in detriment of manual selection and 3. users were satisfied with the performance of the platform, as demonstrated by a post-study survey.

2014

Dendro: Collaborative Research Data Management Built on Linked Open Data

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

Publication
SEMANTIC WEB: ESWC 2014 SATELLITE EVENTS

Abstract
Research datasets in the so-called "long-tail of science" are easily lost after their primary use. Support for preservation, if available, is hard to fit in the research agenda. Our previous work has provided evidence that dataset creators are motivated to spend time on data description, especially if this also facilitates data exchange within a group or a project. This activity should take place early in the data generation process, when it can be regarded as an actual part of data creation. We present the first prototype of the Dendro platform, designed to help researchers use concepts from domain-specific ontologies to collaboratively describe and share datasets within their groups. Unlike existing solutions, ontologies are used at the core of the data storage and querying layer, enabling users to establish meaningful domain-specific links between data, for any domain. The platform is currently being tested with research groups from the University of Porto.

Supervised
thesis

2017

Indicadores de Desempenho de Bases de Dados

Author
Eugenio Andre Leal Ferreira dos Santos

Institution
UP-FEUP

2017

YWeb – Plataforma de Criação de Templates para Marketing Online

Author
José Carlos Calhau Pinto

Institution
UP-FEUP

2017

Sistema de apoio à decisão suportado por armazém de dados na logística da cadeia de abastecimento

Author
Pedro Emanuel Caldas Ferreira

Institution
UP-FEUP

2017

Implementation of a data virtualization layer applied to insurance data

Author
Catarina Raquel da Silva Teixeira

Institution
UP-FEUP

2016

Usage-driven Application Profile Generation Using Ontologies

Author
João Miguel Rocha da Silva

Institution
UP-FEUP