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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

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.

2014

Ontology-Based Multi-Domain metadata for research data management using triple stores

Authors
Silva, JRD; Ribeiro, C; Lopes, JC;

Publication
ACM International Conference Proceeding Series

Abstract
Most current research data management solutions rely on a fixed set of descriptors (e.g. Dublin Core Terms) for the description of the resources that they manage. These are easy to understand and use, but their semantics are limited to general concepts, leaving out domain-specific metadata. The textual values for descriptors are easily indexed through free-text indexes, but faceted search and dataset interlinking becomes limited. From the point of view of the relational database schema modeler, designing a more flexible metadata model represents a non-trivial challenge because it means representing entities with attributes unknown at the time of modeling and that can change in time. Those traits, combined with the presence of hierarchies among the entities, can make the relational schema quite complex. This work demonstrates the approaches followed by current opensource platforms and proposes a graph-based model for achieving modular, ontology-based metadata for interlinked data assets in the Semantic Web. The proposed model was implemented in a collaborative research data management platform currently under development at the University of Porto. © 2014 ACM.

Supervised
thesis

2016

Usage-driven Application Profile Generation Using Ontologies

Author
João Miguel Rocha da Silva

Institution
UP-FEUP

2016

Platform for monitoring and treat depression

Author
José Pedro Alves Ornelas

Institution
UP-FCUP

2015

Suporte para séries temporais em plataforma e-Science

Author
José Tiago Paiva Antunes Magalhães

Institution
UP-FEUP

2015

Arquitetura Orientada a Componentes para uma Web Responsiva

Author
Rui Tiago Bugalho Monteiro

Institution
UP-FEUP

2015

Suporte para Séries Temporais em Plataforma e-Science

Author
José Tiago Paiva Antunes Magalhães

Institution
UP-FEUP