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Sobre
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Sobre

Sou Professora Associada no Departamento de Engenharia Informática da FEUP, Universidade do Porto, e investigadora senior do INESC TEC. Colaborei e fui responsável por projetos nas áreas do património cultural, bases de dados multimédia, recuperação de informação e otimização combinatória. Supervisionei 9 dissertações de doutoramento e 33 de mestrado. Fui responsável técnica do laboratório SAPO/U.Porto durante 5 anos. A minha atividade de ensino desenvolve-se na Engenharia Informática e na Ciência da Informação. A gestão de dados de investigação está no centro da minha atividade de investigação atual. Sou investigadora principal do projeto TAIL (FCT/POCI), que desenvolve ferramentas e métodos para a publicação de dados de investigação e responsável pelo piloto DataPublication@U.Porto da iniciativa europeia EUDAT. Sou membro do Grupo de Trabalho para a Política Nacional da Ciência Aberta da SECTES. Os meus interesses de investigação incluem a recuperação de informação, a preservação digital e a representação de conhecimento.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Cristina Ribeiro
  • Cluster

    Informática
  • Cargo

    Responsável de Área
  • Desde

    01 abril 1985
006
Publicações

2020

ArchOnto, a CIDOC-CRM-Based Linked Data Model for the Portuguese Archives

Autores
Koch, I; Ribeiro, C; Lopes, CT;

Publicação
Digital Libraries for Open Knowledge - Lecture Notes in Computer Science

Abstract

2019

Data Deposit in a CKAN Repository: A Dublin Core-Based Simplified Workflow

Autores
Karimova, Y; Castro, JA; Ribeiro, C;

Publicação
Communications in Computer and Information Science - Digital Libraries: Supporting Open Science

Abstract

2019

Interplay of Documents' Readability, Comprehension and Consumer Health Search Performance Across Query Terminology

Autores
Lopes, CT; Ribeiro, C;

Publicação
Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, CHIIR 2019, Glasgow, Scotland, UK, March 10-14, 2019

Abstract
Because of terminology mismatches, health consumers frequently face difficulties while searching the Web for health information. Difficulties arise in query formulation but also in understanding the retrieved documents. In this work we analyze how documents' readability affects users' comprehension and how both affect the retrieval performance, measured in different ways. In addition, we analyze how performance measures relate with each other. For this purpose we have conducted a laboratory user study with 40 participants. We found that readability is essential for a document to be at least partially relevant and that it becomes even more important if the document has medico-scientific terminology. Moreover, the relevance of a document to a specific user highly depends on its comprehension. In lay queries we found the medical accuracy of users' answers is related to the session's relevance assessments. This shows that users can, at least in part, relate their relevance assessments with the medical accuracy of the documents. On the other hand, this relationship does not exist with medico-scientific queries. © 2019 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery.

2019

Hands-On Data Publishing with Researchers: Five Experiments with Metadata in Multiple Domains

Autores
Rodrigues, J; Castro, JA; da Silva, JR; Ribeiro, C;

Publicação
Communications in Computer and Information Science

Abstract
The current requirements for open data in the EU are increasing the awareness of researchers with respect to data management and data publication. Metadata is essential in research data management, namely on data discovery and reuse. Current practices tend to either leave metadata definition to researchers, or to assign their creation to curators. The former typically results in ad-hoc descriptors, while the latter follows standards but lacks specificity. In this exploratory study, we adopt a researcher-curator collaborative approach in five data publication cases, involving researchers in data description and discussing the use of both generic and domain-oriented metadata. The study shows that researchers working on familiar datasets can contribute effectively to the definition of metadata models, in addition to the actual metadata creation. The cases also provide preliminary evidence of cross-disciplinary descriptor use. Moreover, the interaction with curators highlights the advantages of data management, making researchers more open to participate in the corresponding tasks. © Springer Nature Switzerland AG 2019.

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

Teses
supervisionadas

2019

Estudo de Mapeamento entre a ISAD/ISAAR e o Modelo CIDOC-CRM para a Descrição de Objetos Culturais da Torre do Tombo

Autor
Inês Dias Koch

Instituição
UP-FEUP

2019

Metadados para o uso de ferramentas de gestão de dados de investigação com investigadores do I3S

Autor
Marcelo da Costa Sampaio

Instituição
UP-FEUP

2019

Descrição de dados de investigação: requisitos de investigadores para modelos de metadados na Psicologia e Ciências da Educação

Autor
Laura Mafalda Carvalho Lopes

Instituição
UP-FEUP

2019

Engaging researchers in research data management: creating metadata models for multi-domain dataset description

Autor
João Daniel Aguiar de Castro

Instituição
UP-FEUP

2019

Application of the LabTablet app in a laboratory environment: Case study I3S

Autor
Ana Luís da Costa Ferreira

Instituição
UP-FEUP