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About

About

I am an Associate Professor with the Department of Informatics Engineering of FEUP, University of Porto, and a senior researcher at INESC TEC. I have collaborated on and been in charge of projects in the areas of cultural heritage, multimedia databases, information retrieval and combinatorial optimisation. I have supervised 9 PhD and 33 MSc dissertations. I was the technical leader of the SAPO/U.Porto extension laboratory for 5 years. My teaching activities include courses in the Informatics Engineering and Information Science programmes. Research Data Management is the core of my current research activity. I am the PI of TAIL (FCT/POCI), on research data management workflows for data publication, and I lead the DataPublication@U.Porto pilot in the EUDAT european initiative. I am a member of the Working Group for the National Policy on Open Science with SECTES. My research interests include information retrieval, digital preservation and knowledge representation.

Interest
Topics
Details

Details

  • Name

    Cristina Ribeiro
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st April 1985
007
Publications

2023

Getting in touch with metadata: a DDI subset for FAIR metadata production in clinical psychology

Authors
Castro, JA; Rodrigues, J; Mena Matos, P; M D Sales, C; Ribeiro, C;

Publication
IASSIST Quarterly

Abstract
To address metadata with researchers it is important to use models that include familiar domain concepts. In the Social Sciences, the DDI is a well-accepted source of such domain concepts. To create FAIR data and metadata, we need to establish a compact set of DDI elements that fit the requirements in projects and are likely to be adopted by researchers inexperienced with metadata creation. Over time, we have engaged in interviews and data description sessions with research groups in the Social Sciences, identifying a manageable DDI subset. A recent Clinical Psychology project, TOGETHER, dealing with risk assessment for hereditary cancer, considered the inclusion of a DDI subset for the production of metadata that are timely and interoperable with data publication initiatives in the same domain. Taking a DDI subset identified by the data curators, we make a preliminary assessment of its use as a realistic effort on the part of researchers, taking into consideration the metadata created in two data description sessions, the effort involved, and overall metadata quality. A follow-up questionnaire was used to assess the perspectives of researchers regarding data description.

2022

Deep Aesthetic Assessment and Retrieval of Breast Cancer Treatment Outcomes

Authors
Silva, W; Carvalho, M; Mavioso, C; Cardoso, MJ; Cardoso, JS;

Publication
PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2022)

Abstract
Treatments for breast cancer have continued to evolve and improve in recent years, resulting in a substantial increase in survival rates, with approximately 80% of patients having a 10-year survival period. Given the serious that impact breast cancer treatments can have on a patient's body image, consequently affecting her self-confidence and sexual and intimate relationships, it is paramount to ensure that women receive the treatment that optimizes both survival and aesthetic outcomes. Currently, there is no gold standard for evaluating the aesthetic outcome of breast cancer treatment. In addition, there is no standard way to show patients the potential outcome of surgery. The presentation of similar cases from the past would be extremely important to manage women's expectations of the possible outcome. In this work, we propose a deep neural network to perform the aesthetic evaluation. As a proof-of-concept, we focus on a binary aesthetic evaluation. Besides its use for classification, this deep neural network can also be used to find the most similar past cases by searching for nearest neighbours in the high-semantic space before classification. We performed the experiments on a dataset consisting of 143 photos of women after conservative treatment for breast cancer. The results for accuracy and balanced accuracy showed the superior performance of our proposed model compared to the state of the art in aesthetic evaluation of breast cancer treatments. In addition, the model showed a good ability to retrieve similar previous cases, with the retrieved cases having the same or adjacent class (in the 4-class setting) and having similar types of asymmetry. Finally, a qualitative interpretability assessment was also performed to analyse the robustness and trustworthiness of the model.

2022

Fostering the Adoption of DMP in Small Research Projects through a Collaborative Approach

Authors
Maciel, A; Castro, JA; Ribeiro, C; Almada, M; Midão, L;

Publication
Int. J. Digit. Curation

Abstract

2021

Report on the 1st linked archives international workshop (LinkedArchives 2021) at TPDL 2021

Authors
Lopes, CT; Ribeiro, C; Niccolucci, F; Rodrigues, IP; Antunes Freire, NM;

Publication
SIGIR Forum

Abstract

2021

Institutional support for data management plans: case studies for a systematic approach

Authors
Karimova, Y; Ribeiro, C; David, G;

Publication
Int. J. Metadata Semant. Ontologies

Abstract
Researchers have to ensure that their projects comply with Research Data Management (RDM) requirements. Consequently, the main funding agencies require Data Management Plans (DMPs) for grant applications. So, institutions are investing in RDM tools and implementing RDM workflows in order to support their researchers. In this context, we propose a collaborative DMP-building method that involves researchers, data stewards and other parties if required. This method was applied as part of an RDM workflow in research groups across several scientific domains. We describe it as a systematic approach and illustrate it through a set of case studies. We also address the DMP monitoring process during the life cycle of projects. The feedback from the researchers highlighted the advantages of creating DMPs and their growing need. So, there is motivation to improve the DMP support process according to the machine-actionable DMPs concept and to the best practices in each scientific community. © 2021 Inderscience Enterprises Ltd.. All rights reserved.

Supervised
thesis

2022

Acessibilidade Web para deficientes visuais: uma análise de repositórios institucionais de universidades federais do Nordeste do Brasil

Author
Aline Karoline da Silva Araújo

Institution
UP-FEUP

2022

Integration of models for linked data in cultural heritage and contributions to the FAIR principles

Author
Inês Dias Koch

Institution
UP-FEUP

2022

Entidades Em Documentos De Arquivo E Sua Expansão Com Fontes De Dados Ligados No Projeto EPISA

Author
Camilla Oliveira da Silveira

Institution
UP-FEUP

2022

Research data description in multiple domains: supporting researchers with data management plans

Author
Yulia Karimova

Institution
UP-FEUP

2022

Avaliação da Migração De Registos De Arquivo Para Dados Ligados No Projeto EPISA

Author
Margarida Gouveia Augusto

Institution
UP-FEUP