Cookies Policy
We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out More
Close
  • Menu
About

About

Holds a Master degree in Information Science, by the University of Porto. Currently a Digital Media PhD student.

The main focus of interest is in the definition of domain-specific metadata modelos so researchers can describe the data they are creating.

Interest
Topics
Details

Details

  • Name

    João Aguiar Castro
  • Cluster

    Computer Science
  • Role

    Research Assistant
  • Since

    15th July 2013
Publications

2017

Involving data creators in an ontology-based design process for metadata models

Authors
Castro, JA; Amorim, RC; Gattelli, R; Karimova, Y; Da Silva, JR; Ribeiro, C;

Publication
Developing Metadata Application Profiles

Abstract
Research data are the cornerstone of science and their current fast rate of production is disquieting researchers. Adequate research data management strongly depends on accurate metadata records that capture the production context of the datasets, thus enabling data interpretation and reuse. This chapter reports on the authors' experience in the development of the metadata models, formalized as ontologies, for several research domains, involving members from small research teams in the overall process. This process is instantiated with four case studies: vehicle simulation; hydrogen production; biological oceanography and social sciences. The authors also present a data description workflow that includes a research data management platform, named Dendro, where researchers can prepare their datasets for further deposit in external data repositories. © 2017, IGI Global.

2017

A comparison of research data management platforms: architecture, flexible metadata and interoperability

Authors
Amorim, RC; Castro, JA; da Silva, JR; Ribeiro, C;

Publication
UNIVERSAL ACCESS IN THE INFORMATION SOCIETY

Abstract
Research data management is rapidly becoming a regular concern for researchers, and institutions need to provide them with platforms to support data organization and preparation for publication. Some institutions have adopted institutional repositories as the basis for data deposit, whereas others are experimenting with richer environments for data description, in spite of the diversity of existing workflows. This paper is a synthetic overview of current platforms that can be used for data management purposes. Adopting a pragmatic view on data management, the paper focuses on solutions that can be adopted in the long tail of science, where investments in tools and manpower are modest. First, a broad set of data management platforms is presented-some designed for institutional repositories and digital libraries-to select a short list of the more promising ones for data management. These platforms are compared considering their architecture, support for metadata, existing programming interfaces, as well as their search mechanisms and community acceptance. In this process, the stakeholders' requirements are also taken into account. The results show that there is still plenty of room for improvement, mainly regarding the specificity of data description in different domains, as well as the potential for integration of the data management platforms with existing research management tools. Nevertheless, depending on the context, some platforms can meet all or part of the stakeholders' requirements.

2015

A Comparative Study of Platforms for Research Data Management: Interoperability, Metadata Capabilities and Integration Potential

Authors
Amorim, RC; Castro, JA; da Silva, JR; Ribeiro, C;

Publication
NEW CONTRIBUTIONS IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 1, PT 1

Abstract
Research data management is acknowledged as an important concern for institutions and several platforms to support data deposits have emerged. In this paper we start by overviewing the current practices in the data management workflow and identifying the stakeholders in this process. We then compare four recently proposed data repository platforms-DSpace, CKAN, Zenodo and Figshare-considering their architecture, support for metadata, API completeness, as well as their search mechanisms and community acceptance. To evaluate these features, we take into consideration the identified stakeholders' requirements. In the end, we argue that, depending on local requirements, different data repositories can meet some of the stakeholders requirements. Nevertheless, there is still room for improvements, mainly regarding the compatibility with the description of data from different research domains, to further improve data reuse.

2015

Motivators and Deterrents for Data Description and Publication: Preliminary Results

Authors
Ribeiro, C; da Silva, JR; Castro, JA; Amorim, RC; Fortuna, P;

Publication
ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2015 WORKSHOPS

Abstract
In the recent trend of data-intensive science, data publication is essential and institutions have to promote it with the researchers. For the past decade, institutional repositories have been widely established for publications, and the motivations for deposit are well established. The situation is quite different for data, as we argue on the basis of a 5-year experience with research data management at the University of Porto. We address research data management from a disciplined yet flexible point of view, focusing on domain-specific metadata models embedded in intuitive tools, to make it easier for researchers to publish their datasets. We use preliminary data from a recent experiment in data publishing to identify motivators and deterrents for data publishing.

2015

Ontologies for Research Data Description: A Design Process Applied to Vehicle Simulation

Authors
Castro, JA; Perrotta, D; Amorim, RC; da Silva, JR; Ribeiro, C;

Publication
METADATA AND SEMANTICS RESEARCH, MTSR 2015

Abstract
Data description is an essential part of research data management, and it is easy to argue for the importance of describing data early in the research workflow. Specific metadata schemas are often proposed to support description. Given the diversity of research domains, such schemas are often missing, and when available they may be too generic, too complex or hard to incorporate in a description platform. In this paper we present a method used to design metadata models for research data description as ontologies. Ontologies are gaining acceptance as knowledge representation structures, and we use them here in the scope of the Dendro platform. The ontology design process is illustrated with a case study from Vehicle Simulation. According to the design process, the resulting model was validated by a domain specialist.

Supervised
thesis

2016

Vocabulários controlados na descrição de dados de investigação no Dendro

Author
Yulia Karimova

Institution
UP-FEUP