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About

About

Google Scholar page: https://scholar.google.pt/citations?user=GYoCHRYAAAAJ

João Rocha da Silva holds a PhD in Informatics Engineering from the Faculty of Engineering of the University of Porto, where he also teaches. He specializes on research data management, applying the latest Semantic Web Technologies to the adequate preservation and discovery of research data assets.

Past experience includes two consulting companies: Deloitte and Sysnovare, in which he worked on SAP modules, business blueprinting and software processes restructuring.

He is experienced in many programming languages (Javascript-Node, PHP with MVC frameworks, Ruby on Rails, J2EE, etc etc) running on the major operating systems (everyday Mac user). Regardless of language, he is a quick learner that can adapt to any new technology quickly and effectively.

He is also an experienced freelancer iOS Developer with several Apps published on the App Store, and a self-taught DIY mechanic with a special interest in japanese classic cars.

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Details

Details

  • Name

    João Rocha Silva
  • Cluster

    Computer Science
  • Role

    Researcher
  • Since

    01st November 2012
001
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

Promoting Semantic Annotation of Research Data by Their Creators: A Use Case with B2NOTE at the End of the RDM Workflow

Authors
Karimova, Y; Castro, JA; da Silva, JR; Pereira, N; Ribeiro, C;

Publication
Metadata and Semantic Research - Communications in Computer and Information Science

Abstract

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

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.

2016

End-to-End Research Data Management Workflows A Case Study with Dendro and EUDAT

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

Publication
METADATA AND SEMANTICS RESEARCH, MTSR 2016

Abstract
Depositing and sharing research data is at the core of open science practices. However, institutions in the long tail of science are struggling to properly manage large amounts of data. Support for research data management is still fragile, and most existing solutions adopt generic metadata schemas for data description. These might be unable to capture the production contexts of many datasets, making them harder to interpret. EUDAT is a large ongoing EU-funded project that aims to provide a platform to help researchers manage their datasets and share them when they are ready to be published. Data-Publication@U. Porto is an EUDAT Data Pilot proposing the integration between Dendro, a prototype research data management platform, and the EUDAT B2Share module. The goal is to offer researchers a streamlined workflow: they organize and describe their data in Dendro as soon as they are available, and decide when to deposit in a data repository. Dendro integrates with the API of B2Share, automatically filling the standard metadata descriptors and complementing the data package with additional files for domain-specific descriptors. Our integration offers researchers a simple but complete workflow, from data preparation and description to data deposit.