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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

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
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.

2016

Voice recognition in the LabTablet electronic laboratory notebook

Authors
Ventura, S; Amorim, RC; Silva, JRd; Ribeiro, C;

Publication
Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering, C3S2E '16, Porto, Portugal, July 20-22, 2016

Abstract
Research institutions are considering data repositories to manage their outputs and ensure their visibility. In many domains, purpose-built tools can help collect data and metadata as they are created. LabTablet is such a tool, designed to provide the functions of a laboratory notebook, and being able to accompany users in either experimental sessions or field trips. In these contexts, the interaction with the device can be problematic, so we experimented with a speech recognition extension for two purposes: to provide commands, such as requesting readings from the built-in sensors, and to record observations such as a dictated note in a field trip. Copyright 2016 ACM.

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.