Abstract
Metadata puts research data in their context, making data intelligible and apt to sustain technology evolution and to be reused, in compliance with the FAIR principles. The workflow proposed in this work includes metadata generation in the context of research projects, created with the Dendro platform, and metadata originated in the interaction of people with the deposited data, created with the B2NOTE service from EUDAT. In our experiments, datasets are prepared with Dendro, taking into consideration general-purpose descriptors and domain-specific ones, then transparently deposited in B2SHARE. After publication, B2NOTE provides an environment where authors, other researchers, and any interested party can enrich the description with less formal comments, tags or keywords. This work contributes with (a) a set of use cases in several domains, (b) details on the descriptors used by authors in each case, and (c) reflections on the use of data after publication, using the B2NOTE contributions. © Copyright 2017 Inderscience Enterprises Ltd.

Abstract
O documento fotográfico constitui um enorme desafio para aquela que é chamada de Era de Informação e que vem aprumada com o avanço tecnológico, nomeadamente a imposição do digital, através de dispositivos de captura de imagem. O tratamento de informação fotográfica, embora, à primeira vista, espelhe um leque imenso de oportunidades e benefícios ainda padece de um estudo limitado e pouco desenvolvido. Se por um lado, os documentos de caráter textual estão presentes, em esmagadora maioria, nos centros de informação e, por esse motivo, o sua análise e tratamento são realizadas quotidianamente, por outro, a imagem tem vindo a posicionar-se, ainda que lentamente, na sociedade de informação como um meio implacável na geração de conhecimento.

Abstract

Abstract
Research data management (RDM) practices are critical for ensuring research success. Data can assume diverse formats and data in image format have been understudied in RDM. To understand image management habits in research, we have conducted semi-structured interviews with researchers from four research domains. Most researchers do not formally manage their images, nor do they develop RDM plans. They assume that image management is not a topic discussed at project meetings. In turn, they tend to perform some individual practices, depending on the context and their own opinion, such as creating captions to describe the images and organizing and storing the images in specific locations. However, they see these habits as necessary and admit that they will start to do so in a formal and collaborative way with the working group. These results provide valuable information on practical aspects of the use and production of images in research.

Abstract
Research data management is an essential process in scientific research activities. It includes monitoring data from the moment it is created until it is deposited in a repository so that later it can be accessed and reused by others. Sharing and reuse are the last steps in this process. It is essential to ensure that the data stored in digital repositories is well preserved in the long term and that its adequate interpretation and future reuse is guaranteed. Following this debate, questions arise related to the interoperability of systems and the suitability of platforms. In this study, we study how data management platforms can solve the problems associated with description, preservation, and access in digital media, making their usefulness evident. We identify some of the most relevant repository platforms in the scope of research data management, offering the scientific community an aggregating view of the various solutions and their main characteristics, thus aiming at a better understanding of them for their appropriate choice.

Abstract
Research data management (RDM) includes people with different needs, specific scientific contexts, and diverse requirements. The description is a big challenge in the domain of RDM. Metadata plays an essential role, allowing the inclusion of essential information for the interpretation of data, enhances the reuse of data and its preservation. The establishment of metadata models can facilitate the process of description and contribute to an improvement in the quality of metadata. When we talk about image data, the task is even more difficult, as there are no explicit recommendations to guide image management. In this work, we present a proposal for a metadata model for image description. To validate the model, we followed an experiment of data description, where eleven participants described images from their research projects, using a metadata model proposed. The experiment shows that participants do not have formal practices for describing their imagery data. Yet, they provided valuable contributions and recommendations to the final definition of a metadata model for image description, to date nonexistent. We also developed controlled vocabularies for some descriptors. These vocabularies aim to improve the image description process, facilitate metadata model interpretation, and reduce the time and effort devoted to data description. © 2022 Joana Rodrigues and Carla Teixeira Lopes Published with license by Taylor & Francis Group, LLC.