Abstract
Weather and sea-related forecasts provide crucial insights for the practice of nautical sports such as surf and kite surf, and mobile devices are appropriate interfaces for the visualization of meteorology and operational oceanography data. Data are collected and processed by several agencies and are often obtained from forecast models. Their use requires adaptation and refinement prior to visualisation. We describe a set of semantic data services using standard common vocabularies and interoperable interfaces following the recommendations of the INSPIRE directive. NautiCast, a mobile application for forecast delivery illustrates the adaptation of data at two levels: 1) semantic, with the integration of data from different sources via standard vocabularies, and 2) syntactic, with the manipulation of the spacial and temporal resolution of data to get effective mobile communication. Copyright 2016 ACM.

Abstract
Dealing with research data management can be a complex task, and recent guidelines prompt researchers to actively participate in this activity. Emergent research data platforms are proposing workflows to motivate researchers to take an active role in the management of their data. Other tools, such as electronic laboratory notebooks, can be embedded in the laboratory environment to ease the collection of valuable data and metadata as soon as it is available. This paper reports an extension of the previously developed LabTablet application to gather data and metadata for different research domains. Along with this extension, we present a case study from the social sciences, concerning the identification of the data description requirements for one of its domains. We argue that the LabTablet can be crucial to engage researchers in data organization and description. After starting the process, researchers can then manage their data in Dendro, a staging platform with stronger, collaborative management capabilities, which allows them to export their annotated datasets to selected research data repositories.

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.