Abstract
Background The small sample sizes available within many very preterm (VPT) longitudinal birth cohort studies mean that it is often necessary to combine and harmonise data from individual studies to increase statistical power, especially for studying rare outcomes. Curating and mapping data is a vital first step in the process of data harmonisation. To facilitate data mapping and harmonisation across VPT birth cohort studies, we developed a custom classification system as part of the Research on European Children and Adults born Preterm (RECAP Preterm) project in order to increase the scope and generalisability of research and the evaluation of outcomes across the lifespan for individuals born VPT. Methods The multidisciplinary consortium of expert clinicians and researchers who made up the RECAP Preterm project participated in a four-phase consultation process via email questionnaire to develop a topic-specific classification system. Descriptive analyses were calculated after each questionnaire round to provide pre- and post- ratings to assess levels of agreement with the classification system as it developed. Amendments and refinements were made to the classification system after each round. Results Expert input from 23 clinicians and researchers from the RECAP Preterm project aided development of the classification system's topic content, refining it from 10 modules, 48 themes and 197 domains to 14 modules, 93 themes and 345 domains. Supplementary classifications for target, source, mode and instrument were also developed to capture additional variable-level information. Over 22,000 individual data variables relating to VPT birth outcomes have been mapped to the classification system to date to facilitate data harmonisation. This will continue to increase as retrospective data items are mapped and harmonised variables are created. Conclusions This bespoke preterm birth classification system is a fundamental component of the RECAP Preterm project's web-based interactive platform. It is freely available for use worldwide by those interested in research into the long term impact of VPT birth. It can also be used to inform the development of future cohort studies.

Abstract
Experimental field campaigns for collecting wind data, essential for academic research and the wind energy industry, are non-trivial due to the complex equipment and infrastructure required. This paper reports the latest developments of the WindsPT e-Science platform for planning, executing, and disseminating wind measurement campaign data. Existing e-Science platforms have been developed for more generic domains, preventing them from capturing the details and requirements of the field. Additionally, we propose a protocol for transferring large volumes of data from the in-site devices to our platform, ensuring data replication. With an easy-to-use Web interface, WindsPT promotes collaboration between participants, disseminates results among the stakeholders, publishes metadata, uses DOI, and includes metadata that enables machine-to-machine communication. The platform has multiple sections, with maps, images, and documents, where there is information about the location of the stations, positioning of the sensors, operating dates, photos, technical sheets, calibration documents, among others. The WindsPT platform has been used to host the Perdigão 2017 experimental campaign and proved to be a valuable tool during all the phases of this large field experiment. A new version of WindsPT, designed to be FAIR, host multiple campaigns, and include multiple cross-campaign shared features, as full-text search capabilities, is now developed and tested.

Abstract
The significant evolution of smartphones has given ordinary people the power to create good-quality content which can then be spread, by the press, over multiple platforms. Citizens are almost always the first ones to arrive at a breaking news location and can provide the initial images of the scene. However, existing crowdsourced tools and platforms are predominantly centralized and are usually fed with unreliable and untrustworthy information. This work introduces a Crowd Journalism ecosystem whose core is a video marketplace web tool based on an organization-level decentralized system that can store, visualize, rate, and execute transactions of live-made videos. Smart contracts ensure that all the transactions are transparent and secure. This approach to Crowd Journalism exploits the inherent features of a blockchain such as offering trustful, anonymized, and immutable transactions, which has the potential to revolutionize the way news content is shared and commercially exploited. © 2020 ACM.

Abstract

Abstract
Dublin Core descriptors capture metadata in most repositories, and this includes recent repositories dedicated to datasets. DC descriptors are generic and are being adapted to the requirements of different communities with the so-called Dublin Core Application Profiles that rely on the agreement within user communities, taking into account their evolving needs. In this paper, we propose an automated process to help curators and users discover the descriptors that best suit the needs of a specific research group in the task of describing and depositing datasets. Our approach is supported on 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. User interaction is recorded and used to score descriptors. 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 viewed descriptors according to the ranking, while the other had the same list of descriptors throughout the experiment. Preliminary results show that (1) some DC Terms are filled in more often than others, with different distribution in the two groups, (2) descriptors in higher ranks were increasingly accepted by users in detriment of manual selection, (3) users were satisfied with the performance of the platform, and (4) the quality of description was not hindered by descriptor ranking. © 2018 Springer-Verlag GmbH Germany, part of Springer Nature