This study evaluates user acceptance of a gamification-enabled collaboration and knowledge sharing platform that has been developed for use by personnel in industrial work environments, aiming at increasing motivation for knowledge exchange. The platform has been evaluated at two manufacturing industries by two groups of users, workers and supervisors, with regard to five criteria: usability, knowledge integration, working experience, user acceptance and overall impact. Results showed that even though the ratings from both industries were positive on all criteria, there is room for improvement on user acceptance and knowledge integration. Driven by this fact, a rule-based adaptive gamification approach which exploits information about workers is proposed in order to further increase motivation and engagement. Based on feedback received from the evaluation, guidelines related to functionalities and design of a gamified collaboration platform are provided. These guidelines can be followed when implementing collaboration tools with gamification support for industrial environments.

In the field of journalism, the collection and processing of information from different heterogeneous sources are difficult and time-consuming processes. In the context of the theory of journalism 3.0, where multimedia data can be extracted from different sources on the web, the possibility of creating a tool for the exploitation of Earth observation (EO) data, especially images by professionals belonging to the field of journalism, is explored. With the production of massive volumes of EO image data, the problem of their exploitation and dissemination to the public, specifically, by professionals in the media industry, arises. In particular, the exploitation of satellite image data from existing tools is difficult for professionals who are not familiar with image processing. In this scope, this article presents a new innovative platform that automates some of the journalistic practices. This platform includes several mechanisms allowing users to early detect and receive information about breaking news in real-time, retrieve EO Sentinel-2 images upon request for a certain event, and automatically generate a personalized article according to the writing style of the author. Through this platform, the journalists or editors can also make any modifications to the generated article before publishing. This platform is an added-value tool not only for journalists and the media industry but also for freelancers and article writers who use information extracted from EO data in their articles.