Abstract
Research data are the cornerstone of science and their current fast rate of production is disquieting researchers. Adequate research data management strongly depends on accurate metadata records that capture the production context of the datasets, thus enabling data interpretation and reuse. This chapter reports on the authors' experience in the development of the metadata models, formalized as ontologies, for several research domains, involving members from small research teams in the overall process. This process is instantiated with four case studies: vehicle simulation; hydrogen production; biological oceanography and social sciences. The authors also present a data description workflow that includes a research data management platform, named Dendro, where researchers can prepare their datasets for further deposit in external data repositories. © 2017, IGI Global.

Abstract
Developing robust and universal methods for unsupervised segmentation of moving objects in video sequences has proved to be a hard and challenging task. The best solutions are, in general, computationally heavy preventing their use in real-time applications. This research addresses this problem by proposing a robust and computationally efficient method, BMOG, that significantly boosts the performance of the widely used MOG2 method. The complexity of BMOG is kept low, proving its suitability for real-time applications. The proposed solution explores a novel classification mechanism that combines color space discrimination capabilities with hysteresis and a dynamic learning rate for background model update.

Abstract

Abstract
Location-based games require, among other things, physical activity and real-world context. Additionally, ensuring that the players are assigned challenges that are adequate and safe for the current context (both physical and spatial) is also important, as it can improve both the gaming experience and the outcomes of the exercise. However, the impact adaptivity has in the specific case of location-based exergames still has not been researched in depth. In this paper, we present a location-based exergame capable of adapting its mechanics to the current context.

Abstract
Location-based games require, among other things, obtaining or computing information regarding the players’ physical activity and real-world context. Additionally, ensuring that the players are assigned challenges that are adequate and safe for the current context (both physical and spatial) is also important, as it can improve both the gaming experience and the outcomes of the exercise. However, the impact adaptivity has in the specific case of location-based exergames still has not been researched in depth. In this paper, we present a location-based exergame and compare different play-through sessions when playing both the context sensitive and the regular versions of the game. Results show that the adaptive version provided a significantly safer gameplay experience. These results showcase the impact in player health and safety that player adaptivity achieves in location-based exergames. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
Nowadays, we continue to write redundant code which can often be reused from the Web. Reusing programming tasks is beneficial since it speeds up the process of creating applications and reduces the errors related with the task creation from scratch. At the same time, the demands of our applications are increasing, leading to a simple problem having to be solved through several tasks. With the advent of the cloud, there are countless Web services that proliferate on the Web. One solution for developers is to use these Web Services. However, the process of mastering and coordinating all these services manually is time-consuming and error-prone. This paper presents SOS, a Simple Orchestration of Services. The ultimate goal of this tool is to act as a service composer while promoting the separation of concerns for two typical actors in this realm: the developer and the business analyst. The developer must define a service as a SOS task based on a JSON schema and submit it in a Web specialized editor. The business analyst uses the SOS editor, in an interactive way, to chain the required tasks to solve a specific problem. Then, the developer, uses a a simple client API – a SOS engine wrapper – to load a SOS manifest and to iterate over all tasks, without the need to dominate any bureaucratic aspects related with HTTP clients and messages. As a case study, several tasks are instantiated and aggregated in order to generate a composite service for a mobile app whose goal is to give an translated description of a picture taken with a mobile phone. © Ricardo Queirós and Alberto Simões