Abstract
Software development is a knowledge-intensive activity. Software products usually start as a simple idea, or a vision, and then progress towards a final deliverable product. Along this evolution, there is a lot of knowledge that is captured, organized, and shared, leading to new knowledge, both as a whole and within specific development activities. The concept of "Ba" provides a foundation to advance individual and collective knowledge, which describes knowledge creation as a spiral involving tacit and explicit knowledge: the Socialization, Externalization, Combination, Internalization model (a.k.a. SECI model). By applying this foundation to software development, we found issues that may hinder the effective knowledge management cycle. In this paper, we present a vision and a set of requirements for tools to overcome such issues and therefore better support the whole process of software knowledge evolution.

Abstract
Falling is a very serious problem for our society, as it affects one out of three older adults. Currently, this is a well-known problem and therefore multiple ICT-based solutions for falls management exist. In addition, a small part of them are said to help preventing falls, but most of the reviewed solutions doesn't seem to have their focus in reducing specific fall risk factors like loss of muscle mass or a poor balance. The proposed ICT-based fall prevention solution is based on an existing fall prevention exercise programme specifically designed for the Portuguese population. It takes advantage of the smartphone processing capabilities as well as its built-in inertial sensors to evaluate the movements performed during the execution of specific exercises. Using only a simple smartphone it is possible to provide a friendly and inexpensive solution capable of increasing seniors' adherence to fall prevention exercises as well as raise their motivation to properly execute the exercises in their home environment. © 2013 IEEE.

Abstract
UNIX-based operative systems were always empowered by scriptable shell interfaces, with a core set of powerful tools to perform manipulation over files and data streams. However those tools can be difficult to manage at the hands of a non-expert programmer. This paper proposes the creation of a Collaborative Web Platform to easily create workflows using common UNIX command line tools for processing Big Data through a collaborative web GUI.

Abstract
E-commerce website owners rely heavily on analysing and summarising the behaviour of costumers, making efforts to influence user actions and optimize success metrics. Machine learning and data mining techniques have been applied in this field, greatly influencing the Internet marketing activities. When faced with a new e-commerce website, the data scientist starts a process of collecting real-time and historical data about it, analysing and transforming this data in order to get a grasp into the website and its users. Data scientists commonly resort to tracking domain-specific events, requiring code modification of the web pages. This paper proposes an alternative approach to retrieve information from a given e-commerce website, collecting data from the site's structure, retrieving semantic information in predefined locations and analysing user's access logs, thus enabling the development of accurate models for predicting users' future behaviour. This is accomplished by the application of a web mining process, comprehending the site's structure, content and usage in a pipeline, resulting in a web graph of the website, complemented with a categorization of each page and the website's archetypical user profiles. 1877-0509 (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
Software business continues to expand globally, highly motivated by the reachability of the Internet and possibilities of Cloud Computing. While widely adopted, development for the cloud has some intrinsic properties to it, making it complex to any newcomer. This research is capturing those intricacies using a pattern catalog, with this paper contributing with three of those patterns: Messaging System, a message bus for abstracting service placement in a cluster and orchestrating messages between multiple services; Preemptive Logging, a design principle where services and servers continuously output relevant information to log files, making them available for later debugging failures; and Log Aggregation, a technique to aggregate logs from multiple services and servers in a centralized location, which indexes and provides them in a queryable, user friendly format. These patterns are useful for anyone designing software for the cloud, either to guide or validate their design decisions. © 2017 Copyright is held by the owner/author(s).

Abstract
In order to increase sales and profits, it is common that e-commerce website owners resort to several marketing and advertising techniques, attempting to influence user actions. Summarizing and analysing user behaviour is a complex task since it is hard to extrapolate patterns that never occurred before and the causality aspects of the system are not usually taken into consideration. There has been studies about characterizing user behaviour and interactions in e-commerce websites that could be used to improve this process. This paper presents an agent-based framework for simulating models of user behaviour created through data mining processes within an e-commerce context. The purpose of framework is to study the reaction of user to stimuli that influence their actions while navigating the website. Furthermore a scalability analysis is performed on a case-study. © Springer International Publishing AG 2018.