Abstract
A critical factor in immersive educational narratives is identification by students with the characters. In this work-in-progress analyzes the process of rendering characters from textual narratives into visual form by non-artists (i.e., instructors). We tried to match archetypes with their visual representation through the platforms: Pixton, Powtoon (both 2D) and The Sims4 (3D). The limitations of characterization can impact students' narrative immersion. As future work we intend to test with the target group and observe the improvements needed to increase identification and sense of immersion in the narrative.

Abstract
Digital presence, especially using websites, is currently one of the pillars for effective communication in the field of marketing. However, it appears that many organizations, despite making high investments in development, even if they present a visually attractive website, face difficulties in attracting visitors. In the case of the tourism sector, in which competition takes place on a global level, it is even more pressing for technologies to reach potential stakeholders, first attracting visitors, then seducing them and converting them into customers. In this context, digital marketing techniques, and more specifically, website optimization techniques to improve their visibility by search engines (Search Engine Optimization) are the key to leveraging the potential for visits to any website. In this article, digital marketing concepts and the technological aspects that affect the indexing made by search engines will be explored. The case study presented intends to demonstrate, in a simplified way, the importance and applicability of these concepts and techniques, proposing a set of improvements that should be implemented to improve the positioning of the “Termas de Chaves” website in the search engine page results. © 2022 IEEE Computer Society. All rights reserved.

Abstract
The requirements of a software are the characteristics of the system, being identified based on information provided by the users or by experts in the business; and the effective management of this information is essential to ensure that the system meets the needs of those who will use it. According to research, one of the problems that negatively impacts the software development process is related to the conduction of the project requirements management activity. And in order to alleviate this problem, we carried out a research to verify if taxonomies, as tools used by the area of information management, can be applied in the context of requirements management. For this, we developed a taxonomy to meet a real software project and the results were evaluated in relation to its complexity, satisfaction, resources involved and adaptability. The present research is characterized in terms of nature as an applied research, aiming at solving real-world problems; as for the objectives, as exploratory and descriptive; and as for the approach, mixed methods are used, since it combines qualitative and quantitative forms of research in the same study. As for the methodological procedures, the bibliographic research was chosen to understand the concepts related to information management, taxonomies and requirements management. The evaluation results showed that taxonomies can contribute to the activities of the requirements management process and consequently increase the chances of project success.

Abstract
Glaucoma is a chronic optic neuropathy characterized by irreversible damage to the retinal nerve fiber layer (RNFL), resulting in changes in the visual field (VC). Glaucoma screening is performed through a complete ophthalmological examination, using images of the optic papilla obtained in vivo for the evaluation of glaucomatous characteristics, eye pressure, and visual field. Identifying the glaucomatous papilla is quite important, as optical papillary images are considered the gold standard for tracking. Therefore, this article presents a review of the diagnostic methods used to identify the glaucomatous papilla through technology over the last five years. Based on the analyzed works, the current state-of-the-art methods are identified, the current challenges are analyzed, and the shortcomings of these methods are investigated, especially from the point of view of automation and independence in performing these measurements. Finally, the topics for future work and the challenges that need to be solved are proposed.

Abstract
The COVID-19 pandemic is producing not only epidemiological consequences on a global scale, but also political, economic, and social repercussions. The health care professionals that have been on the front lines fighting the pandemic need the support and assistance of other organizations to meet the many daily challenges. Volunteer firefighters stand out for their outreach approach and implementation of the Human2Human paradigm that has enabled them to meet the needs of the most vulnerable population that have been hit the hardest by the pandemic. This study adopts an ethnographic-action method considering Portuguese volunteer firefighters to explore the characteristics and relevance of these initiatives in areas such as combating isolation, medical assistance, containing the spread of COVID-19, and promoting public-private partnerships. The findings reveal that factors associated with altruism are central elements in the emergence of these initiatives, although some locally or nationally coordinated initiatives have been replicated in other contexts. It is also noteworthy that volunteer firefighters also present initiatives that can be fit into more than one category.

Abstract
Research data on the activities of student teams in online learning environments are relevant for evaluating instructional methods, strategies, tools, and materials. For research data sharing and publication purposes, these personal data must be anonymized or pseudonymized as recommended by data protection and privacy policies. This paper addresses issues related to anonymizing and pseudonymizing student data on the Slack teamwork platform, one often employed in educational and business settings. Issues are discussed from two perspectives: data extraction and data transformation. Difficulties and challenges concerning data extraction and transformation are described. The complexities of these two processes are considered, and a starting point for developing more efficient methods is put forward.