Políticas de Copyright de Publicações Científicas em Repositórios Institucionais: O Caso do INESC TEC

A progressiva transformação das práticas científicas, impulsionada pelo desenvolvimento das novas Tecnologias de Informação e Comunicação (TIC), têm possibilitado aumentar o acesso à informação, caminhando gradualmente para uma abertura do ciclo de pesquisa. Isto permitirá resolver a longo prazo uma adversidade que se tem colocado aos investigadores, que passa pela existência de barreiras que limitam as condições de acesso, sejam estas geográficas ou financeiras. Apesar da produção científica ser dominada, maioritariamente, por grandes editoras comerciais, estando sujeita às regras por estas impostas, o Movimento do Acesso Aberto cuja primeira declaração pública, a Declaração de Budapeste (BOAI), é de 2002, vem propor alterações significativas que beneficiam os autores e os leitores. Este Movimento vem a ganhar importância em Portugal desde 2003, com a constituição do primeiro repositório institucional a nível nacional. Os repositórios institucionais surgiram como uma ferramenta de divulgação da produção científica de uma instituição, com o intuito de permitir abrir aos resultados da investigação, quer antes da publicação e do próprio processo de arbitragem (preprint), quer depois (postprint), e, consequentemente, aumentar a visibilidade do trabalho desenvolvido por um investigador e a respetiva instituição. O estudo apresentado, que passou por uma análise das políticas de copyright das publicações científicas mais relevantes do INESC TEC, permitiu não só perceber que as editoras adotam cada vez mais políticas que possibilitam o auto-arquivo das publicações em repositórios institucionais, como também que existe todo um trabalho de sensibilização a percorrer, não só para os investigadores, como para a instituição e toda a sociedade. A produção de um conjunto de recomendações, que passam pela implementação de uma política institucional que incentive o auto-arquivo das publicações desenvolvidas no âmbito institucional no repositório, serve como mote para uma maior valorização da produção científica do INESC TEC.The progressive transformation of scientific practices, driven by the development of new Information and Communication Technologies (ICT), which made it possible to increase access to information, gradually moving towards an opening of the research cycle. This opening makes it possible to resolve, in the long term, the adversity that has been placed on researchers, which involves the existence of barriers that limit access conditions, whether geographical or financial. Although large commercial publishers predominantly dominate scientific production and subject it to the rules imposed by them, the Open Access movement whose first public declaration, the Budapest Declaration (BOAI), was in 2002, proposes significant changes that benefit the authors and the readers. This Movement has gained importance in Portugal since 2003, with the constitution of the first institutional repository at the national level. Institutional repositories have emerged as a tool for disseminating the scientific production of an institution to open the results of the research, both before publication and the preprint process and postprint, increase the visibility of work done by an investigator and his or her institution. The present study, which underwent an analysis of the copyright policies of INESC TEC most relevant scientific publications, allowed not only to realize that publishers are increasingly adopting policies that make it possible to self-archive publications in institutional repositories, all the work of raising awareness, not only for researchers but also for the institution and the whole society. The production of a set of recommendations, which go through the implementation of an institutional policy that encourages the self-archiving of the publications developed in the institutional scope in the repository, serves as a motto for a greater appreciation of the scientific production of INESC TEC

More compact orthogonal drawings by allowing additional bends

Compacting orthogonal drawings is a challenging task. Usually, algorithms try to compute drawings with small area or total edge length while preserving the underlying orthogonal shape. We suggest a moderate relaxation of the orthogonal compaction problem, namely the one-dimensional monotone flexible edge compaction problem with fixed vertex star geometry. We further show that this problem can be solved in polynomial time using a network flow model. An experimental evaluation shows that by allowing additional bends could reduce the total edge length and the drawing area

Brave New GES World:A Systematic Literature Review of Gestures and Referents in Gesture Elicitation Studies

How to determine highly effective and intuitive gesture sets for interactive systems tailored to end users’ preferences? A substantial body of knowledge is available on this topic, among which gesture elicitation studies stand out distinctively. In these studies, end users are invited to propose gestures for specific referents, which are the functions to control for an interactive system. The vast majority of gesture elicitation studies conclude with a consensus gesture set identified following a process of consensus or agreement analysis. However, the information about specific gesture sets determined for specific applications is scattered across a wide landscape of disconnected scientific publications, which poses challenges to researchers and practitioners to effectively harness this body of knowledge. To address this challenge, we conducted a systematic literature review and examined a corpus of N=267 studies encompassing a total of 187, 265 gestures elicited from 6, 659 participants for 4, 106 referents. To understand similarities in users’ gesture preferences within this extensive dataset, we analyzed a sample of 2, 304 gestures extracted from the studies identified in our literature review. Our approach consisted of (i) identifying the context of use represented by end users, devices, platforms, and gesture sensing technology, (ii) categorizing the referents, (iii) classifying the gestures elicited for those referents, and (iv) cataloging the gestures based on their representation and implementation modalities. Drawing from the findings of this review, we propose guidelines for conducting future end-user gesture elicitation studies

Automatic generation of software interfaces for supporting decisionmaking processes. An application of domain engineering & machine learning

[EN] Data analysis is a key process to foster knowledge generation in particular domains or fields of study. With a strong informative foundation derived from the analysis of collected data, decision-makers can make strategic choices with the aim of obtaining valuable benefits in their specific areas of action. However, given the steady growth of data volumes, data analysis needs to rely on powerful tools to enable knowledge extraction. Information dashboards offer a software solution to analyze large volumes of data visually to identify patterns and relations and make decisions according to the presented information. But decision-makers may have different goals and, consequently, different necessities regarding their dashboards. Moreover, the variety of data sources, structures, and domains can hamper the design and implementation of these tools. This Ph.D. Thesis tackles the challenge of improving the development process of information dashboards and data visualizations while enhancing their quality and features in terms of personalization, usability, and flexibility, among others. Several research activities have been carried out to support this thesis. First, a systematic literature mapping and review was performed to analyze different methodologies and solutions related to the automatic generation of tailored information dashboards. The outcomes of the review led to the selection of a modeldriven approach in combination with the software product line paradigm to deal with the automatic generation of information dashboards. In this context, a meta-model was developed following a domain engineering approach. This meta-model represents the skeleton of information dashboards and data visualizations through the abstraction of their components and features and has been the backbone of the subsequent generative pipeline of these tools. The meta-model and generative pipeline have been tested through their integration in different scenarios, both theoretical and practical. Regarding the theoretical dimension of the research, the meta-model has been successfully integrated with other meta-model to support knowledge generation in learning ecosystems, and as a framework to conceptualize and instantiate information dashboards in different domains. In terms of the practical applications, the focus has been put on how to transform the meta-model into an instance adapted to a specific context, and how to finally transform this later model into code, i.e., the final, functional product. These practical scenarios involved the automatic generation of dashboards in the context of a Ph.D. Programme, the application of Artificial Intelligence algorithms in the process, and the development of a graphical instantiation platform that combines the meta-model and the generative pipeline into a visual generation system. Finally, different case studies have been conducted in the employment and employability, health, and education domains. The number of applications of the meta-model in theoretical and practical dimensions and domains is also a result itself. Every outcome associated to this thesis is driven by the dashboard meta-model, which also proves its versatility and flexibility when it comes to conceptualize, generate, and capture knowledge related to dashboards and data visualizations

Image and Video Forensics

Nowadays, images and videos have become the main modalities of information being exchanged in everyday life, and their pervasiveness has led the image forensics community to question their reliability, integrity, confidentiality, and security. Multimedia contents are generated in many different ways through the use of consumer electronics and high-quality digital imaging devices, such as smartphones, digital cameras, tablets, and wearable and IoT devices. The ever-increasing convenience of image acquisition has facilitated instant distribution and sharing of digital images on digital social platforms, determining a great amount of exchange data. Moreover, the pervasiveness of powerful image editing tools has allowed the manipulation of digital images for malicious or criminal ends, up to the creation of synthesized images and videos with the use of deep learning techniques. In response to these threats, the multimedia forensics community has produced major research efforts regarding the identification of the source and the detection of manipulation. In all cases (e.g., forensic investigations, fake news debunking, information warfare, and cyberattacks) where images and videos serve as critical evidence, forensic technologies that help to determine the origin, authenticity, and integrity of multimedia content can become essential tools. This book aims to collect a diverse and complementary set of articles that demonstrate new developments and applications in image and video forensics to tackle new and serious challenges to ensure media authenticity

Data Science, Data Visualization, and Digital Twins

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development

Saliency Prediction in the Data Visualization Design Process

L'abstract è presente nell'allegato / the abstract is in the attachmen

Comparative Uncertainty Visualization for High-Level Analysis of Scalar- and Vector-Valued Ensembles

With this thesis, I contribute to the research field of uncertainty visualization, considering parameter dependencies in multi valued fields and the uncertainty of automated data analysis. Like uncertainty visualization in general, both of these fields are becoming more and more important due to increasing computational power, growing importance and availability of complex models and collected data, and progress in artificial intelligence. I contribute in the following application areas: Uncertain Topology of Scalar Field Ensembles. The generalization of topology-based visualizations to multi valued data involves many challenges. An example is the comparative visualization of multiple contour trees, complicated by the random nature of prevalent contour tree layout algorithms. I present a novel approach for the comparative visualization of contour trees - the Fuzzy Contour Tree. Uncertain Topological Features in Time-Dependent Scalar Fields. Tracking features in time-dependent scalar fields is an active field of research, where most approaches rely on the comparison of consecutive time steps. I created a more holistic visualization for time-varying scalar field topology by adapting Fuzzy Contour Trees to the time-dependent setting. Uncertain Trajectories in Vector Field Ensembles. Visitation maps are an intuitive and well-known visualization of uncertain trajectories in vector field ensembles. For large ensembles, visitation maps are not applicable, or only with extensive time requirements. I developed Visitation Graphs, a new representation and data reduction method for vector field ensembles that can be calculated in situ and is an optimal basis for the efficient generation of visitation maps. This is accomplished by bringing forward calculation times to the pre-processing. Visually Supported Anomaly Detection in Cyber Security. Numerous cyber attacks and the increasing complexity of networks and their protection necessitate the application of automated data analysis in cyber security. Due to uncertainty in automated anomaly detection, the results need to be communicated to analysts to ensure appropriate reactions. I introduce a visualization system combining device readings and anomaly detection results: the Security in Process System. To further support analysts I developed an application agnostic framework that supports the integration of knowledge assistance and applied it to the Security in Process System. I present this Knowledge Rocks Framework, its application and the results of evaluations for both, the original and the knowledge assisted Security in Process System. For all presented systems, I provide implementation details, illustrations and applications

Cultural Heritage Storytelling, Engagement and Management in the Era of Big Data and the Semantic Web

The current Special Issue launched with the aim of further enlightening important CH areas, inviting researchers to submit original/featured multidisciplinary research works related to heritage crowdsourcing, documentation, management, authoring, storytelling, and dissemination. Audience engagement is considered very important at both sites of the CH production–consumption chain (i.e., push and pull ends). At the same time, sustainability factors are placed at the center of the envisioned analysis. A total of eleven (11) contributions were finally published within this Special Issue, enlightening various aspects of contemporary heritage strategies placed in today’s ubiquitous society. The finally published papers are related but not limited to the following multidisciplinary topics:Digital storytelling for cultural heritage;Audience engagement in cultural heritage;Sustainability impact indicators of cultural heritage;Cultural heritage digitization, organization, and management;Collaborative cultural heritage archiving, dissemination, and management;Cultural heritage communication and education for sustainable development;Semantic services of cultural heritage;Big data of cultural heritage;Smart systems for Historical cities – smart cities;Smart systems for cultural heritage sustainability

Workshop, Long and Short Paper, and Poster Proceedings from the Fourth Immersive Learning Research Network Conference (iLRN 2018 Montana), 2018.

ILRN 2018 - Conferência internacional realizada em Montana de 24-29 de june de 2018.Workshop, short paper, and long paper proceedingsinfo:eu-repo/semantics/publishedVersio