Enhancing the Digital Backchannel Backstage on the Basis of a Formative User Study

Contemporary higher education with its large audiences suffers from passivity of students. Enhancing the classroom with a digital backchannel can contribute to establishing and fostering active participation of and collaboration among students in the lecture. Therefore, we conceived the digital backchannel Backstage specifically tailored for the use in large classes. At an early phase of development we tested its core functionalities in a small-scale user study. The aim of the study was to gain first impressions of its adoption, and also to form a basis for further steps in the conception of Backstage. Regarding adoption we particularly focused on how Backstage influences the participants' questioning behavior, a salient aspect in learning. We observed that during the study much more questions were uttered on Backstage than being asked without backchannel support. Regarding the further development of Backstage we capitalized on the participants' usability feedback. The key of the refinement is the integration of presentation slides in Backstage, which leads to an interesting reconsideration of the user interactions of Backstage

Information Dashboards and Tailoring Capabilities: A Systematic Literature Review

[EN]The design and development of information dashboards are not trivial. Several factors must be accounted; from the data to be displayed to the audience that will use the dashboard. However, the increase in popularity of these tools has extended their use in several and very different contexts among very different user pro les. This popularization has increased the necessity of building tailored displays focused on speci c requirements, goals, user roles, situations, domains, etc. Requirements are more sophisticated and varying; thus, dashboards need to match them to enhance knowledge generation and support more complex decision-making processes. This sophistication has led to the proposal of new approaches to address personal requirements and foster individualization regarding dashboards without involving high quantities of resources and long development processes. The goal of this work is to present a systematic review of the literature to analyze and classify the existing dashboard solutions that support tailoring capabilities and the methodologies used to achieve them. The methodology follows the guidelines proposed by Kitchenham and other authors in the eld of software engineering. As results, 23 papers about tailored dashboards were retrieved. Three main approaches were identi ed regarding tailored solutions: customization, personalization, and adaptation. However, there is a wide variety of employed paradigms and features to develop tailored dashboards. The present systematic literature review analyzes challenges and issues regarding the existing solutions. It also identi es new research paths to enhance tailoring capabilities and thus, to improve user experience and insight delivery when it comes to visual analysis

Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards

[EN]Information dashboards are everywhere. They support knowledge discovery in a huge variety of contexts and domains. Although powerful, these tools can be complex, not only for the end-users but also for developers and designers. Information dashboards encode complex datasets into different visual marks to ease knowledge discovery. Choosing a wrong design could compromise the entire dashboard’s effectiveness, selecting the appropriate encoding or configuration for each potential context, user, or data domain is a crucial task. For these reasons, there is a necessity to automatize the recommendation of visualizations and dashboard configurations to deliver tools adapted to their context. Recommendations can be based on different aspects, such as user characteristics, the data domain, or the goals and tasks that will be achieved or carried out through the visualizations. This work presents a dashboard meta-model that abstracts all these factors and the integration of a visualization task taxonomy to account for the different actions that can be performed with information dashboards. This meta-model has been used to design a domain specific language to specify dashboards requirements in a structured way. The ultimate goal is to obtain a dashboard generation pipeline to deliver dashboards adapted to any context, such as the educational context, in which a lot of data are generated, and there are several actors involved (students, teachers, managers, etc.) that would want to reach different insights regarding their learning performance or learning methodologies

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

A component- and connector-based approach for end-user composite web applications development

Enabling real end-user development is the next logical stage in the evolution of Internet-wide service-based applications. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. This weakness can be attributed to the fact that the composition model does not satisfy end-user needs rather than to the actual infrastructure technologies. In our opinion, the best way to overcome this weakness is to offer end-to-end composition from the user interface to service invocation, plus an understandable abstraction of building blocks and a visual composition technique empowering end users to develop their own applications. In this paper, we present a visual framework for end users, called FAST, which fulfils this objective. FAST implements a novel composition model designed to empower non-programmer end users to create and share their own self-service composite applications in a fully visual fashion. We projected the development environment implementing this model as part of the European FP7 FAST Project, which was used to validate the rationale behind our approach

A framework for dashboarding city performance : an application to Cascais smart city

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThere has been a recent move to open up the data about the cities and transform it in indicators of interest to share with citizens through online, interactive data visualizations, often termed ‘city dashboards’. This project reflects on the building of dashboards mainly based on open data generated in the smart city context of Cascais. The main goal of these dashboards is to provide detailed information about city performance and trends, without citizens or the managers of the municipality needing to collect or learn how to handle data. These open data and dashboard initiatives are changing not only the relationship between government and the public, but also the way that the municipality is managed. The work begins with a literature review composed by a framework describing the characteristics of a smart city followed by an approach about the open data and a perspective about dashboards. Then, a benchmarking is presented as a means to select a series of indicators that can efficiently capture the performance of the smart city. These indicators will feed the dashboards that will permit to see Cascais as visualized facts, changing the way how managers and citizens know their municipality. The work also identifies the need of a graphic rules manual to follow up in future dashboards in order to achieve coherence in the public share of dashboards by the various departments of Cascais. The project ends with the presentation of a set of key indicators that describe the municipality in several dimensions and with an application case of the constructed dashboards to the open data portal of Cascais

Unilever food solutions new digital CRM platform- what is the combination of tools, processes and content that will help Unilever food solutions grow his business?

Unilever Food Solutions new digital CRM1 Platform - What is the combination of tools, processes and content that will help Unilever Food Solutions grow his business? Unilever Food Solutions (UFS) intend to create a new online platform to enable it to communicate with segments of the markets, which have previously been too difficult to reach. Specifically targeted at Chefs and other food professionals, the aim is to create an interactive website, which delivers value to its intended users by providing a variety of relevant content and functions, while simultaneously opening up a potential transactional channel to those same users

A Meta-Model Integration for Supporting Knowledge Discovery in Specific Domains: A Case Study in Healthcare

[EN]Knowledge management is one of the key priorities of many organizations. They face di erent challenges in the implementation of knowledge management processes, including the transformation of tacit knowledge—experience, skills, insights, intuition, judgment and know-how—into explicit knowledge. Furthermore, the increasing number of information sources and services in some domains, such as healthcare, increase the amount of information available. Therefore, there is a need to transform that information in knowledge. In this context, learning ecosystems emerge as solutions to support knowledge management in a di erent context. On the other hand, the dashboards enable the generation of knowledge through the exploitation of the data provided from di erent sources. The model-driven development of these solutions is possible through two meta-models developed in previous works. Even though those meta-models solve several problems, the learning ecosystem meta-model has a lack of decision-making support. In this context, this work provides two main contributions to face this issue. First, the definition of a holistic meta-model to support decision-making processes in ecosystems focused on knowledge management, also called learning ecosystems. The second contribution of this work is an instantiation of the presented holistic meta-model in the healthcare domain

Ending Extreme Poverty and Sharing Prosperity: Progress and Policies

To guide its work toward a "world free of poverty," the World Bank Group in 2013 established two clear goals: end extreme poverty by 2030 and promote shared prosperity. Along with the requirement to pursue these goals sustainably -- economically, environmentally, and socially -- the two goals are comprehensive in nature. They are fully aligned to support the Sustainable Development Goals (SDGs) set by the United Nations to replace the Millennium Development Goals (MDGs). To evaluate progress, the two goals are measured by two overall indicators: a reduction in the global headcount ratio of extreme poverty (the population share of those whose income is below the international poverty line) to 3 percent by 2030, and the promotion of income growth in the bottom 40 (B40) percent of the population in each country.This Policy Research Note updates the assessment of progress toward these two goals in a sustainable manner. The poverty goal is examined through three lenses: the evolution of income poverty based on the new international poverty line that has been re-estimated at $1.90 a day; an assessment of person-equivalent income poverty, a new intuitive indicator that combines the incidence with the depth of poverty; and a review of the breadth of poverty, recognizing that income shortfalls often coexist with multiple non-income deprivations. The shared prosperity goal is examined on the basis of the latest comparison of (comparable) household data on B40 income growth. As part of its analysis of the two goals, this note also comments on the status of defining and monitoring sustainability in its economic, environmental and social aspects

Human resources analytics module at Quidgest: One more step for human resources to become a true strategic partner

Analytics has been a source of competitive advantage due to improved decision-making processes in several business areas. Organizations have reported gains in efficiency and effectiveness based on the implementation of data-driven strategies. However, Human Resources (HR) professionals have been struggling to implement Analytics processes and are missing out on the opportunity of using data to improve organizational performance and truly become a Business Strategic Partner. This Enterprise Project aims to contribute to shortening that gap. It sets out to gather and elicit business, user, functional, and nonfunctional requirements for a new Human Resources Analytics Module (HRAM) at Quidgest, a Portuguese Technological Consultancy company that develops Human Resources Information Systems. The gathering and elicitation of requirements were done through Interviews, a Questionnaire, and 2 Joint Application Development (JAD) Sessions. A Value Proposition Canvas was developed to convey a fit between the system’s main functionalities and HR Professionals’ needs based on those requirements. The relevance of this project is two-folded: First, when developed, the new Analytics Module can become a new revenue stream for Quidgest and a way to maintain and improve its competitiveness in the market; Second, HR Professionals may find a new tool that meets their needs towards implementing Analytics processes and take a step forward in becoming a Strategic Partner. The conclusion of this project also sets out to suggest the next steps for the Module Development and implementation.O uso de Analytics tem sido uma fonte de vantagem competitiva devido à melhoria dos processos de tomada de decisão. As organizações relatam ganhos em eficiência e eficácia com base na implementação de estratégias baseadas em análise de dados. No entanto, os profissionais de Recursos Humanos (RH) têm se debatido para implementar processos analíticos e estão a perder a oportunidade de usar os seus dados para melhorar o desempenho organizacional e se tornarem realmente Strategic Business Partners. Este projeto em empresa visa colmatar essa lacuna. Pretende-se recolher e clarificar requisitos de negócio, utilizador, funcionais e não funcionais para um novo Módulo de Human Resources (HR) Analytics na Quidgest, uma constultora tecnológica portuguesa que desenvolve Sistemas de Informação de RH. A recolha e a clarificação de requisitos foi feita através de entrevistas, um questionário, e 2 Joint Application Development Sessions. De seguida, foi desenvolvido um Value Proposition Canvas, que mostra como há um fit entre as principais funcionalidades do sistema e as necessidades dos profissionais de RH nesta área. A relevância deste projeto prende-se em dois aspetos: primeiro, o novo Módulo de Analytics pode tornar-se uma nova fonte de receita para a Quidgest e uma forma de manter e melhorar sua competitividade; Em segundo lugar, os profissionais de RH podem encontrar uma nova ferramenta que responda às suas necessidades de implementação de processos analíticos e dar um passo em frente para se tornarem um Business Partner. A conclusão deste projeto sugere os próximos passos para o Desenvolvimento do Módulo de Analytics