In a time of 'Big Data,' 'Personal Informatics' and 'Infographics' the definitions of data visualization and data analytics are splintering rapidly. When one compares how Fortune 500 companies are using analytics to optimize their supply chains and lone individuals are visualizing their Twitter messages, we can see how multipurpose these areas are becoming. Visualization and analytics are frequently exhibited as tools for increasing efficiency and informing future decisions. At the same time, they are used to produce artworks that alter our perspectives of how data is represented and analyzed. During this time of turbulent reflection within the fields of data visualization and analytics, digital games have been going through a similar period of data metamorphosis as players are increasingly being connected and tracked through various platform systems and social networks. The amount of game-related data collected and shared today greatly exceeds that of previous gaming eras and, by utilizing the domains of data visualization and analytics, this increased access to data is poised to reshape, and continue to reshape, how players experience games. This dissertation examines how visualization, analytics and games intersect into a domain with a fluctuating identity but has the overall goal to analyze game-related data. At this intersection exists play analytics, a blend of digital systems and data analysis methods connecting players, games and their data. Play analytic systems surround the experience of playing a game, visualizing data collected from players and act as external online hubs where players congregate. As part of this dissertation's examination of play analytics, over eighty systems are analyzed and discussed. Additionally, a user study was conducted to test the effects play analytic systems have on a player's gameplay behavior. Both studies are used to highlight how play analytic systems function and are experienced by players. With millions of players already using play analytics systems, this dissertation provides a chronicle of the current state of play analytics, how the design of play analytics systems may shift in the future and what it means to play with data.

Learning analytics focuses on using existing accumulated learning data through analysis related techniques to provide appropriate information to learners and facilitating learners to adjust their learning strategies (personalization and adaptation) in improving learning effectiveness. Through learning analytics, activities of teaching, learning, and management processes will be significantly changed. Although learning analytics has been considered one of the six critical trends (ebook, mobile learning, augmented reality, game-based learning, natural user interface, and learning analytics) of high education in the near future, there are only few studies focusing on exploring learning analytics related issues. To address this void, this thesis aims for analyzing and designing a personalized mobile learning analytics system that is a mobile application prototyping system developed by incorporating concepts of learning analytics and mobile learning. User requirements of the prototyping system are collected by database analysis (LMS platform), focus groups (users of mobile learning), and expert interviews (experts and practitioners in e-learning domain). Those collected requirements have been translated into system functionalities and then they have been appropriately implemented through adequate system development tools. Finally, the implemented prototyping system has been tested and validated by experts and practitioners in e-learning domain. Therefore, this study has significant contributions on conducting an in-depth system analysis and design relating to mobile learning with learning analytics and validating the feasibility of learning analytics by the prototyping approach. We suggest that academics and practitioners can conduct more in-depth research on investigating learning analytics related issues based on the findings of this study.

In der Netzwerkgesellschaft des 21. Jahrhunderts gilt die kollaborative Verteilung und Nutzung von Information und Wissen als Schlüsselstrategie für den webbasierten Informations- und Wissenstransfer. Durch die technologischen Möglichkeiten werden technische Zugangsbarrieren weitestgehend überwunden und traditionelle Formen der Wissensvermittlung durch moderne webbasierte Lernumgebungen ergänzt. Der Umgang mit kollaborativen Lehr- und Lernszenarien im dynamischen Informations- und Wissenstransfer bildet die Grundlage für den soziokulturellen Fortschritt innerhalb der Bildungsforschung. Der Schwerpunkt dieser Arbeit lag auf der strukturellen und relationalen Analyse sozialer Organisationsstrukturen innerhalb von Wissensnetzwerken. Ziel war es, Einflussfaktoren offenzulegen, die sich auf das Innovations- und Distributionspotential von Information und Wissen innerhalb von kollaborativen Wissensnetzwerken auswirken. Es wurden dazu Interaktionsprozesse von Teilnehmern innerhalb von Diskussionsforen am Beispiel der Lernplattform OPAL – dem aktuell populärsten Lernmanagementsystem in der Hochschulbildung Sachsens, Deutschland – untersucht. Unter der Annahme, dass soziale Interaktion besonders im Umgang mit kollaborativen Medien den Bildungsablauf und der Aufbau von Wissensnetzwerken die Lehr- und Lernprozesse beeinflusst, wurden in dieser Arbeit die strukturellen Bedingungen des kollaborativen Wissensnetzwerkes in OPAL exploriert und soziale Rollenkonstrukte relational identifiziert, um die Auswirkungen kollaborativer Aktivitäten auf den Informations- und Wissenstransfer in Wissensnetzwerken zu erklären. Es wurden vornehmlich beziehungsorientierte kommunikationstheoretische Modelle zugrunde gelegt und relationale Forschungsmethoden wie SNA (Social Network Analysis) und DNA (Dynamic Network Analysis) angewandt, um eine Basis für die weiterführende Implementierung sozial vernetzter Lehr- und Lernstrategien in der Bildungsforschung zu schaffen. […] / In the network society of the 21st century, a key strategy for web-based exchange of information and knowledge is their collaborative distribution and use. Technical hurdles of access are mostly being overcome with technological advances and traditional forms of passing on knowledge are being complemented by modern, e-learning environments. Within research into education, the foundation for socio-cultural progress is formed by involvement with collaborative teaching and learning scenarios in a dynamic exchange of information and knowledge. The emphasis of this work lay in the analysis of structures and relationships of social organisations within knowledge networks. The aim was to describe the exchange of information and knowledge in collaborative learning systems and to explore its influence on the potential for innovation and distribution of information and knowledge. A study was undertaken of the interaction of participants in discussion forums as exemplified by the learning platform OPAL – currently the most popular learning management system in secondary school education in Saxony, Germany. On the assumption that social interaction, particularly involving collaborative media, the progress of education and the construction of knowledge networks do influence teaching and learning processes, this work explored the structural conditions of OPAL's collaborative knowledge network and identified relationships between social role constructs in order to explain the effect of collaborative activities on the process of diffusion of information and knowledge in knowledge networks. Primarily the study was based on relationship oriented sociological models and communication theory models, and research methods for relationships, including SNA (Social Network Analysis) and DNA (Dynamic Network Analysis) were applied, so as to create a basis for further implementation of social network teaching and learning strategies in educational research. [...]

The evolution of structured data from simple rows and columns on a spreadsheet to more complex unstructured data such as tweets, videos, voice, and others, has resulted in a need for more adaptive analytical platforms. It is estimated that upwards of 80% of data on the Internet today is unstructured. There is a drastic need for crowdsourcing platforms to perform better in the wake of the tsunami of data. We investigated the employment of a monitoring service which would allow the system take corrective action in the event the results were trending in away from meeting the accuracy, budget, and time SLOs. Initial implementation and system validation has shown that taking corrective action generally leads to a better success rate of reaching the SLOs. Having a system which can dynamically adjust internal parameters in order to perform better can lead to more harmonious interactions between humans and machine algorithms and lead to more efficient use of resources.

As estrategias de passes têm sido sempre de interesse para a pesquisa de futebol. Desde os inícios do futebol, os técnicos tem usado olheiros, gravações de vídeo, exercícios de treinamento e feeds de dados para coletar informações sobre as táticas e desempenho dos jogadores. No entanto, a natureza dinâmica das estratégias de passes são bastante complexas para refletir o que está acontecendo dentro do campo e torna difícil o entendimento do jogo. Além disso, existe uma demanda crecente pela deteção de padrões e analise de estrategias de passes popularizado pelo tiki-taka utilizado pelo FC. Barcelona. Neste trabalho, propomos uma abordagem para abstrair as sequências de pases e agrupálas baseadas na geometria da trajetória da bola. Para analizar as estratégias de passes, apresentamos um esquema de visualização interátiva para explorar a frequência de uso, a localização espacial e ocorrência temporal das sequências. A visualização Frequency Stripes fornece uma visão geral da frequencia dos grupos achados em tres regiões do campo: defesa, meio e ataque. O heatmap de trajetórias coordenado com a timeline de passes permite a exploração das formas mais recorrentes no espaço e tempo. Os resultados demostram oito trajetórias comunes da bola para sequências de três pases as quais dependem da posição dos jogadores e os ângulos de passe. Demonstramos o potencial da nossa abordagem com utilizando dados de várias partidas do Campeonato Brasileiro sob diferentes casos de estudo, e reportamos os comentários de especialistas em futebol. / Passing strategies analysis has always been of interest for soccer research. Since the beginning of soccer, managers have used scouting, video footage, training drills and data feeds to collect information about tactics and player performance. However, the dynamic nature of passing strategies is complex enough to reflect what is happening in the game and makes it hard to understand its dynamics. Furthermore, there exists a growing demand for pattern detection and passing sequence analysis popularized by FC Barcelona’s tiki-taka. We propose an approach to abstract passing strategies and group them based on the geometry of the ball trajectory. To analyse passing sequences, we introduce a interactive visualization scheme to explore the frequency of usage, spatial location and time occurrence of the sequences. The frequency stripes visualization provide, an overview of passing groups frequency on three pitch regions: defense, middle, attack. A trajectory heatmap coordinated with a passing timeline allow, for the exploration of most recurrent passing shapes in temporal and spatial domains. Results show eight common ball trajectories for three-long passing sequences which depend on players positioning and on the angle of the pass. We demonstrate the potential of our approach with data from the Brazilian league under several case studies, and report feedback from a soccer expert.

abstract: Predictive analytics embraces an extensive area of techniques from statistical modeling to machine learning to data mining and is applied in business intelligence, public health, disaster management and response, and many other fields. To date, visualization has been broadly used to support tasks in the predictive analytics pipeline under the underlying assumption that a human-in-the-loop can aid the analysis by integrating domain knowledge that might not be broadly captured by the system. Primary uses of visualization in the predictive analytics pipeline have focused on data cleaning, exploratory analysis, and diagnostics. More recently, numerous visual analytics systems for feature selection, incremental learning, and various prediction tasks have been proposed to support the growing use of complex models, agent-specific optimization, and comprehensive model comparison and result exploration. Such work is being driven by advances in interactive machine learning and the desire of end-users to understand and engage with the modeling process. However, despite the numerous and promising applications of visual analytics to predictive analytics tasks, work to assess the effectiveness of predictive visual analytics is lacking. This thesis studies the current methodologies in predictive visual analytics. It first defines the scope of predictive analytics and presents a predictive visual analytics (PVA) pipeline. Following the proposed pipeline, a predictive visual analytics framework is developed to be used to explore under what circumstances a human-in-the-loop prediction process is most effective. This framework combines sentiment analysis, feature selection mechanisms, similarity comparisons and model cross-validation through a variety of interactive visualizations to support analysts in model building and prediction. To test the proposed framework, an instantiation for movie box-office prediction is developed and evaluated. Results from small-scale user studies are presented and discussed, and a generalized user study is carried out to assess the role of predictive visual analytics under a movie box-office prediction scenario. / Dissertation/Thesis / Doctoral Dissertation Engineering 2017

As estrategias de passes têm sido sempre de interesse para a pesquisa de futebol. Desde os inícios do futebol, os técnicos tem usado olheiros, gravações de vídeo, exercícios de treinamento e feeds de dados para coletar informações sobre as táticas e desempenho dos jogadores. No entanto, a natureza dinâmica das estratégias de passes são bastante complexas para refletir o que está acontecendo dentro do campo e torna difícil o entendimento do jogo. Além disso, existe uma demanda crecente pela deteção de padrões e analise de estrategias de passes popularizado pelo tiki-taka utilizado pelo FC. Barcelona. Neste trabalho, propomos uma abordagem para abstrair as sequências de pases e agrupálas baseadas na geometria da trajetória da bola. Para analizar as estratégias de passes, apresentamos um esquema de visualização interátiva para explorar a frequência de uso, a localização espacial e ocorrência temporal das sequências. A visualização Frequency Stripes fornece uma visão geral da frequencia dos grupos achados em tres regiões do campo: defesa, meio e ataque. O heatmap de trajetórias coordenado com a timeline de passes permite a exploração das formas mais recorrentes no espaço e tempo. Os resultados demostram oito trajetórias comunes da bola para sequências de três pases as quais dependem da posição dos jogadores e os ângulos de passe. Demonstramos o potencial da nossa abordagem com utilizando dados de várias partidas do Campeonato Brasileiro sob diferentes casos de estudo, e reportamos os comentários de especialistas em futebol. / Passing strategies analysis has always been of interest for soccer research. Since the beginning of soccer, managers have used scouting, video footage, training drills and data feeds to collect information about tactics and player performance. However, the dynamic nature of passing strategies is complex enough to reflect what is happening in the game and makes it hard to understand its dynamics. Furthermore, there exists a growing demand for pattern detection and passing sequence analysis popularized by FC Barcelona’s tiki-taka. We propose an approach to abstract passing strategies and group them based on the geometry of the ball trajectory. To analyse passing sequences, we introduce a interactive visualization scheme to explore the frequency of usage, spatial location and time occurrence of the sequences. The frequency stripes visualization provide, an overview of passing groups frequency on three pitch regions: defense, middle, attack. A trajectory heatmap coordinated with a passing timeline allow, for the exploration of most recurrent passing shapes in temporal and spatial domains. Results show eight common ball trajectories for three-long passing sequences which depend on players positioning and on the angle of the pass. We demonstrate the potential of our approach with data from the Brazilian league under several case studies, and report feedback from a soccer expert.

Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2017-04-10T18:23:48Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação de Mestrado_PROPAD_UFPE_Ijon Santos.pdf: 3007544 bytes, checksum: c798b542d8e9f98334c33dbb694d633e (MD5) / Made available in DSpace on 2017-04-10T18:23:48Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação de Mestrado_PROPAD_UFPE_Ijon Santos.pdf: 3007544 bytes, checksum: c798b542d8e9f98334c33dbb694d633e (MD5) Previous issue date: 2016-05-31 / A presente dissertação busca explicar os fatores condicionantes para a adoção efetiva de Big Data e Business Analytics por parte das Organizações Privadas de Pernambuco em termos de atitudes, aptidão e resultados. Para esse fim, um apanhado teórico-conceitual é reunido sobre o avanço no tráfego de dados na era da Revolução Digital e a predisposição das organizações em se apropriar das tecnologias compatíveis de informação e comunicação que transformam o modus faciendi e o modus pensandi da sociedade. No corpus de pesquisa se destacam duas teorias fundamentadoras: A Teoria da Mediação Cognitiva e a Teoria da Estruturação (base do Modelo de Estruturação de Tecnologia). Ambas exploradas no cerne da questão da dualidade tecnologia-uso, em que o convívio com artefatos tecnológicos em interação com as ações humanas inicia um processo mútuo de influência entre esses elementos, constituindo uma nova modalidade de mediação denominada Hipercultura. Em um método quantitativo de pesquisa, tais construtos serão relacionados entre si e investigados em 183 líderes estratégicos pernambucanos, além de comparados com indivíduos equivalentes de outras naturalidades e nacionalidades por meio de um formulário especialmente preparado. Os resultados obtidos indicam o nível de prontidão das empresas sobre este tema e a relação com o sucesso ou fracasso, quando considerados os níveis de hipercultura, de capacidade analítica e das condições de Tecnologias de Informação e Comunicação existentes nas empresas. Ao final do estudo, são levantados possíveis desdobramentos para os conceitos introduzidos. / The present dissertation seeks to explain the determining factors for the effective adoption of Big Data and Business Analytics on Pernambuco’s Private Organization in terms of attitudes, skills and results. For this purpose, a theoretical-conceptual caught is gathered about the progress in data traffic in the Digital Revolution age and the willingness of organizations to take ownership of supported technologies of information and communication that transform the modus faciendi and the modus pensandi of the society. In the research corpus stand two essential theories: The Cognitive Mediation Networks Theory and the Structuration Theory (base Structurational Model of Technology). Both explored the matter of duality-use technology, in which the interaction with technological artifacts interacting with human actions starts a process of mutual influence between these elements, constituting a new form of mediation called Hyperculture. In a quantitative search method, such constructs will be related to each other and investigated 183 strategic leaders from Pernambuco, and equivalents compared to individuals with other places of birth and nationality using a specially prepared form. The results may indicate the level of readiness of the companies on this issue and if there is, or not, relation with success or failure, when considering the hyperculture levels, analytical capacity and conditions of information and communication technologies in the existing companies. At the end of the study a several possible developments, implications, and applications for the concepts introduced are presented.

This thesis deals with the state of the web analytics in the marketing research of an academic institution. The theoretical part summarises the state of the (online) marketing in marketing activities of the academic institution and substantiates the importance of the analysis of the attendance of academic institution's web pages. It also submits basic conclusions for choosing the suitable analytic tool. In the applicative part the thesis analyses the traffic of web pages of Faculty of Management in 2010 and suggests actions leading to the higher satisfaction of web pages visitors and fulfilment of web conversion goals.

This thesis looks into problematic of data originating from visits of a company websites. It is partly devoted to web analytics and Business Intelligence. The aim was to create a tool for transforming and saving these data, their analysis and reporting. The product of this thesis was created for a management of a company specifically by their requests. It was made to support managerial decisions in creating a successful web strategy.