Sensemaking (i.e. the process of deriving meaning from complex information to make decisions) is often cited as an important and challenging activity for collaborative technology. A key element to the success of collaborative sensemaking is effective coordination and communication within the team. It requires team members to divide the task load, communicate findings and discuss the results. Sensemaking is one of the human activities involved in visual analytics (i.e. the science of analytical reasoning facilitated by interactive visual interfaces). The inherent complexity of the sensemaking process imposes many challenges for designers. Therefore, providing effective tool support for collaborative sensemaking is a multifaceted and complex problem. Such tools should provide support for visualization as well as communication and coordination. Analysts need to organize their findings, hypotheses, and evidence, share that information with their collaborators, and coordinate work activities amongst members of the team. Sharing externalizations (i.e. any information related to the course of analysis such as insights, hypotheses, to-do lists, reminders, etc recorded in the form of note/ annotation) could increase awareness and assist team members to better communicate and coordinate their work activities. However, we currently know very little about how to provide tool support for this sort of sharing. This thesis is structured around three major phases. It consists of a series of studies to better understand collaborative Visual Analytics (VA) processes and challenges, and empirically evaluate design ideas for supporting collaborative sensemaking. I investigate how collaborative sensemaking can be supported during visual analytics by a small team of collocated analysts. In the first phase of this research, I conducted an observational study to better understand the process of sensemaking during collaborative visual analytics as well as identify challenges and further requirements. This study enabled me to develop a deeper understanding of the collocated collaborative visual analytics process and activities involved. I found that record-keeping plays a critical role in the overall process of collaborative visual analytics. Record-keeping involves recording any information related to the analysis task including visualization snapshots, system states, notes, annotations and any other material for further analysis such as reminders and to-do lists. Based on my observations, I proposed a characterization of activities during collaborative visual analytics that encompasses record-keeping as one of the main activities. In addition, I characterized notes according to their content, scope, and usage, and described how they fit into a process of collaborative data analysis. Then, I derived guidelines to improve the design of record-keeping functionality for collocated collaborative visual analytics tools. One of the main design implications of my observational study was to integrate record-keeping functionality into a collaborative visual analytics tool. In order to examine how this feature should be integrated with current VA tools, in the second phase of this research, I designed, developed and evaluated a tool, CoSpaces (Collaborative Spaces), tailor-made for collocated collaborative data analysis on large interactive surfaces. Based on the result of a user study with this tool, I characterized users' actions on visual record-keeping as well as their key intentions for each action. In addition, I proposed further design guidelines such as providing various views of recorded material, showing manually saved rather than automatically saved items by default, enabling people to review collaborators' work unobtrusively, and automatically recommending items related to a user's analytical task. In the third phase, I took supporting record-keeping activities in the context of collaborative sensemaking a step further to investigate how this support should be designed to facilitate collaboration. To this end, I explored how automatic discovery and linking of common work can be employed within a ``collaborative thinking space'' (i.e. a space to enable analysts to record and organize findings, evidence, and hypotheses, also facilitate the process of sharing findings amongst collaborators), to facilitate synchronous collaborative sensemaking activities in visual analytics. The main goal of this phase was to provide an environment for analysts to record, organize, share and connect externalizations. I expected that this would increase awareness among team members and in turn would enhance communication and coordination of activities. I designed, implemented and evaluated a new tool, CLIP (Collaborative Intelligence Pad), that extends earlier thinking spaces by integrating new features that reveal relationships between collaborators' findings. Comparing CLIP versus a baseline tool demonstrated that linking collaborators' work led to significant improvement in analytical outcomes at a collaborative intelligence task. Groups using CLIP were also able to more effectively coordinate their work, and held more discussion of their findings and hypotheses. Based on this study, I proposed design guidelines collaborative VA tools. In summary, I contribute an understanding for how analysts use VA tools during collocated collaboration. Through a series of observational user studies, I investigated how we can better support this complex process. More specifically, I empirically studied recording and sharing of analytical results. For this purpose, I implemented and evaluated two systems to be able to understand the effects of these tools on collaboration mechanics. These user studies along with various literature surveys on each specific topic resulted in a collection of guidelines for supporting and sharing externalizations. In addition, I proposed and evaluated several mechanisms to increase awareness among team members, resulting in more effective coordination and communication during the collaborative sensemaking process. The most novel contributions of this research are the identification and subsequent characterization of note taking behaviours as an important component of visual data exploration and analysis. Moreover, the design and evaluation of CLIP, providing preliminary evidence in support of automatically identifying and presenting relationships between collaborators' findings. / Graduate / 0984 / narges.mahyar@gmail.com

Índice del video: Daniel Navarrete (00:19 - 23:50); Daniela Sarzosa (24:00 - 47:12); Jorge Maldonado (48:30-1:13:30); Jimmy Pérez (1:13:30 - 1:13:55) / Primera meetup del 2019 de la comunidad Learning Analytics Perú, donde se conversó sobre experiencias de éxito en el uso de herramientas, estrategias y métodos que han conducido a resultados satisfactorios en la aplicación estratégica de los datos en Educación Superior, de la mano de profesionales de Perú, Colombia y Ecuador... Evento realizado el 9 de enero de 2019 en la Universidad Peruana de Ciencias Aplicadas, campus San Isidro, auditorio Luis Bustamante.

Accede a la filmación de la conferencia en : http://hdl.handle.net/10757/624838 / Presentación realizada en el marco de la primera meetup del 2019 de la comunidad Learning Analytics Perú, donde se conversó sobre experiencias de éxito en el uso de herramientas, estrategias y métodos que han conducido a resultados satisfactorios en la aplicación estratégica de los datos en Educación Superior, de la mano de profesionales de Perú, Colombia y Ecuador.

Accede a la filmación de la conferencia en : http://hdl.handle.net/10757/624838 / Presentación realizada en el marco de la primera meetup del 2019 de la comunidad Learning Analytics Perú, donde se conversó sobre experiencias de éxito en el uso de herramientas, estrategias y métodos que han conducido a resultados satisfactorios en la aplicación estratégica de los datos en Educación Superior, de la mano de profesionales de Perú, Colombia y Ecuador.

Parte de la conferencia: Experiencias exitosas en el uso de learning analytics en educación superior. Accede a la filmación de la conferencia en : http://hdl.handle.net/10757/624838 / Presentación realizada en el marco de la primera meetup del 2019 de la comunidad Learning Analytics Perú, donde se conversó sobre experiencias de éxito en el uso de herramientas, estrategias y métodos que han conducido a resultados satisfactorios en la aplicación estratégica de los datos en Educación Superior, de la mano de profesionales de Perú, Colombia y Ecuador.

Parte de la conferencia: Experiencias exitosas en el uso de learning analytics en educación superior. Accede a la filmación de la conferencia en : http://hdl.handle.net/10757/624838 / Presentación realizada en el marco de la primera meetup del 2019 de la comunidad Learning Analytics Perú, donde se conversó sobre experiencias de éxito en el uso de herramientas, estrategias y métodos que han conducido a resultados satisfactorios en la aplicación estratégica de los datos en Educación Superior, de la mano de profesionales de Perú, Colombia y Ecuador.

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O mercado consumidor passou por diversas transformações ao longo do tempo devido principalmente à evolução tecnológica. A evolução tecnológica proporcionou ao consumidor a possibilidade de escolher por produtos e marcas, e permite a oportunidade de colaborar e influenciar a opinião de outros consumidores através do compartilhamento de experiências, principalmente através da utilização de plataformas digitais. O CRM (gerenciamento do relacionamento com o consumidor) é a forma utilizada pelas empresas para conhecerem o consumidor e criar um relacionamento satisfatório entre empresa e consumidor. Esse relacionamento tem o intuito de satisfazer e fidelizar o consumidor, evitando que ele deixe de consumir a marca e evitando que ele influencie negativamente outros consumidores. O e-CRM é o gerenciamento eletrônico do relacionamento com o consumidor, que possui todas as tradicionais características do CRM, porém com o incremento do ambiente digital. O ambiente digital diminuiu a distância entre pessoas e empresas e se tornou um meio colaborativo de baixo custo de interação com o consumidor. Por outro lado, este é um meio onde o consumidor deixa de ser passivo e se torna ativo, o que o torna capaz de influenciar não só um pequeno grupo de amigos, mas toda uma rede de consumidores. A digital analytics é a medição, coleta, análise e elaboração de relatórios de dados digitais para os propósitos de entendimento e otimização da performance em negócios. A utilização de dados digitais auxilia no desenvolvimento do e-CRM através da compreensão do comportamento do consumidor em um ambiente onde o consumidor é ativo. O ambiente digital permite um conhecimento mais detalhado dos consumidores, baseado não somente nos hábitos de compra, mas também nos interesses e interações. Este estudo tem como objetivo principal compreender como as empresas aplicam os conceitos do e-CRM em suas estratégias de negócios, compreendendo de que forma a digital analytics contribui para o desenvolvimento do e-CRM, e compreendendo como os fatores críticos de sucesso (humano, tecnológico e estratégico) impactam na implantação e desenvolvimento do e-CRM. Quatro empresas de diferentes segmentos foram estudadas através da aplicação de estudo de caso. As empresas buscam cada vez mais explorar as estratégias de e-CRM no ambiente digital, porém existem limitações identificadas devido à captação, armazenamento e análise de informações multicanais, principalmente considerando os canais digitais. Outros fatores como o apoio da alta direção e a compreensão de funcionários para lidar com estratégias focadas no consumidor único também foram identificados neste estudo. O estudo foi capaz de identificar as informações mais relevantes para a geração de estratégias de gerenciamento eletrônico do relacionamento com o consumidor e identificou os aspectos mais relevantes dos fatores críticos de sucesso. / The consumer market has undergone several transformations over time mainly due to technological developments. Technological progress has given the consumer a choice of products and brands, allowing the opportunity to collaborate and influence the opinion of other consumers through the sharing of experiences, specially by the use of digital platforms. The CRM (customer relationship management) is the form used by companies to know the consumer and establish a satisfactory relationship between both. This relationship aims to satisfy and retain consumers, preventing it ceases to consume the brand and preventing it negatively influence on others. The e-CRM is the electronic management of the relationship with the consumer, which has all the traditional CRM features, which increase the digital environment. The digital environment reduced the distance between consumer and companies becoming a collaborative low-cost way of interaction with the consumer. On the other hand, this is a medium where the consumer is no longer passive and becomes active, which makes it able to influence not only a small group of friends, but a whole network of consumers. The digital analytics is the measurement, collection, analysis and preparation of digital data reports for the purposes of understanding and optimizing business performance. The use of digital data helps in the development of e-CRM through understanding consumer behavior in an environment where the consumer is active. The digital environment allows a more detailed knowledge of consumers, based not only on buying habits, but also on the interests and interactions. This study aims to understand how companies apply the concepts of e-CRM in their business strategies, including how the digital analytics contributes to the development of e-CRM, and understanding how the critical success factors (human, technological and strategic) impact in the implementation and development of e-CRM. Four companies from different segments were studied through study case application. Nowadays, Companies are increasingly looking to explore the e-CRM strategies in the digital environment, but there are limitations identified due to capture, storage and analysis of multi-channel information, especially considering digital channels. Other factors were also identified in this study, such as the support of senior management and the understanding of employees to deal with strategies focused on single consumer. The study was able to identify the most relevant information for the generation of electronic management strategies relationship with the consumer and identified the most relevant aspects of the critical success factors.

Video surveillance systems have been commonly used in transportation systems to support traffic monitoring, speed estimation, and incident detection. However, there are several challenges in developing and deploying such systems, including high development and maintenance costs, bandwidth bottleneck for long range link, and lack of advanced analytics. In this thesis, I leverage current wireless, video camera, and analytics technologies, and present a wireless traffic monitoring system. I first present an overview of the system. Then I describe the site investigation and several test links with different hardware/software configurations to demonstrate the effectiveness of the system. The system development process was documented to provide guidelines for future development. Furthermore, I propose a novel speed-estimation analytics algorithm that takes into consideration roads with slope angles. I prove the correctness of the algorithm theoretically, and validate the effectiveness of the algorithm experimentally. The experimental results on both synthetic and real dataset show that the algorithm is more accurate than the baseline algorithm 80% of the time. On average the accuracy improvement of speed estimation is over 3.7% even for very small slope angles.

The purpose of this dissertation was to examine how managers' judgments from an internal auditor's recommendation are influenced by some aspects of newer data sources and the related visualizations. This study specifically examined how managers' judgments from an internal auditor's recommendation are influenced by the (1) supportiveness of non-financial data with the internal auditor's recommendation and (2) evaluability of visual representations for non-financial data used to communicate the recommendation. This was investigated in a setting where financial data does not support the internal auditor's recommendation. To test my hypotheses, I conducted an experiment that uses an inventory write-down task to examine the likelihood that a manager agrees with an internal auditor's inventory write-down recommendation. This task was selected as it requires making a prediction and both financial and newer non-financial data sources are relevant to inform this judgment. The study was conducted with MBA students who proxy for managers in organizations. Evaluability of visual representations was operationalized as the (1) proximity of financial and non-financial graphs, and (2) type of non-financial graph as requiring a length judgment or not. This dissertation contributes to accounting literature and the internal auditing profession. First, I contribute to recent experimental literature on data analytics by providing evidence that newer non-financial data sources will be integrated into managers' judgments even when financial data is inconsistent. However, I also identified that the effectiveness of appropriate agreement with an internal auditor's recommendation depends on the evaluability of the visualizations for non-financial data. Second, I expand on the literature that examines managers' agreement with recommendations from internal auditors by examining an unexplored yet relevant context of using newer non-financial data sources and communicating these results. Specifically, I identified how the evaluability of visual representations for non-financial data interacts with the supportiveness of non-financial data with the internal auditor's recommendation to create differences in managers' agreement with the recommendation. I also identified confidence in the internal auditor's recommendation as an explanatory variable in some situations. My findings also have practical value for the internal auditing profession to understand the importance of appropriate visualizations in audit reporting.