Evaluating human-centered approaches for geovisualization

Working with two small group of domain experts I evaluate human-centered approaches to application development which are applicable to geovisualization, following an ISO13407 taxonomy that covers context of use, eliciting requirements, and design. These approaches include field studies and contextual analysis of subjects' context; establishing requirements using a template, via a lecture to communicate geovisualization to subjects and by communicating subjects' context to geovisualization experts with a scenario; autoethnography to understand the geovisualization design process; wireframe, paper and digital interactive prototyping with alternative protocols; and a decision making process for prioritising application improvement. I find that the acquisition and use of real user data is key; that a template approach and teaching subjects about visualization tools and interactions both fail to elicit useful requirements for a visualization application. Consulting geovisualization experts with a scenario of user context and samples of user data does yield suggestions for tools and interactions of use to a visualization designer. The complex and composite natures of both visualization and human-centered domains, incorporating learning from both domains, with user context, makes design challenging. Wireframe, paper and digital interactive prototypes mediate between the user and visualization domains successfully, eliciting exploratory behaviour and suggestions to improve prototypes. Paper prototypes are particularly successful at eliciting suggestions and especially novel visualization improvements. Decision-making techniques prove useful for prioritising different possible improvements, although domain subjects select data-related features over more novel alternative and rank these more inconsistently. The research concludes that understanding subject context of use and data is important and occurs throughout the process of engagement with domain experts, and that standard requirements elicitation techniques are unsuccessful for geovisualization. Engagement with subjects at an early stage with simple prototypes incorporating real subject data and moving to successively more complex prototypes holds the best promise for creating successful geovisualization applications

Advancing self-escape training : a needs analysis based on the National Academy of Sciences report "improving self-escape from underground coal mines."

"This report summarizes a needs analysis and actions taken by NIOSH based on the National Academy of Sciences recommendations specific to advancing self-escape training, with an emphasis on preparing rank-and-file mineworkers for self-escape. This report also provides the foundation for the practical guidance offered in its sister publication, the NIOSH Information Circular (IC) "Self-escape Core Competency Profile: Guidance for Improving Underground Coal Miners' Self-escape Competency" [NIOSH 2023], which offers an evidence-based self-escape competency framework derived from the results of this work." - NIOSHTIC-2NIOSHTIC no. 20067688Suggested citation: NIOSH [2023]. Advancing self-escape training: a needs analysis based on the National Academy of Sciences report, \u201cImproving Self-escape from Underground Coal Mines.\u201d By Hoebbel CL, Bellanca JL, Ryan ME, Brnich MJ. Pittsburgh PA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, DHHS (NIOSH) Publication No. 2023-134, https://doi.org/10.26616/NIOSHPUB2023134

Data science for buildings, a multi-scale approach bridging occupants to smart-city energy planning

In a context of global carbon emission reduction goals, buildings have been identified to detain valuable energy-saving abilities. With the exponential increase of smart, connected building automation systems, massive amounts of data are now accessible for analysis. These coupled with powerful data science methods and machine learning algorithms present a unique opportunity to identify untapped energy-saving potentials from field information, and effectively turn buildings into active assets of the built energy infrastructure.However, the diversity of building occupants, infrastructures, and the disparities in collected information has produced disjointed scales of analytics that make it tedious for approaches to scale and generalize over the building stock.This coupled with the lack of standards in the sector has hindered the broader adoption of data science practices in the field, and engendered the following questioning:How can data science facilitate the scaling of approaches and bridge disconnected spatiotemporal scales of the built environment to deliver enhanced energy-saving strategies?This thesis focuses on addressing this interrogation by investigating data-driven, scalable, interpretable, and multi-scale approaches across varying types of analytical classes. The work particularly explores descriptive, predictive, and prescriptive analytics to connect occupants, buildings, and urban energy planning together for improved energy performances.First, a novel multi-dimensional data-mining framework is developed, producing distinct dimensional outlines supporting systematic methodological approaches and refined knowledge discovery. Second, an automated building heat dynamics identification method is put forward, supporting large-scale thermal performance examination of buildings in a non-intrusive manner. The method produced 64\% of good quality model fits, against 14\% close, and 22\% poor ones out of 225 Dutch residential buildings. %, which were open-sourced in the interest of developing benchmarks. Third, a pioneering hierarchical forecasting method was designed, bridging individual and aggregated building load predictions in a coherent, data-efficient fashion. The approach was evaluated over hierarchies of 37, 140, and 383 nodal elements and showcased improved accuracy and coherency performances against disjointed prediction systems.Finally, building occupants and urban energy planning strategies are investigated under the prism of uncertainty. In a neighborhood of 41 Dutch residential buildings, occupants were determined to significantly impact optimal energy community designs in the context of weather and economic uncertainties.Overall, the thesis demonstrated the added value of multi-scale approaches in all analytical classes while fostering best data-science practices in the sector from benchmarks and open-source implementations

How to tell stories using visualization: strategies towards narrative visualization

Os benefícios da utilização das narrativas são desde há muito conhecidos e o seu potencial para simplificar conceitos, transmitir valores culturais e experiências, criar ligações emocionais e capacidade para ajudar a reter a informação tem sido explorado em diferentes áreas. As narrativas não são só a principal forma como as pessoas obtêm o sentido do mundo, mas também a forma mais fácil que encontrámos para partilhar informações complexas. Devido ao seu potencial, as narrativas foram recentemente abordadas na área da Visualização de Informação e do Conhecimento, muitas vezes apelidada de Visualização Narrativa. Esta questão é particularmente importante para os media, uma das áreas que tem impulsionado a investigação em Visualização Narrativa. A necessidade de incorporar histórias nas visualizações surge da necessidade de partilhar dados complexos de um modo envolvente. Hoje em dia somos confrontados com a elevada quantidade de informação disponível, um desafio difícil de resolver. Os avanços da tecnologia permitiram ir além das formas tradicionais de narrativa e de representação de dados, dando-nos meios mais atraentes e sofisticados para contar histórias. Nesta tese, exploro os benefícios da introdução de narrativas nas visualizações. Adicionalmente também exploro formas de combinar histórias com a visualizações e métodos eficientes para representar e dar sentido aos dados de uma forma que permite que as pessoas se relacionem com a informação. Esta investigação está bastante próxima da área do jornalismo, no entanto estas técnicas podem ser aplicadas em diferente áreas (educação, visualização científica, etc.). Para explorar ainda mais este tema foi adotada um avaliação que utiliza diferentes metodologias como a tipologia, vários casos de estudo, um estudo com grupos de foco, e ainda estudos de design e análise de técnicas.The benefits of storytelling are long-known and its potential to simplify concepts, convey cultural values and experiences, create emotional connection, and capacity to help retain information has been explored in di erent areas, such as journalism, education, marketing, and others. Narratives not only have been the main way people make sense of the world, but also the easiest way humans found out to share complex information. Due to its potential narratives have also recently been approached in the area of Information and Knowledge Visualization, several times being referred to as Narrative Visualization. This matter is also particularly important for news media, one of the areas that has been pushing the research on Narrative Visualization. The necessity to incorporate storytelling in visualizations arises from the need to share complex data in a way that is engaging. Nowadays we also have the challenge of the high amount of information available, which can be hard to cope with. Advances in technology have enabled us to go beyond the traditional forms of storytelling and representing data, giving us more attractive and sophisticated means to tell stories. In this dissertation, I explore the benefits of infusing visualizations with narratives. In addition I also present ways of combining storytelling with visualization and e cient methods to represent and make sense of data in a way that allows people to relate with the information. This research is closely related to journalism, but these techniques can be applied to completely di erent areas (education, scientific visualization, etc.). To further explore this topic a mixedmethod evaluation that consists of a typology, several case studies and a focus group study was chosen, as well as design studies and techniques review. This dissertation is intended to contribute to the evolving understanding of the field of narrative visualization

Intelligent Systems

This book is dedicated to intelligent systems of broad-spectrum application, such as personal and social biosafety or use of intelligent sensory micro-nanosystems such as "e-nose", "e-tongue" and "e-eye". In addition to that, effective acquiring information, knowledge management and improved knowledge transfer in any media, as well as modeling its information content using meta-and hyper heuristics and semantic reasoning all benefit from the systems covered in this book. Intelligent systems can also be applied in education and generating the intelligent distributed eLearning architecture, as well as in a large number of technical fields, such as industrial design, manufacturing and utilization, e.g., in precision agriculture, cartography, electric power distribution systems, intelligent building management systems, drilling operations etc. Furthermore, decision making using fuzzy logic models, computational recognition of comprehension uncertainty and the joint synthesis of goals and means of intelligent behavior biosystems, as well as diagnostic and human support in the healthcare environment have also been made easier

Visualising player data for video game designers

The collection and analysis of videogame players' actions in the game world, known as game telemetry, is a common technique for understanding the behaviour of players. This process, known as Game Analytics, often uses data visualisation to allow designers to manually analyse features of the data. Heatmap visualisation, a grid-based visualisation showing how often an event occurs across the game world (e.g. �ring of weapons), is used widely in the games industry for visualising aggregated data, but has limitations when used to classify player behaviour at an individual or group level. Existing works using clustering to identify player behaviour yield results that must be interpreted by an expert, a problem acknowledged by existing research. Motivated by these limitations, this work presents the novel application of dendrogram visualisation as a means to interpret large datasets of heatmaps, through the use of hierarchical clustering, to aid designers in exploring and analysing player behaviour. This allows an intuitive and well- understood visualisation technique (heatmaps) to be used for cluster analysis, presenting intelligible results to a game designer, in a format they are familiar with. To evaluate dendrograms as a design tool, a system was designed and implemented to visualise player data, using heatmaps, with hierarchical clustering being performed on these heatmaps, the results displayed as a dendrogram. A feasibility study was con- ducted with a set of game designers, to understand the opportunities and limitations of dendrograms as a game analytics tool. The results a�rmed the utility of heatmaps for visualising aggregate data, but visual complexity increases in large quantities. Den- drograms were found to be initially di�cult to read, but showed promise for analysing large sets of data and guiding the designer to interesting areas of the data, provided they could \drill down" into the base data (heatmaps). In light of these �ndings, a us- ability study was designed and conducted with a set of 40 game development students, where they were presented with realistic game design scenarios, and asked to �nd an- swers to analytics questions using heatmaps and dendrograms. The results showed that whilst dendrograms were initially di�cult to understand, they were used to successfully explore and understand cluster relationships, with participants providing the correct answers grounded in the data. Furthermore participants reiterated the need to explore the base data (heatmaps) to understand the cluster relationships of the dendrogram. This work concludes that dendrograms represent a viable and useful tool for identifying interesting behaviour patterns within a heatmap dataset. Whilst some familiarity is required with the tool, it is possible to use dendrograms to explore behaviour clusters within a large dataset, and this work presents a solution to the limitations of analysing player behaviour through the use of heatmaps in large datasets. This work highlights a number of avenues for future work, such as deploying and studying dendrograms in a game production setting, or evaluating the dendrogram visualisation in di�erent game genres

Community college students\u27 plant biodiversity learning experience in an introductory biology course: exploring the value added by using a CD-ROM to develop inquiry lessons

This study examined the value added to standard textbook-based instruction of plant biodiversity by the use of the exemplary interactive CD-ROM, Conserving Earth’s Biodiversity. This CD-ROM features renowned conservation figure E.O. Wilson. The setting of the research was an introductory biology course in a rural public community college in the Deep South. Six participants were purposively selected to represent three levels of achievement and two groups, the CD-ROM group (exposed to CD-ROM in addition to the textbook) and the textbook group (only course textbook). Students experienced lecture-based, textual, virtual, and real experiences, and examined their ability to understand biodiversity-related concepts and to pursue guided-inquiry questions about local plant biodiversity. Their performance was assessed through activities, quizzes, concept maps, interviews, surveys, and students’ presentations. This study led to three main findings. First, use of the CD-ROM, in addition to the textbook, allowed students to form a well-rounded grasp of plant biodiversity. Second, use of the CD-ROM enhanced the development of inquiries on local plant biodiversity and the metacognitive phase of assigning roles for local plant diversity. Third, the Plant Biodiversity Literacy Rubric [PBLR] was developed, based upon the history of the concept of biodiversity and was used to evaluate students’ progress by assigning them to various levels of understanding during the study. The students in the CD-ROM group gained a broader perspective of plant biodiversity-related concepts, such as levels of biodiversity, hot spots, genetic diversity, food plant diversity, and threats to biodiversity. The CD-ROM was never detrimental to the learning process. They were more self-directed in their development of inquiries, felt more confident about their presentations, and were more metacognitive during their inquiries. Performance on specific activities such as the essay and The Golden List of Species suggested an enhanced cognitive-behavioral/affective experience for students in the CD-ROM group. The PBLR is an exportable instrument, which may allow ecology educators at all levels to assess student’s levels of understanding in a sensitive way. At this time, it is critical to gauge effective understanding of plant biodiversity and ecology education, as it is vital to the survival and well-being of life on Earth