Designing Improved Sediment Transport Visualizations

Monitoring, or more commonly, modeling of sediment transport in the coastal environment is a critical task with relevance to coastline stability, beach erosion, tracking environmental contaminants, and safety of navigation. Increased intensity and regularity of storms such as Superstorm Sandy heighten the importance of our understanding of sediment transport processes. A weakness of current modeling capabilities is the ability to easily visualize the result in an intuitive manner. Many of the available visualization software packages display only a single variable at once, usually as a two-dimensional, plan-view cross-section. With such limited display capabilities, sophisticated 3D models are undermined in both the interpretation of results and dissemination of information to the public. Here we explore a subset of existing modeling capabilities (specifically, modeling scour around man-made structures) and visualization solutions, examine their shortcomings and present a design for a 4D visualization for sediment transport studies that is based on perceptually-focused data visualization research and recent and ongoing developments in multivariate displays. Vector and scalar fields are co-displayed, yet kept independently identifiable utilizing human perception\u27s separation of color, texture, and motion. Bathymetry, sediment grain-size distribution, and forcing hydrodynamics are a subset of the variables investigated for simultaneous representation. Direct interaction with field data is tested to support rapid validation of sediment transport model results. Our goal is a tight integration of both simulated data and real world observations to support analysis and simulation of the impact of major sediment transport events such as hurricanes. We unite modeled results and field observations within a geodatabase designed as an application schema of the Arc Marine Data Model. Our real-world focus is on the Redbird Artificial Reef Site, roughly 18 nautical miles offshor- Delaware Bay, Delaware, where repeated surveys have identified active scour and bedform migration in 27 m water depth amongst the more than 900 deliberately sunken subway cars and vessels. Coincidently collected high-resolution multibeam bathymetry, backscatter, and side-scan sonar data from surface and autonomous underwater vehicle (AUV) systems along with complementary sub-bottom, grab sample, bottom imagery, and wave and current (via ADCP) datasets provide the basis for analysis. This site is particularly attractive due to overlap with the Delaware Bay Operational Forecast System (DBOFS), a model that provides historical and forecast oceanographic data that can be tested in hindcast against significant changes observed at the site during Superstorm Sandy and in predicting future changes through small-scale modeling around the individual reef objects

Information visualization as creative nonfiction

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Comparative Media Studies, 2013.Cataloged from PDF version of thesis. "June 2013."Includes bibliographical references (p. 86-88).Information visualizations are an important means through which we communicate knowledge. By considering visualizations as data-driven narratives, this thesis uses narrative thinking as an orienting concept to support the production and evaluation of information visualizations. It proposes a set of guides that are central to future developments in the visualization of information through the analysis of historical examples and a design-based research process resulting in a system called the Royal Society Network. This thesis investigates the themes of various types of objectivity, the layering of quantitative and qualitative methods, the parallel relationship between investigation and visualization, and the graphical nature of statistical thinking. It then identifies transparency, hybridity, and investigation as the central concepts to visualization, where transparency is the communication of underlying structures to end users and is expressed through the building of interface elements as equal components to visualization, the recording and visual incorporation of usage patterns, and the representation of uncertainty; where hybridity is-in terms of both method and form-expressed through the use of quantitative and qualitative methods to drive visualizations forward and the use of multiple graphical forms to aid in understanding and providing contextual information; and where the investigative quality of visualizations is based on the coordination of grain size and axis of representation with the author's line of inquiry.by Jia Zhang.S.M

Extending the Glue Visualization Tool with Biological Data-Types

Glue is a data visualization tool designed for exploratory analysis that allows users to interactively explore relationships and patterns in large multidimensional datasets. Users can construct scatter plots and histograms, select regions of interest, and have their selections propagated across other visualizations and even across multiple files. This powerful functionality, known as data brushing, is immensely useful in teasing out hidden relationships in large complex datasets. Originally developed for astronomical information, we have subsequently extended its use with common biological data-types and visualizations. This project will present and discuss the addition of features designed for visualizing longitudinal time-series datasets and genetic sequences, both of which are common data-types in biological processes. These features will be illustrated in a research case study investigating how sequence variants of the human immunodeficiency virus type 1 (HIV-1) affect clinical outcomes. The implemented features will be discussed in the context of alternative solutions and broad impact.M.S., Biomedical Engineering -- Drexel University, 201

Interactions in Visualizations to Support Knowledge Activation

Humans have several exceptional abilities, one of which is the perceptual tasks of their visual sense. Humans have the unique ability to perceive data and identify patterns, trends, and outliers. This research investigates the design of interactive visualizations to identify the benefits of interacting with information. The research question leading the investigation is how does interacting with visualizations support analytical reasoning of emergent information to activate knowledge? The study uses the theory of distributed cognition and human-information interaction to apply the design science research framework. The motivation behind the research is to identify guidelines for interactive visualizations to enhance a user’s ability to make decisions in dynamic situations and apply knowledge gleaned from the visualization. An experiment is used to analyze the use of an interactive dashboard in a dynamic decision-making situation. The results of this experiment specifically look at the combination of interactions as they support the distribution of cognition over three spaces of a human-visualization cognitive system. The results provide insight into the benefits that interactions have for enhancing analytical reasoning, expanding the use of visualizations beyond communicating or disseminating information. Providing a broad range of interactions that work with multiple views of information increases the opportunities that users have to complete tasks. This research contributes to the information visualization discipline by expanding the focus from representing data to representing and interacting with information. Secondly, my results provide an example of a qualitative assessment based on the value of visualization, in comparison to traditional usability assessment

Cognitive Foundations for Visual Analytics

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions

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

Understanding people through the aggregation of their digital footprints

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 160-172).Every day, millions of people encounter strangers online. We read their medical advice, buy their products, and ask them out on dates. Yet our views of them are very limited; we see individual communication acts rather than the person(s) as a whole. This thesis contends that socially-focused machine learning and visualization of archived digital footprints can improve the capacity of social media to help form impressions of online strangers. Four original designs are presented that each examine the social fabric of a different existing online world. The designs address unique perspectives on the problem of and opportunities offered by online impression formation. The first work, Is Britney Spears Span?, examines a way of prototyping strangers on first contact by modeling their past behaviors across a social network. Landscape of Words identifies cultural and topical trends in large online publics. Personas is a data portrait that characterizes individuals by collating heterogenous textual artifacts. The final design, Defuse, navigates and visualizes virtual crowds using metrics grounded in sociology. A reflection on these experimental endeavors is also presented, including a formalization of the problem and considerations for future research. A meta-critique by a panel of domain experts completes the discussion.by Aaron Robert Zinman.Ph.D

Visualization methods for sustainable planning

In urban planning, both measuring and communicating sustainability are among the most recent concerns. Therefore, the primary emphasis of this thesis concerns establishing metrics and visualization techniques in order to deal with indicators of sustainability. First, this thesis provides a novel approach for measuring and monitoring two indicators of sustainability - urban sprawl and carbon footprints – at the urban neighborhood scale. By designating different sectors of relevant carbon emissions as well as different household categories, this thesis provides detailed information about carbon emissions in order to estimate impacts of daily consumption decisions and travel behavior by household type. Regarding urban sprawl, a novel gridcell-based indicator model is established, based on different dimensions of urban sprawl. Second, this thesis presents a three-step-based visualization method, addressing predefined requirements for geovisualizations and visualizing those indicator results, introduced above. This surface-visualization combines advantages from both common GIS representation and three-dimensional representation techniques within the field of urban planning, and is assisted by a web-based graphical user interface which allows for accessing the results by the public. In addition, by focusing on local neighborhoods, this thesis provides an alternative approach in measuring and visualizing both indicators by utilizing a Neighborhood Relation Diagram (NRD), based on weighted Voronoi diagrams. Thus, the user is able to a) utilize original census data, b) compare direct impacts of indicator results on the neighboring cells, and c) compare both indicators of sustainability visually

P14.02 An electronic behaviour diary: Monitoring the effects of advanced obstetric surgical skills training

Objective: Training should lead to improvements in the quality of clinical care delivery. It is essential to follow up participants after a training intervention to monitor changes in behaviour associated with adoption of lessons learned into clinical practice. We introduced an electronic diary to facilitate monitoring whilst minimising effort for participants. Method: An electronic diary was created using a freely available on-line platform. Following a training intervention on advanced obstetric surgical skills, obstetric residents from Kenya were invited to pilot completing the diary after their labour ward shifts. Entries were anonymised. Participants were asked to enumerate the times they utilised specific skills, or to state why they had been unable to do so, using tick box options. Reflections on skills used were entered using free comments. Results: All participants reported changed behaviours, for example, improved surgical knot-tying, safer needle handling, separate closure of uterine incision angles and techniques for delivery of the impacted fetal head. 6 reported conducting vaginal breech birth and 6 performed vacuum-assisted birth. All reported improvements in use of the safe surgical checklist, obtaining consent and respectful maternity care. 7 had participated in newborn resuscitation. Reflections suggested participants experienced improved levels of confidence and satisfaction when implementing new skills. Conclusion: This pilot study has demonstrated the feasibility of monitoring clinical behaviour change following training using an electronic platform. Monitoring the effect of training is essential to prove that training results in improvements to clinical practice. We plan to roll out this intervention following future training interventions

P14.01 An example of too much too soon? A review of caesarean sections performed in the first stage of labour in Kenya

Objective: Caesarean Section (CS) has potential short and long-term complications and is associated with excess maternal death. Decisions to perform (CS) are frequently made by inexperienced and unsupported non-specialist doctors, sometimes resulting in inappropriate decision-making and surgery. Our study assesses decision-making for CS in the first stage of labour in Kenya. Method: A panel of one UK and six Kenyan expert obstetricians reviewed clinical data extracted from 87 case-notes, that were randomly selected from a series obtained from seven referral hospitals in five Kenyan counties over six months in 2020. Following a preliminary review of the data and email discussion, an online panel was convened to discuss outstanding cases where consensus was yet to be reached. Agreement was reached by the panel in all but 5 cases. Results: In 41.3% cases, CS was considered appropriate, including 8% where CS was performed too late. The decision to delivery interval exceeded 2 h in 58.6% cases, including 16 cases of non-reassuring fetal status. In 10.3% it was considered that due to delay, further reassessment should have occurred. In 9.1% the CS was done too soon. There was insufficient information available to make a full assessment in 21.8% of cases. In 11.5% the CS was inappropriate. Conclusion: This review demonstrates that unnecessary caesarean sections are being performed, while some with appropriate indications are subject to delays. There is need for improved support for decision-making, coupled with improved record-keeping, improved quality of fetal monitoring during labour and more timely surgery when necessary