Affective colormap design for accurate visual comprehension in industrial tomography

The design of colormaps can help tomography operators obtain accurate visual compre-hension, thereby assisting safety-critical decisions. The research presented here is about deploying colormaps that promote the best affective responses for industrial microwave tomography (MWT). To answer the two research questions related to our study, we firstly conducted a quantitative analysis of 11 frequently-used colormaps on a segmentation task. Secondly, we presented the same colormaps within a crowdsourced study comprising two parts to verify the quantitative outcomes. The first part encoded affective responses from participants into a prevailing four-quadrant valence–arousal grid; the second part recorded participant ratings towards the accuracy of each colormap on MWT segmentation. We concluded that three colormaps are the best suited in the context of MWT tasks. We also found that the colormaps triggering emotions in the positive–exciting quadrant can facilitate more accurate visual comprehension than other affect-related quadrants. A synthetic colormap design guideline was consequently proposed

Using Graphs for Exposing the Underlying Competence Design of Academic Degrees

Open Access DocumentAcademic degrees are usually presented with textual tables and lists, following a semester structure. This information is expected to help learners to create their own itineraries within a given degree, which may not be the case in a distance university, where learners may not take complete semesters. Furthermore, both tables and lists are useful to explain the contents of a specific degree, but they are limited for visualizing the relationships between the different subjects and the competences acquired and developed through them. In this paper we propose a new way to visualize an academic degree, equating subjects and competences as two complementary dimensions. We have applied this visualization to two degrees already offered by the Universitat Oberta de Catalunya and to another during its design phase, involving learners and degree managers, respectivelyLos títulos académicos generalmente se presentan con tablas y listas de texto, siguiendo una estructura semestral. Se espera esta información para ayudar a los alumnos a crear sus propios itinerarios dentro de un determinado grado, lo que puede no ser el caso en una universidad a distancia, donde los estudiantes no pueden tomar semestres completos. Además, tanto las tablas como las listas son útiles para explicar el contenido de un grado específico, pero están limitados para visualizar las relaciones entre las diferentes asignaturas y las competencias adquiridas y desarrollado a través de ellos. En este artículo, proponemos una nueva forma de visualizar un título académico, equiparando temas y competencias como dos dimensiones complementarias. Hemos aplicado esta visualización a dos grados ya ofrecidos por la Universitat Oberta de Catalunya y otro durante su fase de diseño, que involucra a estudiantes y directores de grado, respectivamente.Els títols acadèmics generalment es presenten amb taules i llistes de text, seguint una estructura semestral. S'espera aquesta informació per ajudar als alumnes a crear els seus propis itineraris dins d'un determinat grau, la qual cosa pugues no ser el cas en una universitat a distància, on els estudiants no poden prendre semestres complets. A més, tant les taules com les llistes són útils per explicar el contingut d'un grau específic, però estan limitats per visualitzar les relacions entre les diferents assignatures i les competències adquirides i desenvolupat a través d'ells. En aquest article, proposem una nova forma de visualitzar un títol acadèmic, equiparant temes i competències com dues dimensions complementàries. Hem aplicat aquesta visualització a dos graus ja oferts per l'Universitat Oberta de Catalunya i un altre durant la seva fase de disseny, que involucra a estudiants i directors de grau, respectivamen

On the challenges and opportunities in visualization for machine learning and knowledge extraction: A research agenda

We describe a selection of challenges at the intersection of machine learning and data visualization and outline a subjective research agenda based on professional and personal experience. The unprecedented increase in the amount, variety and the value of data has been significantly transforming the way that scientific research is carried out and businesses operate. Within data science, which has emerged as a practice to enable this data-intensive innovation by gathering together and advancing the knowledge from fields such as statistics, machine learning, knowledge extraction, data management, and visualization, visualization plays a unique and maybe the ultimate role as an approach to facilitate the human and computer cooperation, and to particularly enable the analysis of diverse and heterogeneous data using complex computational methods where algorithmic results are challenging to interpret and operationalize. Whilst algorithm development is surely at the center of the whole pipeline in disciplines such as Machine Learning and Knowledge Discovery, it is visualization which ultimately makes the results accessible to the end user. Visualization thus can be seen as a mapping from arbitrarily high-dimensional abstract spaces to the lower dimensions and plays a central and critical role in interacting with machine learning algorithms, and particularly in interactive machine learning (iML) with including the human-in-the-loop. The central goal of the CD-MAKE VIS workshop is to spark discussions at this intersection of visualization, machine learning and knowledge discovery and bring together experts from these disciplines. This paper discusses a perspective on the challenges and opportunities in this integration of these discipline and presents a number of directions and strategies for further research

Spectral Visualization Sharpening

In this paper, we propose a perceptually-guided visualization sharpening technique. We analyze the spectral behavior of an established comprehensive perceptual model to arrive at our approximated model based on an adapted weighting of the bandpass images from a Gaussian pyramid. The main benefit of this approximated model is its controllability and predictability for sharpening color-mapped visualizations. Our method can be integrated into any visualization tool as it adopts generic image-based post-processing, and it is intuitive and easy to use as viewing distance is the only parameter. Using highly diverse datasets, we show the usefulness of our method across a wide range of typical visualizations.Comment: Symposium of Applied Perception'1

Visual Characterisation of Temporal Occupancy for Movement Ecology

Movement ecologists study aspects of animals' movement, behaviour, and the factors that might drive these. Temporal patterns of local occupancy often reveal the type of usage at a location. We present and apply temporal tile-maps that embed temporal visual encodings into cartographic representations, and do so in an interactive visual analysis context. This reveals spatial variation in temporal occupancy that allows places to be identified and distinguished according to their use by animals. We apply these to GPS data from tracking gulls and illustrate the application to movement ecology. The tool that implements this and data are available to download and use

A Visual Analytics Approach for User Behaviour Understanding through Action Sequence Analysis

Analysis of action sequence data provides new opportunities to understand and model user behaviour. Such data are often in the form of timestamped and labelled series of atomic user actions. Cyber security is one of the domains that show the value of the analysis of these data. Elaborate and specialised models of user-behaviour are desired for effective decision making during investigation of cyber threats. However, due to their complex nature, activity sequences are not yet well-exploited within cyber security systems. In this paper, we describe the initial phases of a visual analytics approach that aims to enable a rich understanding of user behaviour through the analysis of user activity sequences. First, we discuss a motivating case study and discuss a number of high level requirements as derived from a series of workshops within an ongoing research project. We then present the components of a visual analytics approach that constitutes a novel combination of ``action space'' analysis, pattern mining, and the interactive visual analysis of multiple sequences to take the initial steps towards a comprehensive understanding of user behaviour

End to End Colonic Content Assessment: ColonMetry Application

Colon segmentation; Colonic content; Intestinal gasSegmentación de colon; Contenido colónico; Gas intestinalSegmentació del còlon; Contingut colònic; Gas intestinalThe analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension.This work was supported by the Spanish Ministry of Science and Innovation (Proyectos de Generación de Conocimiento), PID2021-122295OB-I00, and Agencia Estatal de Investigación and Fondos FEDER, PID2021-122136OB-C21); Ciberehd is funded by the Instituto de Salud Carlos III

TeCoMiner: Topic Discovery Through Term Community Detection

This note is a short description of TeCoMiner, an interactive tool for exploring the topic content of text collections. Unlike other topic modeling tools, TeCoMiner is not based on some generative probabilistic model but on topological considerations about co-occurrence networks of terms. We outline the methods used for identifying topics, describe the features of the tool, and sketch an application, using a corpus of policy related scientific news on environmental issues published by the European Commission over the last decade.Comment: 8 pages, 4 figure

Reflections on an Experiment, Evaluating the Impact of Spatialisation on Exploration

This paper reports on an experiment designed to evaluate whether visualising a digital library (using a spatialisation technique) can influence exploratory search behaviour. In the experiment we asked participants to complete a set of novel tasks using one of two interfaces - a visualisation interface, ExploViz, and its search-based equivalent, LibSearch. A set of measures were used to capture sensemaking and exploratory behaviour and to analyse cognitive load. As results were non-significant, we reflect upon the design of the experiment, consider possible issues and suggest how these could be addressed in future iterations

The State of the Art in Multilayer Network Visualization

Modelling relationships between entities in real-world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real-world datasets. Examples of multilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domain of graph visualization there are many systems which visualize datasets having many characteristics of multilayer graphs. This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those developing systems across application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer graph visualization, as well as tools, tasks, and analytic techniques from within application domains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future research directions for addressing them