Use Of Interactive Visualization Research Articles

Forming Cognitive Maps of Ontologies Using Interactive Visualizations

Ontology datasets, which encode the expert-defined complex objects mapping the entities, relations, and structures of a domain ontology, are increasingly being integrated into the performance of challenging knowledge-based tasks. Yet, it is hard to use ontology datasets within our tasks without first understanding the ontology which it describes. Using visual representation and interaction design, interactive visualization tools can help us learn and develop our understanding of unfamiliar ontologies. After a review of existing tools which visualize ontology datasets, we find that current design practices struggle to support learning tasks when attempting to build understanding of the ontological spaces within ontology datasets. During encounters with unfamiliar spaces, our cognitive processes align with the theoretical framework of cognitive map formation. Furthermore, designing encounters to promote cognitive map formation can improve our performance during learning tasks. In this paper, we examine related work on cognitive load, cognitive map formation, and the use of interactive visualizations during learning tasks. From these findings, we formalize a set of high-level design criteria for visualizing ontology datasets to promote cognitive map formation during learning tasks. We then perform a review of existing tools which visualize ontology datasets and assess their interface design towards their alignment with the cognitive map framework. We then present PRONTOVISE (PRogressive ONTOlogy VISualization Explorer), an interactive visualization tool which applies the high-level criteria within its design. We perform a task-based usage scenario to illustrate the design of PRONTOVISE. We conclude with a discussion of the implications of PRONTOVISE and its use of the criteria towards the design of interactive visualization tools which help us develop understanding of the ontological space within ontology datasets.

The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations

AbstractMachine learning (ML) models are nowadays used in complex applications in various domains, such as medicine, bioinformatics, and other sciences. Due to their black box nature, however, it may sometimes be hard to understand and trust the results they provide. This has increased the demand for reliable visualization tools related to enhancing trust in ML models, which has become a prominent topic of research in the visualization community over the past decades. To provide an overview and present the frontiers of current research on the topic, we present a State‐of‐the‐Art Report (STAR) on enhancing trust in ML models with the use of interactive visualization. We define and describe the background of the topic, introduce a categorization for visualization techniques that aim to accomplish this goal, and discuss insights and opportunities for future research directions. Among our contributions is a categorization of trust against different facets of interactive ML, expanded and improved from previous research. Our results are investigated from different analytical perspectives: (a) providing a statistical overview, (b) summarizing key findings, (c) performing topic analyses, and (d) exploring the data sets used in the individual papers, all with the support of an interactive web‐based survey browser. We intend this survey to be beneficial for visualization researchers whose interests involve making ML models more trustworthy, as well as researchers and practitioners from other disciplines in their search for effective visualization techniques suitable for solving their tasks with confidence and conveying meaning to their data.

The Interactive Visualization Gap in Initial Exploratory Data Analysis.

Data scientists and other analytic professionals often use interactive visualization in the dissemination phase at the end of a workflow during which findings are communicated to a wider audience. Visualization scientists, however, hold that interactive representation of data can also be used during exploratory analysis itself. Since the use of interactive visualization is optional rather than mandatory, this leaves a "visualization gap" during initial exploratory analysis that is the onus of visualization researchers to fill. In this paper, we explore areas where visualization would be beneficial in applied research by conducting a design study using a novel variation on contextual inquiry conducted with professional data analysts. Based on these interviews and experiments, we propose a set of interactive initial exploratory visualization guidelines which we believe will promote adoption by this type of user.

The use of interactive visualizations to foster the understanding of concepts of calculus: design principles and empirical results

Calculus and functional thinking are closely related. Functional thinking includes thinking in variations and functional dependencies with a strong emphasis on the aspect of change. Calculus is a climax within school mathematics and the education to functional thinking can be seen as propaedeutics to it. Many authors describe that functions at school are mainly treated in a static way, by regarding them as pointwise relations. This often leads to the underrepresentation of the aspect of change at school. Moreover, calculus at school is mainly procedure-oriented and structural understanding is lacking. In this work, two specially designed interactive activities for the teaching and learning of concepts of calculus based on dynamic geometry software are presented. They accentuate the aspect of change and the object aspect of functions using a double stage visualization. Moreover, the activities allow the discovery and exploration of some concepts of calculus in a qualitative-structural way without knowing or using curve-sketching routines. The activities were used in a qualitative study with 10th grade students of age 15–16 in secondary schools in Berlin, Germany. Some pairs of students were videotaped while working with the activities. After transcribing, the interactions of the students were interpreted and analyzed focusing to the use of the computer. The results show how the students mobilize their knowledge about functions working on the given tasks, and using the activities to formulate important concepts of calculus in a qualitative way. Also, some important epistemological obstacles can be detected.

Assessing the Preservation Condition of Large and Heterogeneous Electronic Records Collections with Visualization

As collections become larger in size, more complex in structure and increasingly diverse in composition, new approaches are needed to help curators assess digital files and make decisions about their long-term preservation. We present research on the use of interactive visualization to analyze file characterization information for the purpose of assessing the preservation condition of a vast collection of complex electronic records. The case study collection contains over 1,000,000 files of diverse formats arranged in varied record structures and record groups. The visualization application uses tree maps and a relational database management system (RDBMS) to represent the collection's arrangement and to show available characterization information at different levels of aggregation, classification and abstraction. Through this visualization interface curators can interact dynamically with the collections' characterization information to discover trends, as well as compare and contrast various file characteristics across the collection. Curators may select and weight the variables that they want to analyze. They can pursue analysis workflows that go from a high-level overview of the collection's preservation condition based on file format risks, to obtaining more detailed results about the condition of record groups and individual records. While there are various digital preservation planning tools available, to our knowledge none have been designed specifically to visually present assessment information across vast and complex collections. We present research to address the need for such a tool.