Related papers: Challenges and Opportunities in Data Visualization…
Scientists often explore and analyze large-scale scientific simulation data by leveraging two- and three-dimensional visualizations. The data and tasks can be complex and therefore best supported using myriad display technologies, from…
While data science has emerged as a contentious new scientific field, enormous debates and discussions have been made on it why we need data science and what makes it as a science. In reviewing hundreds of pieces of literature which include…
Visualization design is often described as the process of solving a well-defined problem by navigating a design space. While existing visualization design models have provided valuable structure and guidance, they tend to foreground…
Data Visualization has become an important aspect of big data analytics and has grown in sophistication and variety. We specifically identify the need for an analytical framework for data visualization with textual information. Data…
Visual representation of information is a fundamental tool for advancing our understanding of science. It enables the research community to extract new knowledge from complex datasets, and plays an equally vital role in communicating new…
Data Physicalization focuses on understanding how physical representations of data can support communication, learning and problem-solving. As an emerging area, Data Physicalization research needs conceptual foundations to support thinking…
One of the most useful techniques to help visual data analysis systems is interactive filtering (brushing). However, visualization techniques often suffer from overlap of graphical items and multiple attributes complexity, making visual…
Intelligent tutoring systems leverage AI models of expert learning and student knowledge to deliver personalized tutoring to students. While these intelligent tutors have demonstrated improved student learning outcomes, it is still unclear…
We introduce the notion of a data-first design study which is triggered by the acquisition of real-world data instead of specific stakeholder analysis questions. We propose an adaptation of the design study methodology framework to provide…
Data visualization design often requires creativity, and research is needed to understand its nature and means for promoting it. The current visualization literature on creativity is not well developed, especially with respect to the…
The virtual learning in University Education is the learning which is presented by set of integrated information and pedagogical technologies, in a process of interaction between subjects and objects as the virtual educational resources.…
Understanding different types of users' needs can even be more critical in today's data visualization field, as exploratory visualizations for novice users are becoming more widespread with an increasing amount of data sources. The…
This paper reports on the process of designing the UK Co-Benefits Atlas, which communicates and publicizes data for climate mitigation. Visualization atlases -- an emerging type of platform to make data about complex topics comprehensive…
Public-facing data visualizations can play a vital role in making complex information clear and engaging, thereby encouraging informed public discourse and participation. However, existing work offers limited insight into how practitioners…
There is a growing interest in designing tools to support interactivity specification and authoring in data visualization. To develop expressive and flexible tools, we need theories and models that describe the task space of interaction…
Supporting equitable instruction is an important issue for teachers attending diverse STEM classrooms. Visual learning analytics along with effective student survey measures can support providing on time feedback to teachers in making…
Data science education is increasingly involving human subjects and societal issues such as privacy, ethics, and fairness. Data scientists need to be equipped with skills to tackle the complexities of the societal context surrounding their…
A typical problem in Visual Analytics is that users are highly trained experts in their application domains, but have mostly no experience in using VA systems. Thus, users often have difficulties interpreting and working with visual…
Data visualization can be defined as the visual communication of information. One important barometer for the success of a visualization is whether the intents of the communicator(s) are faithfully conveyed. The processes of constructing…
The basic objective of data visualization is to provide an efficient graphical display for summarizing and reasoning about quantitative information. During the last decades, political science has accumulated a large corpus of various kinds…