Visual Representation Of Concepts Research Articles

Jupyter widgets and extensions for education and research in computational physics and chemistry

Interactive notebooks are a precious tool for creating graphical user interfaces and teaching materials. Python and Jupyter are becoming increasingly popular in this context, with Jupyter widgets at the core of the interactive functionalities. However, while packages and libraries which offer a broad range of general-purpose widgets exist, there is limited development of specialized widgets for computational physics, chemistry and materials science. This deficiency implies significant time investments for the development of effective Jupyter notebooks for research and education in these domains. Here, we present custom Jupyter widgets that we have developed to target the needs of these communities. These widgets constitute high-quality interactive graphical components and can be employed, for example, to visualize and manipulate data, or to explore different visual representations of concepts, clarifying the relationships existing between them. In addition, we discuss with one example how similar functionality can be exposed in the form of JupyterLab extensions, modifying the JupyterLab interface for an enhanced user experience when working with applications within the targeted scientific domains.

Toward a framework for visual nomen

PurposeThrough examination of the Library Reference Model (LRM) specifications for nomen and the potential challenges visual nomen might present for their description and use in information systems, the purpose of this study was to investigate two questions: (1) how do nonlinguistic or nonalphanumeric signs or symbols act as nomen to identify entities? and (2) what details or attributes are relevant to describe and classify such nomen to integrate them into information systems?Design/methodology/approachThis research was built on an exploratory, qualitative instrumental case study design using multiple (or comparative) cases. Using the International Federation of Library Associations and Institutions LRM conceptualization of nomen as the basis, this research explored the similarities and differences between the LRM definition, its attributes and the use of nonlinguistic and nonalphanumeric “strings” for visual nomen to represent a res, moving iteratively between the LRM documentation, visual nomen identified in previous research and additional examples. This study used a constant comparative method to conduct a structured, focused comparison across different cases found in the source survey.FindingsA close review of the history of the development of the nomen entity was made to understand the semiotic relationship between entities and their symbolic representation, how those symbols are then reified to be further classified and described and how such definitions in the LRM offer a path forward for better understanding the role and function of visual nomen. Based on the foundation of the nomen entity and its attributes established in the LRM, this research then looked at visual representations of concepts and entities to suggest a nascent framework for describing aspects of visual nomen which may be relevant to their use and applicationOriginality/valueThis exploratory study of the use of supralinguistic ways of referencing entities delineates novel insights into a potential framework for describing and using visual nomen as a way of labeling or naming entities represented in information systems. By examining the specifications of the nomen entity and its attributes as delineated by the LRM, this study reinforces the applicability of LRM-defined attributes in the use of visual nomen in addition to offering other attributes or dimensions.

Automatic Code Generation of Data Visualization for Structural Health Monitoring

Structural Health Monitoring (SHM) aims at detecting, localizing, and characterizing damages in civil, mechanical, and aerospatial structures, which are hardly detectable in visual inspections. The collection, analysis, and visualization of data captured by sensors installed on these structures can be strongly supported by modern techniques of Data Science. In particular, the visualization of these data provides valuable help to experts on structural health and decision makers on preventive and corrective maintenance. Unfortunately, existing systems of data visualization still demand those stakeholders for a high level of software programming skills to take full advantage of visual and interactive exploration of data that sensors capture and output. This work introduces a model-driven approach to develop data visualization in the domain of structural health monitoring, in particular, of bridges. This approach is based on the definition of a Domain Specific Language (DSL) that describes the main concepts of an infrastructure of sensors typically used in SHM, along with common graphics and visual alternatives of data visualization. This DSL is instantiated by a modeling language, composed of a metamodel, a visual representation of concepts, and a set of model-to-text transformation rules. In this way, non-programmers can implement their own data visualization from a graphical and intuitive design, by automatically generating the corresponding code. This approach was implemented in a modeling and code-generation tool, called Vis4bridge, whose usability and output were successfully evaluated through the development of tasks and case studies.

Developing and researching PhET simulations for teaching quantum mechanics

Quantum mechanics is counterintuitive, difficult to visualize, mathematically challenging, and abstract. The Physics Education Technology (PhET) Project now includes 18 simulations on quantum mechanics designed to improve the learning of this subject. These simulations include several key features to help students build mental models and intuition about quantum mechanics: visual representations of abstract concepts and microscopic processes that cannot be directly observed, interactive environments that directly couple students’ actions to animations, connections to everyday life, and efficient calculations so that students can focus on the concepts rather than the mathematics. Like all PhET simulations, these are developed using the results of research and feedback from educators, and are tested in student interviews and classroom studies. This article provides an overview of the PhET quantum simulations and their development. We also describe research demonstrating their effectiveness and discuss some insights about student thinking.

Using Concept Maps to Plan an Introductory Structural Geology Course

A concept map is a visual representation of concepts and their relationship to each other in a body of knowledge. They show the hierarchy of these concepts and emphasize the links between them. Concept maps are valuable pedagogical tools used to design the syllabus for an undergraduate structural geology course. Their value as an aid to student learning has been widely documented (Novak, 1990), and we have found them particularly suitable in the initial planning of courses such as structural geology where many new concepts are introduced.Concept maps used in the design stage of our structural geology course has resulted in a significant re-ordering of the topics. A more logical sequence begins with descriptive topics (joints and faults) and progresses to more abstract topics (stress and strain and continuum mechanics). The resultant sequence of topics is not that used in most traditional structural geology textbooks. Although it is not necessary for a course to be taught in the same sequence as material is presented in a textbook it is more convenient for students if it does.