interactive design techniques

CV-35 - Geovisualization

Geovisualization is primarily understood as the process of interactively visualizing geographic information in any of the steps in spatial analyses, even though it can also refer to the visual output (e.g., plots, maps, combinations of these), or the associated techniques. Rooted in cartography, geovisualization emerged as a research thrust with the leadership of Alan MacEachren (Pennsylvania State University) and colleagues when interactive maps and digitally-enabled exploratory data analysis led to a paradigm shift in 1980s and 1990s. A core argument for geovisualization is that visual thinking using maps is integral to the scientific process and hypothesis generation, and the role of maps grew beyond communicating the end results of an analysis or documentation process. As such, geovisualization interacts with a number of disciplines including cartography, visual analytics, information visualization, scientific visualization, statistics, computer science, art-and-design, and cognitive science; borrowing from and contributing to each. In this entry, we provide a definition and a brief history of geovisualization including its fundamental concepts, elaborate on its relationship to other disciplines, and briefly review the skills/tools that are relevant in working with geovisualization environments. We finish the entry with a list of learning objectives, instructional questions, and additional resources.

CV-19 - Big Data Visualization

As new information and communication technologies have altered so many aspects of our daily lives over the past decades, they have simultaneously stimulated a shift in the types of data that we collect, produce, and analyze. Together, this changing data landscape is often referred to as "big data." Big data is distinguished from "small data" not only by its high volume but also by the velocity, variety, exhaustivity, resolution, relationality, and flexibility of the datasets. This entry discusses the visualization of big spatial datasets. As many such datasets contain geographic attributes or are situated and produced within geographic space, cartography takes on a pivotal role in big data visualization. Visualization of big data is frequently and effectively used to communicate and present information, but it is in making sense of big data – generating new insights and knowledge – that visualization is becoming an indispensable tool, making cartography vital to understanding geographic big data. Although visualization of big data presents several challenges, human experts can use visualization in general, and cartography in particular, aided by interfaces and software designed for this purpose, to effectively explore and analyze big data.

CV-16 - Virtual and immersive environments
  • Discuss the nature and use of virtual environments, such as Google Earth
  • Explain how various data formats and software and hardware environments support immersive visualization
  • Compare and contrast the relative advantages of different immersive display systems used for cartographic visualization (e.g., CAVEs, GeoWalls)
  • Evaluate the extent to which a GeoWall or CAVE does or does not enhance understanding of spatial data
  • Explain how the virtual and immersive environments become increasingly more complex as we move from the relatively non-immersive VRML desktop environment to a stereoscopic display (e.g., a GeoWall) to a more fully immersive CAVE
CV-15 - Web Mapping

As internet use has grown, many paper maps have been scanned and published online, and new maps have increasingly been designed for viewing in a web browser or mobile app. Web maps may be static or dynamic, and dynamic maps may either be animated or interactive. Tiled web maps are interactive maps that use tiled images to allow for fast data loading and smooth interaction, while vector web maps support rendering a wide variety of map designs on the client. Web maps follow a client-server architecture, with specialized map servers sometimes used to publish data and maps as geospatial web services. Web maps are composed of data from a database or file on the server, style information rendered on either server or client, and optionally animation or interaction instructions executed on the client. Several graphic web platforms provide user-friendly web mapping solutions, while greater customization is possible through the user of commercial or open source web mapping APIs. When designing web maps, cartographers should consider the map’s purpose on a continuum from exploratory and highly interactive to thematic and less interactive or static, the constraints of desktop and/or mobile web contexts, and accessibility for disabled, elderly, and poorly connected users.

CV-13 - User Interface and User Experience (UI/UX) Design

Advances in personal computing and information technologies have fundamentally transformed how maps are produced and consumed, as many maps today are highly interactive and delivered online or through mobile devices. Accordingly, we need to consider interaction as a fundamental complement to representation in cartography and visualization. UI (user interface) / UX (user experience) describes a set of concepts, guidelines, and workflows for critically thinking about the design and use of an interactive product, map or otherwise. This entry introduces core concepts from UI/UX design important to cartography and visualization, focusing on issues related to visual design. First, a fundamental distinction is made between the use of an interface as a tool and the broader experience of an interaction, a distinction that separates UI design and UX design. Norman’s stages of interaction framework then is summarized as a guiding model for understanding the user experience with interactive maps, noting how different UX design solutions can be applied to breakdowns at different stages of the interaction. Finally, three dimensions of UI design are described: the fundamental interaction operators that form the basic building blocks of an interface, interface styles that implement these operator primitives, and recommendations for visual design of an interface.

CV-19 - Big Data Visualization

As new information and communication technologies have altered so many aspects of our daily lives over the past decades, they have simultaneously stimulated a shift in the types of data that we collect, produce, and analyze. Together, this changing data landscape is often referred to as "big data." Big data is distinguished from "small data" not only by its high volume but also by the velocity, variety, exhaustivity, resolution, relationality, and flexibility of the datasets. This entry discusses the visualization of big spatial datasets. As many such datasets contain geographic attributes or are situated and produced within geographic space, cartography takes on a pivotal role in big data visualization. Visualization of big data is frequently and effectively used to communicate and present information, but it is in making sense of big data – generating new insights and knowledge – that visualization is becoming an indispensable tool, making cartography vital to understanding geographic big data. Although visualization of big data presents several challenges, human experts can use visualization in general, and cartography in particular, aided by interfaces and software designed for this purpose, to effectively explore and analyze big data.

CV-35 - Geovisualization

Geovisualization is primarily understood as the process of interactively visualizing geographic information in any of the steps in spatial analyses, even though it can also refer to the visual output (e.g., plots, maps, combinations of these), or the associated techniques. Rooted in cartography, geovisualization emerged as a research thrust with the leadership of Alan MacEachren (Pennsylvania State University) and colleagues when interactive maps and digitally-enabled exploratory data analysis led to a paradigm shift in 1980s and 1990s. A core argument for geovisualization is that visual thinking using maps is integral to the scientific process and hypothesis generation, and the role of maps grew beyond communicating the end results of an analysis or documentation process. As such, geovisualization interacts with a number of disciplines including cartography, visual analytics, information visualization, scientific visualization, statistics, computer science, art-and-design, and cognitive science; borrowing from and contributing to each. In this entry, we provide a definition and a brief history of geovisualization including its fundamental concepts, elaborate on its relationship to other disciplines, and briefly review the skills/tools that are relevant in working with geovisualization environments. We finish the entry with a list of learning objectives, instructional questions, and additional resources.

CV-15 - Web Mapping

As internet use has grown, many paper maps have been scanned and published online, and new maps have increasingly been designed for viewing in a web browser or mobile app. Web maps may be static or dynamic, and dynamic maps may either be animated or interactive. Tiled web maps are interactive maps that use tiled images to allow for fast data loading and smooth interaction, while vector web maps support rendering a wide variety of map designs on the client. Web maps follow a client-server architecture, with specialized map servers sometimes used to publish data and maps as geospatial web services. Web maps are composed of data from a database or file on the server, style information rendered on either server or client, and optionally animation or interaction instructions executed on the client. Several graphic web platforms provide user-friendly web mapping solutions, while greater customization is possible through the user of commercial or open source web mapping APIs. When designing web maps, cartographers should consider the map’s purpose on a continuum from exploratory and highly interactive to thematic and less interactive or static, the constraints of desktop and/or mobile web contexts, and accessibility for disabled, elderly, and poorly connected users.

CV-19 - Big Data Visualization
  • Explain how the concept “digital cartographic models” unifies a number of principles for computer cartography
  • Identify areas in cartography and visualization that have, and those that have not, advanced because of computational approaches
  • Explain how the rise of interoperability and open standards has affected the production of cartographic representations and visualizations
  • Explain how optimization techniques are improving the automated design of maps
  • Describe the structure and function of geographic names databases (i.e., gazetteer) for use in mapping
  • Differentiate between GIS and graphics software tools for mapping and those for visualization purposes
CV-16 - Virtual and immersive environments
  • Discuss the nature and use of virtual environments, such as Google Earth
  • Explain how various data formats and software and hardware environments support immersive visualization
  • Compare and contrast the relative advantages of different immersive display systems used for cartographic visualization (e.g., CAVEs, GeoWalls)
  • Evaluate the extent to which a GeoWall or CAVE does or does not enhance understanding of spatial data
  • Explain how the virtual and immersive environments become increasingly more complex as we move from the relatively non-immersive VRML desktop environment to a stereoscopic display (e.g., a GeoWall) to a more fully immersive CAVE

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