The explosion of map use in the past few decades as part of everyday activities, accelerated through the digital production and dissemination of maps and the availability of low-cost, location-aware devices, has made the job of cartographers and map display designers more challenging. Yet, how do these recent changes affect effective map design? Can we accurately predict which designs will work for a given context? We investigate the concepts of design transferability and context and their potential to help us create map design outcomes that are effective for varying map use situations. We then present a model for operationalizing map use context to support evaluating map design transferability and pose several open research questions that need to be answered to support operationalizing map use context. This is followed by a research agenda that identifies research opportunities related to key research needs that will underpin transferable map design.

Over four workshops, we collected community input on what people considered as persistent challenges in geovisualization with the participation of 72 experts from various sub-domains of geographic information science and technology. We categorize and analyze this bottom-up input, and contrast it with the previously published research challenges based on five research agenda papers (top-down). We observe certain overlaps but also some interesting differences between the top-down and bottom-up approaches. A synthesis of the two suggests three major issues as persistent challenges: (1) a better understanding of the scope of our domain, how it interacts with other domains, and how to make this happen, (2) a systematic understanding of human factors, (3) a ‘practicable’ set of guidelines that matches the visualization types to task types, and guides the practitioner to design geovisualizations that are appropriate and helpful to the user. Distinguishing persistent from important, we discuss why the identified challenges are persistent, and draw recommendations for action based on our observations and interpretations. We believe these findings will help building a stronger, better-grounded research agenda for our community.

3D geovisualizations are quite popular, typical examples include 3D city models or virtual globes. They are reported to be more useful when they not only depict the real world but also include additional information. The creation of 3D geovisualizations is often very technology driven and we are yet missing solid theory. The paper aims to compile definitions and structures that allow the consideration and evaluation of the usefulness of 3D geovisualization with additional abstract information less focussing on technical and implementational aspects. The different purposes of 3D geovisualizations, as illustrated through the geovisualization cube, together with considerations of the specific characteristics of 3D visualizations, for example the inherent need for navigation, build the base for conscious design decisions. Those decisions can build upon existing theories from related disciplines, such as cartography or information visualization, but need to consider onto what dimension of the three-dimensional space the data is mapped. A categorisation of the use of 3D space is discussed before reviewing different task definitions. A generic task structure which allows separation between interaction and navigational tasks together with the presented definitions and the categorisation of using 3D space build the basic framework for considering, evaluating and discussing the usefulness of 3D geovisualizations and ultimately support 3D geovisualization theory building. The knowledge of what works well and is useful in specific contexts can improve future technological developments and hopefully make 3D geovisualizations become an important tool for the visual exploration of 3D geospatial data sets.

This paper reports on a controlled experiment evaluating how different cartographic representations of risk affect participants’ performance on a complex spatial decision task: route planning. The specific experimental scenario used is oriented towards emergency route-planning during flood response. The experiment compared six common abstract and metaphorical graphical symbolizations of risk. The results indicate a pattern of less-preferred graphical symbolizations associated with slower responses and lower-risk route choices. One mechanism that might explain these observed relationships would be that more complex and effortful maps promote closer attention paid by participants and lower levels of risk taking. Such user considerations have important implications for the design of maps and mapping interfaces for emergency planning and response. The data also highlights the importance of the ‘right decision, wrong outcome problem’ inherent in decision-making under uncertainty: in individual instances, more risky decisions do not always lead to worse outcomes.

3D desktop-based virtual environments provide a means for displaying quantitative data in context. Data that are inherently spatial in three dimensions may benefit from visual exploration and analysis in relation to the environment in which they were collected and to which they relate. We empirically evaluate how effectively and efficiently such data can be visually analyzed in relation to location and landform in 3D versus 2D visualizations. In two experiments, participants performed visual analysis tasks in 2D and 3D visualizations and reported insights and their confidence in them. The results showed only small differences between the 2D and 3D visualizations in the performance measures that we evaluated: task completion time, confidence, complexity, and insight plausibility. However, we found differences for different datasets and settings suggesting that 3D visualizations or 2D representations, respectively, may be more or less useful for particular datasets and contexts.