A systematic review of shared visualisation to achieve common ground

Yusoff, Nor'ain Mohd; Salim, Siti Salwah

doi:10.1016/j.jvlc.2014.12.003

Cited by 24 publications

(21 citation statements)

References 42 publications

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“…This review follows the guidelines for systematic reviews proposed by Kitchenham and Charters (). These guidelines were originally designed for the field of software engineering, but have been adopted successfully in other domains such as information visualization (Yusoff & Salim, ), spatio‐temporal analysis (Steiger, de Albuquerque, & Zipf, ), and educational resources (Arimoto & Barbosa, ). A systematic review has three phases: planning, conducting, and reporting.…”

Section: Motivation and Research Objectivesmentioning

confidence: 99%

Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges

Garcia-Chapeton

Ostermann

et al. 2018

Transactions in GIS

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Collaboration across disciplines is recognized as one of the great challenges for research in visual analysis of geographic information (GeoVisual Analytics, GVA). Considering the increasing availability of geodata and the complexity of analytical problems, the need to advance the support for collaborative work is becoming more pressing and prominent. This article contributes to this objective by reviewing the state‐of‐the‐art of the support for collaborative work in GVA systems and by identifying research challenges and proposing strategies to address them. We conducted a systematic review, resulting in the identification of 13 collaborative systems, 6 distinct collaborative techniques, and 3 research challenges. We conclude that GVA is moving toward more effective support of multidisciplinary and cross‐domain collaborative analysis. However, to materialize this potential, research is needed to improve the support for hybrid collaborative scenarios, cross‐device collaboration, and support for time‐critical and long‐term analysis.

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Section: Motivation and Research Objectivesmentioning

confidence: 99%

Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges

Garcia-Chapeton

Ostermann

et al. 2018

Transactions in GIS

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“…Yusoff and Salim (2015) identified five types of visualization on a virtual team level: shared -and shared coordination visualization, shared multiple representation and shared mirroring display -each type has effects on SMM [37]. Shared visualization is utilized to envision content, process and artifacts within a team process in order to foster SMM [37].…”

Section: Wicked Problems Visualization and Shared Mental Modelsmentioning

confidence: 99%

“…Shared visualization is utilized to envision content, process and artifacts within a team process in order to foster SMM [37]. The visualization type shared mirroring display supports collaboration within interrelated tasks whereas shared multiple representation collates different visualizations for collaboration, which can be advantageous for solving Wicked Problems.…”

Section: Wicked Problems Visualization and Shared Mental Modelsmentioning

confidence: 99%

“…All of these categories refer to different kinds of visualization concerning methodology, collaboration, complexity, etc. Yusoff and Salim (2015) examined the type of visualization concerning competencies of specific technologies [37], our focus is the investigation of the effect on SMM when using virtual visualization in teams.…”

Section: Wicked Problems Visualization and Shared Mental Modelsmentioning

confidence: 99%

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Shared Mental Models in Creative Virtual Teamwork

Redlich

Siemon

Lattemann

et al. 2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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“…Visualization can also serve as a means of reporting, detection or as an inherent part of the process of thinking (Gahegan et al 2001). yusoff and Salim (2015) in their work dealing with shared visualizations also define five strategies of shared The last strategy allows the integration of knowledge through the border. Analyst (understand the role of the analyst can be divided into many specializations right according to the following schedule of activities) should be responsible for the selection of appropriate method of spatial decision-making, software selection and tools for following processing and appropriate method for visualization.…”

Section: Introductionmentioning

confidence: 99%

Cartographic Visualization of Outputs for Spatial Decision-Making in Regional Development

Ruda

2015

Geodesy and Cartography

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Regional development is full of planning and decision making. Having precise results for spatial decision making (SDM) is more than necessary. On one site, there are many approaches how to process input data, on the other hand thematic cartography also operates with many visualizing methods and techniques. Loss of accuracy of the results is more than expected because there are two phases (data processing during SDM and cartographic visualization) where the accuracy might be distorted. In both phases processing recommendations must be obeyed. Selection of spatial decision making method must follow considered aims as well as visualization techniques and setting their parameters (especially during reclassification, interpolation or generalization). Paper deals with the proposal of elementary scheme of SDM and related visualization during two case studies (CS). First CS represents composite indicators proposal followed by weighted sum method using heuristics approaches with the aim to identify the tourism influence on the landscape. Combined visualization techniques for quantitative and qualitative data are presented. Second CS uses ordered weighted average method for finding the best place for building of a new public logistics centre. Constraints and factors represent key indicators and following factor and order weights enable to propose the best accepted risk model. In this case grid maps describe derived values and chosen reclassification documents conversion into linguistic variables.

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A systematic review of shared visualisation to achieve common ground

Cited by 24 publications

References 42 publications

Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges

Enabling collaborative GeoVisual analytics: Systems, techniques, and research challenges

Shared Mental Models in Creative Virtual Teamwork

Cartographic Visualization of Outputs for Spatial Decision-Making in Regional Development

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