Designing visual analytics systems for organizational environments

Wang, Xiaoyu; Bier, Eric A.; Butkiewicz, Thomas; Ribarsky, William; Dou, Wenwen

doi:10.1145/2016656.2016657

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…We started by extending current models (e.g., the nested model [41]) and frameworks pertaining to analytical workflow and focused, in particular, on investigating its effects on the design of visual analytics systems for organizational environments. As reported in [56], we then iteratively categorized our design experiences from these collaborations into a more general organizational analysis workflow, and used it to inform future system designs. In doing so, we identified and enriched the design components of our framework by comparing the commonality and differences between individual analytical domains.…”

Section: 1mentioning

confidence: 99%

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A two-stage framework for designing visual analytics system in organizational environments

Wang

Dou

Butkiewicz

et al. 2011

2011 IEEE Conference on Visual Analytics Science and Technology (VAST)

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A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational users' decision-making and reasoning processes. The problem is, however, most domain analytical practices generally vary from organization to organization. This leads to diverse designs of visual analytics systems in incorporating domain analytical processes, making it difficult to generalize the success from one domain to another. Exacerbating this problem is the dearth of general models of analytical workflows available to enable such timely and effective designs.To alleviate these problems, we present a two-stage framework for informing the design of a visual analytics system. This design framework builds upon and extends current practices pertaining to analytical workflow and focuses, in particular, on incorporating both general domain analysis processes as well as individual's analytical activities. We illustrate both stages and their design components through examples, and hope this framework will be useful for designing future visual analytics systems. We validate the soundness of our framework with two visual analytics systems, namely Entity Workspace [8] [14,41,46] suggest that the establishment of a general design framework is significant. The objective for such a VA design framework is threefold: firstly, the framework must inform designers to systematically incorporate the support for domain analytical processes. Secondly, the framework should provide a basis for designers to evaluate their system and further help them identify a cohesive technology transition progress, from system design and implementation to its release and deployment [49]. Finally, the framework must serve an educational purpose, contributing to the identification of potential course materials that are necessary to educate others regarding the field of VA [1].However, constructing a convincing and appropriate design framework is challenging. The framework must be validated against existing systems and more importantly, it must give researchers and designers new ideas regarding how to evaluate and improve their own work.Given the need to incorporate successes from diverse VA systems, it is difficult to generate a framework that can summarize and instruct all the design requirements from a top-down perspective. High-level VA design frameworks like [14,41,44,55] are certainly of great value. Nonetheless, little specific guidance or recommendation is currently available to articulate the boundaries within which particular design assumptions apply, leaving the system design to be solely based on designers' prior experience. For example, how does a designer know which analysis method is suitable to characterize an organization? Are there components that a designer should follow to systematically incorporate a domain analytical process? Further, what recommendations exist that specify the appropriate methods for supporting both general and individual analytical workflows? Encouraged by the di...

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Section: 1mentioning

confidence: 99%

“…To provide the designers a concrete understanding of both the dissemination and transformation process, we further illustrate key action knowledge and its matching design considerations based on our design experience with the aforementioned three organizations. This process is detailed separately in [56].…”

Section: Design Artifacts Specificationmentioning

confidence: 99%

A two-stage framework for designing visual analytics system in organizational environments

Wang

Dou

Butkiewicz

et al. 2011

2011 IEEE Conference on Visual Analytics Science and Technology (VAST)

Self Cite

View full text Add to dashboard Cite

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A workflow to systematically design uncertainty-aware visual analytics applications

Maack,

Raith,

Pérez

et al. 2024

Vis Comput

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Visual analytics (VA) is a paradigm for insight generation by using visual analysis techniques and automated reasoning by transforming data into hypotheses and visualization to extract new insights. The insights are fed back into the data to enhance it until the desired insight is found. Many applications use this principle to provide meaningful mechanisms to assist decision-makers in achieving their goals. This process can be affected by various uncertainties that can interfere with the user decision-making process. Currently, there are no methodical description and handling tool to include uncertainty in VA systematically. We provide a unified workflow to transform the classic VA cycle into an uncertainty-aware visual analytics (UAVA) cycle consisting of five steps. To prove its usability, three real-world applications represent examples of the UAVA cycle implementation and the described workflow.

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Designing visual analytics systems for organizational environments

Cited by 2 publications

References 12 publications

A two-stage framework for designing visual analytics system in organizational environments

A two-stage framework for designing visual analytics system in organizational environments

A workflow to systematically design uncertainty-aware visual analytics applications

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