Complex data visualization design projects often entail collaboration between people with different visualization-related skills. For example, many teams include both designers who create new visualization designs and developers who implement the resulting visualization software. We identify gaps between data characterization tools, visualization design tools, and development platforms that pose challenges for designer-developer teams working to create new data visualizations. While it is common for commercial interaction design tools to support collaboration between designers and developers, creating data visualizations poses several unique challenges that are not supported by current tools. In particular, visualization designers must characterize and build an understanding of the underlying data, then specify layouts, data encodings, and other data-driven parameters that will be robust across many different data values. In larger teams, designers must also clearly communicate these mappings and their dependencies to developers, clients, and other collaborators. We report observations and reflections from five large multidisciplinary visualization design projects and highlight six data-specific visualization challenges for design specification and handoff. These challenges include adapting to changing data, anticipating edge cases in data, understanding technical challenges, articulating data-dependent interactions, communicating data mappings, and preserving the integrity of data mappings across iterations. Based on these observations, we identify opportunities for future tools for prototyping, testing, and communicating data-driven designs, which might contribute to more successful and collaborative data visualization design.

中文翻译：

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数据改变了一切：数据可视化设计移交中的挑战和机遇。

复杂的数据可视化设计项目通常需要具有不同可视化相关技能的人之间进行协作。例如，许多团队既包括创建新的可视化设计的设计师，也包括实现最终的可视化软件的开发人员。我们确定了数据表征工具，可视化设计工具和开发平台之间的差距，这对致力于创建新数据可视化的设计师-开发人员团队构成了挑战。尽管商业交互设计工具通常支持设计人员和开发人员之间的协作，但是创建数据可视化带来了一些独特的挑战，而当前工具却无法支持这些挑战。特别是，可视化设计人员必须表征和建立对基础数据的理解，然后指定布局，数据编码，以及其他在许多不同数据值之间都具有鲁棒性的数据驱动参数。在较大的团队中，设计人员还必须将这些映射及其依赖关系清楚地传达给开发人员，客户和其他协作者。我们报告了来自五个大型多学科可视化设计项目的观察和思考，并突出了针对设计规范和移交的六个特定于数据的可视化挑战。这些挑战包括适应不断变化的数据，预测数据中的极端情况，了解技术挑战，明确数据相关的交互，传达数据映射以及在迭代之间保持数据映射的完整性。基于这些观察，我们确定了用于原型设计，测试和交流数据驱动设计的未来工具的机会，