Collecting, Debating and Contesting Data through Visualization

通过可视化收集、辩论和争论数据

• 批准号: 2265140
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2265140
• 关键词: Collecting; Debating; Contesting; Data; through

Data visualization interfaces remain artifacts of a unidirectional creation and communication process: from the data source to the audience. This process is curated by designers and domain experts with specific goals, tasks, and audiences in mind. Typically, this results in a dedicated, but possibly single-sided perspective onto the data. One example for this are visualizations of urban data collected by governments or corporations. The audience of such visualizations are citizens, who have relevant knowledge through their everyday experience of the city - but they have no means of voicing their perspective within the visualization.We revisit the concept of participatory visualization: Prior work on this topic has focused on ways of working together to shape the visual representation or annotation of data. We look at the participatory potential of visualization interfaces as an invitation to start a dialogue about the data it represents. Participatory visualization can create a fruitful tension between visualizing the data for common understanding and using the visualizations as an interface for data collection, verification, contestation, and discussion.We describe efforts that imply interrogation, annotation, and discussion of data. The focus and novelty of this participatory visualization lies in its strong focus on including a diverse, remote, and large audience that has a personal perspective on the data. This poses challenges for storytelling, literacy, and annotation:How do people express themselves in data visualizations? In co-located workshops, participants can annotate printed visualizations. We seek expressions of personal relations to the presented data and how these expressions change with different settings and datasets. We are looking for patterns in the expressions that allow conclusions about their intention, form, content, and where in the visualization they anchor.What are incentives for people to share their opinions and what interfaces do they need for that? Based on the previous conclusions, we imagine digital user interfaces that allow for more scalable, remote annotation of visualizations. For example, using participatory maps to let citizens contest census data about their neighborhood based on their everyday experience. This process comes with the challenge to determine what incentives motivate people to share personal perspectives. How can we visualize these personal perspectives? Existing visualization techniques and design patterns are insufficient to represent situated knowledge that is not objective, but personal, polyvocal and socially constructed. After extending the visualization pipeline to the considerate and deliberate collection of data, we expect to collect insights that culminate in strategies to embed qualitative data in visualizations.There is an increasing, yet mostly theoretical recognition of the situated and constructed nature of data. With participatory visualization we work towards a practical approach to collect and represent personal relations to institutional datasets. This can be used in various scenarios: Stakeholders in policy-making benefit from scalable tools to crowdsource people's opinions - for example in urban planning, where institutional planners as well as activists and citizen scientists seek to integrate local perspectives on issues like urban mobility, housing policy, or climate change impact. The idea also applies to data-driven journalism: As of now, readers of data dossiers can comment the articles as a whole, but have little possibility to change the granularity and aim of their contributions. With more precise annotation interfaces, participatory data dossiers can become audience-driven online representations of discussed topics.

数据可视化界面仍然是单向创建和通信过程的产物：从数据源到受众。这个过程是由设计师和领域专家策划的，他们有特定的目标，任务和受众。通常，这会导致对数据的专用但可能是单侧的透视。这方面的一个例子是政府或公司收集的城市数据的可视化。这种可视化的受众是市民，他们通过对城市的日常体验获得相关知识，但他们无法在可视化中表达自己的观点。我们重新审视了参与式可视化的概念：以前关于这个主题的工作集中在共同塑造数据的视觉表示或注释的方式上。我们把可视化界面的参与潜力看作是一种邀请，邀请人们就它所代表的数据展开对话。可视化可以创建一个富有成效的紧张关系之间的可视化数据的共同理解，并使用可视化作为一个接口的数据收集，验证，验证和discussions.We描述的努力，意味着询问，注释和讨论的数据。这种参与式可视化的重点和新奇在于它强烈关注包括对数据具有个人观点的多样化，远程和大量受众。这给讲故事、识字和注释带来了挑战：人们如何在数据可视化中表达自己？在同一地点的研讨会中，参与者可以注释打印的可视化。我们寻求个人关系的表达所呈现的数据以及这些表达如何随着不同的设置和数据集而变化。我们正在寻找表达中的模式，这些模式可以让我们对他们的意图、形式、内容以及他们在可视化中的位置得出结论。什么是人们分享他们的观点的动机，他们需要什么样的界面？基于前面的结论，我们设想数字用户界面，允许更可扩展的，远程注释的可视化。例如，使用参与式地图，让公民根据他们的日常经验对有关他们社区的人口普查数据提出质疑。这一过程伴随着一个挑战，即确定什么样的激励因素会促使人们分享个人观点。我们如何想象这些个人观点？现有的可视化技术和设计模式是不够的，以表示现场的知识，这是不客观的，但个人，多语言和社会建设。在将可视化管道扩展到深思熟虑和深思熟虑的数据收集之后，我们希望收集的见解最终能够在可视化中嵌入定性数据的策略。通过参与式可视化，我们致力于一种实用的方法来收集和代表个人与机构数据集的关系。这可以在各种情况下使用：决策中的利益相关者受益于可扩展的工具，以众包人们的意见-例如在城市规划中，机构规划师以及活动家和公民科学家寻求整合当地对城市流动性，住房政策或气候变化影响等问题的观点。这个想法也适用于数据驱动的新闻：截至目前，数据档案的读者可以对文章进行整体评论，但几乎没有可能改变其贡献的粒度和目标。通过更精确的注释界面，参与性数据档案可以成为观众驱动的讨论主题的在线表示。