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Extreme weather events, such as flooding, are expected to increase in frequency and intensity. Therefore, the prediction of extreme weather events, assessment of their local impacts in urban environments, and implementation of adaptation measures are becoming high-priority challenges for local, regional, and national agencies and authorities. To manage these challenges, access to accurate weather warnings and information about the occurrence, extent, and impacts of extreme weather events are crucial. As a result, in addition to official sources of information for prediction and monitoring, citizen volunteered geographic information (VGI) has emerged as a complementary source of valuable information. In this work, we propose the formulation of an approach to complement the impact-based weather warning system that has been introduced in Sweden in 2021 by making use of such alternative sources of data. We present and discuss design considerations and opportunities towards the creation of a visual analytics (VA) pipeline for the identification and exploration of extreme weather events and their impacts from VGI texts and images retrieved from social media. The envisioned VA pipeline incorporates three main steps: (1) data collection, (2) image/text classification and analysis, and (3) visualization and exploration through an interactive visual interface. We envision that our work has the potential to support three processes that involve multiple stakeholders of the weather warning system: (1) the validation of previously issued warnings, (2) local and regional assessment-support documentation, and (3) the monitoring of ongoing events. The results of this work could thus generate information that is relevant to climate adaptation decision making and provide potential support for the future development of national weather warning systems. [ABSTRACT FROM AUTHOR]

This paper investigates the potential aspects of visual literacy that might appear when visual analytics and students interact in social science secondary classrooms. Interacting with visual technology likely demands new forms of literacy as various dimensions of complexity emerge in such learning activities where reading imposes order and relevance on what is displayed. However, only a few studies have evaluated how these visual processes emerge. Applying a socio-material semiotic approach, this paper examines the interactions between teachers, students and a visual analytics application, clarifying what strengthens or weakens the socio-material relations at work in emerging visual literacy. Methodologically, a designbased research approach is chosen. Notably, it is the early stages of the designed-based research cycle that are applied. Interventions were designed and conducted in five classes in three secondary schools in Sweden (97 students). The visual analytics application introduced was Statistics eXplorer. For each class, two to three lessons were video recorded to capture how the students interacted with the application. The socio-material analyses show that the interactions between the visual analytics and the students were both strengthened and weakened by different social as well as material forces. The actions were directed by visual properties such as movement, highlighting, and color, properties that often resulted in quick vision or locked vision. This paper argues that there needs to be a close didactic alignment and deeper knowledge of how visual interfaces attract students' attention and how students' visual literacy emerges in that relationship. [ABSTRACT FROM AUTHOR]