Visualizing Climate Change & Resilience

Use of innovative and insightful data sources (30%)

Participants are encouraged to identify and explore publicly-available data from any source. Examples of innovative and insightful data sources are those that have been recently published, those that provide real-time information from data streams, and those integrating multiple sensors (such as weather stations and meteorological data, etc).

Storytelling effectiveness (30%)

A good solution is one that tells a compelling story that can be easily understood by a variety of audiences. As participants seek to describe climate change risk and resilience, it is important not only to approach data analytics and visualization from technical points of entry but also to ensure that visualization conveys the meaning and insights obtained from these data in an easy-to-understand and compelling manner.

Collaborative coding (20%)

The Observable platform aims to help people make sense of data---together. Collaborative coding may be considered as coding that starts from identifying and adapting pre-existing work shared on Observable, and re-purposing that code to suit this challenge. Collaborative coding may also be considered as team submissions demonstrating the contributions of multiple authors.

Replicability across Asia and the Pacific (20%)

Research on climate change and resilience are most effective when it can be shared and adapted across time and space. Visualizations that are designed to be 'portable' from one country to another and those that may be repeated over time as new information becomes available to give further insights into changing trends will be prioritized for this challenge.