We will explore, interrelate and discuss the myriad layers of digital data within the world of climate change research – petabytes of raw data stored in scientific supercomputers, countless pages of online explanation, documentation and visualization, as well as seemingly endless social media threads passionately debating these explanations. We invite the re:publica crowd to a journey through today’s scientific and civic open data practices.
Using scientific expertise, supercomputers and big data, researchers are able to broaden our understanding of the past and present of our climate system. By drawing on knowledge of our natural and social worlds, they can go even further, envisioning possible impacts, risks, and solutions for a future with climate change. These scenarios of the future don’t just define abstract quantities, like average global temperatures, they describe future worlds that are relevant for policy makers, stakeholders, and for a curious and knowledge-hungry public.
The web has no shortage of open data, visualizations, photos, videos and blogs describing climate change and its impacts. To put it bluntly, we have more than enough information available to understand and act on climate change. However, for researchers and non-scientists alike, the challenge is to match informational needs with the scientific data and knowledge available. It’s time-consuming work searching through all these web sources, and most citizen scientists give up, before they find what they’re looking for. Quite often a certain level of expertise is required to realize the answer has been staring you in the face all along! We’ve come to think that open data is still a long way from truly open science. During the last couple of months, we’ve been wading through the sea of climate information available on websites, information portals, and social media platforms. Based on this work, we will take a closer look at the ‘openness’ of information on climate impacts together with interested rp18 participants. The discussions' premise is that openness is not a stable state, but always requires work: ‘data’ doesn’t talk on its own, it is constantly being translated, situated, and put into new perspectives. If so, what’s the role of open data scientists in the digital society? How to deal with the fact that “looking at big data” has become a mundane element of our contemporary digital culture - not just in science, but in everyday life?