Make open climate data work
Scared of big data? We eat this stuff for breakfast! 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 onl
59 Minuten
Podcast
Podcaster
Beschreibung
vor 6 Jahren
Simon David Hirsbrunner, Lila Warszawski, Tobias Geiger, Toralf
Staud 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?
Staud 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?
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