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Traveling Waves: The Indonesian Tsunami Warning System - STS Webinar Series #1

Authors: Rafliana, Irina;

Traveling Waves: The Indonesian Tsunami Warning System - STS Webinar Series #1

Abstract

Previously published on YouTube: https://www.youtube.com/watch?v=CWK1_Nxi__Y (Indonesian) Seri webinar ini diadakan oleh Pusat Riset Kewilayahan (PRW) BRIN untuk mendiskusikan tema-tema terkait Science, Technology, and Society Studies, salah satu program kajian yang dikembangkan di PRW-BRIN. Webinar ini membahas kelindan antara diskursus, aktor, mesin deteksi, serta praktik sains dan teknologi untuk menghadapi risiko dan ketidakpastian sistem pengetahuan peringatan dini tsunami di Indonesia. Dengan menggunakan pendekatan etnografis, diskusi ini akan berusaha menjawab pertanyaan terkait teknologi sistem peringatan dini tsunami Indonesia sebagai infrastruktur sosial dan jaringan konektivitas pakar Jerman - Indonesia dalam pengembangan sistem teknologi tersebut di Indonesia. (English) This webinar series was held by the BRIN Regional Research Center (PRW) to discuss themes related to Science, Technology, and Society Studies, one of the study programs developed at PRW-BRIN. This webinar discusses the interplay between discourse, actors, detection machines, as well as science and technology practices to deal with the risks and uncertainties of the tsunami early warning knowledge system in Indonesia. Using an ethnographic approach, this discussion will attempt to answer questions related to the technology of the Indonesian tsunami early warning system as a social infrastructure and connectivity network of German-Indonesian experts in developing the technology system in Indonesia.

Horizon 2020 MSCA-RISE, Grant Agreement #873119

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Keywords

Indonesia, technology, discourse, digitalisation, tsunami, STS, ethnography, early warning system

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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