If Corona-Warn-App (CWA) is successful in its Open Science approach it will be a game changer for the responsible use of machine learning in the public realm but also to enable more and better data gathering and applications.
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Open Energy Modelling has been built up as a research community over the last ten years aiming to bring transparency to the field using an array of Open Science methods for the planning of energy systems. The role of collaboration in the research cycle used by scientists in this engineering community is now an established Open Science practice. Similar practices of collaboration and participation outside of academia involving the public are still in their infancy. Harnessing public participation in energy planning and policy development is likely change as the energy sector is undergoing rapid changes due to its large contribution to greenhouse gases and the consequent demands for transparency and innovation to tackle climate change.
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Note: This is a reblog from the OKFN Science Blog. As part of my duties as a Panton Fellow, I will be regularly blogging there about my activities concerning open data and open science. Altmetrics are a hot topic in scientific community right now. Classic citation-based indicators such as the impact factor are amended by …