The epistemological chaos of platform capitalism and the future of the social sciences
Author: Mark Carrigan and Lambros Fatsis Networked digital platforms have destabilised and reconfigured long-established forms of knowledge production and communication, changing the ways in which we consume media and engage with the public sphere and expert knowledge. In this extract from their new book, The Public and Their Platforms, Mark Carrigan and Lambros Fatsis, outline […]
Read moreRevisiting: Turning a Critical Eye on Reference Lists
Author: ANGELA COCHRAN Automated tools to help flag references is absolutely the direction we should be moving in. No doubt, the willingness of publishers to open and share their full reference lists via CrossRef and the I4OC initiative will further shed a light on areas in need of improvement. In this post, Angela Cochran revisits […]
Read moreScientific publishing’s new weapon for the next crisis: the rapid correction
Author: Gideon Meyerowitz-Katz and James Heathers The world has gained a better understanding of the relevant Covid-19 disease processes, assembled a solid clinical research base for managing the disease, and produced multiple vaccines that are driving down infections and deaths. Yet the infrastructure for producing empirical knowledge about the SARS-CoV-2 virus frequently failed, leading to […]
Read moreSecurity, Safety, SeamlessAccess
Author: TODD A CARPENTER, HYLKE KOERS, HEATHER FLANAGAN In the past year of the pandemic, researchers increasingly required remote access to their academic institutions, ranging from library resources to the data gathered by their research group or in the lab. These changes in access patterns – some of which are looking like they will be […]
Read moreResearch data infrastructure needs to keep pace with technology, look to the future, and focus on trust
Author: Victoria Moody Back in the mid-2000s, the open-source ‘data lake’ emerged. Structured and unstructured data could flow in, promising innovative and unlimited insights. Today data science, machine learning, and algorithmic approaches to data intensive research have become a cornerstone of research. It is a complex space, and research is increasingly dependent on infrastructure to […]
Read more