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OMICS ; 26(11): 589-593, 2022 11.
Article in English | MEDLINE | ID: covidwho-2227769


Big data and data deluge are topics that are well known in the field of systems science. Digital transformation of big data and omics fields is also underway at present. These changes are impacting life sciences broadly, and high-throughput omics inquiries specifically. On the other hand, digital transformation also calls for rethinking citizenship and moving toward critically informed digital citizenship. Past approaches to digital citizenship have tended to frame the digital health issues narrowly, around technocracy, digital literacy, and technical competence in deployment and use of digital technologies. However, digital citizenship also calls for questioning the means and ends of digital transformation, the frames in which knowledge is produced in the current era. In this context, Industry 4.0 has been one of the innovation frameworks for automation through big data, and embedded sensors connected by wireless communication. Industry 4.0 and the attendant "smart" technologies relate to various automation approaches deployed as part of the public health responses to the COVID-19 pandemic as well. This article argues that there is a growing need to steer digital transformation toward critically informed digital citizenship, so that the provenance of digital data and knowledge is held to account from scientific design to implementation science, whether they concern academic or Industry 4.0 paradigms of innovation. There are enormous potentials and expectations from digital transformation in an era of COVID-19 and digital health. For this potential to materialize in ways that are efficient, democratic, and socially just, critical digital citizenship offers new ways forward. Systems science scholarship stands to benefit from a broadening of the focus on high-throughput omics technologies to a realm of critical digital citizenship, so the digital health innovations are well situated in their societal and political contexts.

Big Data , COVID-19 , Humans , Pandemics , Citizenship , Industry