Abstract
Various industries worldwide have been severely affected by the COVID-19 pandemic, highlighting the gaps between social systems and forcing major transformations of our lives. To understand and mitigate the phenomena related to the unprecedented danger of COVID-19, we have become acutely aware of the importance of data distribution, exchange, and sharing across fields; indeed, various data are published and used in decision-making processes. However, although many international organizations and companies have been publishing data and adopting relevant measures, data sharing regarding the question of what data are required for any purpose is insufficient; that is, data are principally provided by organizations who publish the data unilaterally; currently, data-related needs are not shared or leveraged. To address this issue, we introduce the concept of “data origination.” Data origination is the act of designing/acquiring/utilizing data that considers the subjective knowledge and diversity of perspectives of humans, and that aims to elucidate and support this process. We also discuss a case study of data needs and unexplored data externalization conducted during the COVID-19 pandemic, based on data origination.
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Notes
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In this model, a mechanism is studied where knowledge further reinforces perceptual and conceptual filters, and influences the world as actions; however, a detailed discussion is omitted in this article.
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Naturally, there is potential for human interpretation in the process where information is obtained from data, and the relevant analytical tools must be selected with care.
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Acknowledgements
This study was supported by JSPS KAKENHI (JP19H05577 and JP20H02384), the “Startup Research Program for Post-Corona Society” of Academic Strategy Office, School of Engineering, the University of Tokyo, the “COVID-19 AI and Simulation Project” of the Office for Novel Coronavirus Disease Control, Cabinet Secretariat, Government of Japan, and the MEXT Quantum Leap Flagship Program (MEXT Q-LEAP) under Grant JPMXS0118067246. We thank Editage for providing English language editing.
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Hayashi, T., Ohsawa, Y. (2023). Externalization of Unexplored Data with Data Origination: Case Analysis of Person-to-Object Contact Data During COVID-19 Pandemic. In: Ohsawa, Y. (eds) Living Beyond Data. Intelligent Systems Reference Library, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-031-11593-6_13
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DOI: https://doi.org/10.1007/978-3-031-11593-6_13
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