Big data in contemporary electron microscopy: challenges and opportunities in data transfer, compute and management.

The second decade of the twenty-first century witnessed a new challenge in the handling of microscopy data. Big data, data deluge, large data, data compliance, data analytics, data integrity, data interoperability, data retention and data lifecycle are terms that have introduced themselves to the el...

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Publicado en:Histochemistry & Cell Biology Vol. 160; no. 3; pp. 169 - 193
Autores principales: Poger, David, Yen, Lisa, Braet, Filip
Formato: Journal Article
Publicado: Springer Nature Sep2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Big data in contemporary electron microscopy: challenges and opportunities in data transfer, compute and management.
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          Poger, David
          Yen, Lisa
          Braet, Filip
        affil: Microscopy Australia, The University of Sydney, 2006, Sydney, NSW, Australia
      sug:
      ab: The second decade of the twenty-first century witnessed a new challenge in the handling of microscopy data. Big data, data deluge, large data, data compliance, data analytics, data integrity, data interoperability, data retention and data lifecycle are terms that have introduced themselves to the electron microscopy sciences. This is largely attributed to the booming development of new microscopy hardware tools. As a result, large digital image files with an average size of one terabyte within one single acquisition session is not uncommon nowadays, especially in the field of cryogenic electron microscopy. This brings along numerous challenges in data transfer, compute and management. In this review, we will discuss in detail the current state of international knowledge on big data in contemporary electron microscopy and how big data can be transferred, computed and managed efficiently and sustainably. Workflows, solutions, approaches and suggestions will be provided, with the example of the latest experiences in Australia. Finally, important principles such as data integrity, data lifetime and the FAIR and CARE principles will be considered.
      pubtype: Academic Journal
      doctype: Journal Article
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    language: English
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