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The Victoria and Albert Museum (V&A) has one of the world’s largest museum environmental monitoring systems. Over the last 10 years, this system has collected data from over 500 sensors across several sites. This data has been processed, analysed and communicated using data science tools from R and RStudio. These tools have saved hours of data processing time, increased engagement with key stakeholders, and ensured the safety of the collections. This paper explores how these data science tools fit into the V&A’s strategy for collections management. This paper will also introduce some methods of transforming, modelling, and translating environmental data into insights that can be communicated to museum stakeholders.

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Harnessing Data Science Technology for Environmental Monitoring at the V&A

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Bhavesh Shah,
  • Emily R Long

摘要

The Victoria and Albert Museum (V&A) has one of the world’s largest museum environmental monitoring systems. Over the last 10 years, this system has collected data from over 500 sensors across several sites. This data has been processed, analysed and communicated using data science tools from R and RStudio. These tools have saved hours of data processing time, increased engagement with key stakeholders, and ensured the safety of the collections. This paper explores how these data science tools fit into the V&A’s strategy for collections management. This paper will also introduce some methods of transforming, modelling, and translating environmental data into insights that can be communicated to museum stakeholders.