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Transforming a museum to be data-driven (using R)

Alice Daish


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{
  "description": "<p><em>How do you transform a traditionally un-data-orientated organisation into being data-driven armed with data science processes and plenty of enthusiasm?</em></p>\n\n<p><em>With the exponential growth of data, more and more organisations are demanding to become data-driven. Seeking value from their data, big data and data science initiatives; jobs and skill sets have risen up the organisations agenda. The first data scientist at a museum shares her experience and learning on the journey to transform the British Museum to be data-driven by 2018.</em></p>\n\n<p><em>How is one of the most popular museums in the world, with 6.8 million annual visitors, using data science to achieve a data-driven transition?</em></p>\n\n<ul>\n\t<li><em>Valuing of Data </em></li>\n\t<li><em>Data Science at the British Museum </em></li>\n\t<li><em>Transformation advice</em></li>\n\t<li><em>Vision for the future</em></li>\n</ul>\n\n<p><em>By valuing data and using data science processes, any organisation can become data-driven.</em></p>", 
  "license": "http://creativecommons.org/licenses/by-nc/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "British Museum", 
      "@type": "Person", 
      "name": "Alice Daish"
    }
  ], 
  "url": "https://zenodo.org/record/437150", 
  "datePublished": "2017-03-15", 
  "keywords": [
    "data science", 
    "data driven", 
    "cultural heritage", 
    "museum", 
    "R", 
    "rstats"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.437150", 
  "@id": "https://doi.org/10.5281/zenodo.437150", 
  "@type": "PresentationDigitalDocument", 
  "name": "Transforming a museum to be data-driven (using R)"
}
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