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FAIR Computational Workflows

Sarah COHEN-BOULAKIA


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4025295", 
  "title": "FAIR Computational Workflows", 
  "issued": {
    "date-parts": [
      [
        2020, 
        9, 
        2
      ]
    ]
  }, 
  "abstract": "<p>Computational workflows describe the complex multi-step methods that are used for data collection, data preparation, analytics, predictive modelling, and simulation that lead to new data products. They can inherently contribute to the <strong>FAIR data principles</strong>: by processing data according to established metadata; by creating metadata themselves during the processing of data; and by tracking and recording data provenance. These properties aid data quality assessment and contribute to secondary data usage. Moreover, workflows are digital objects in their own right.</p>\n\n<p>This is a presentation of the paper <a href=\"https://doi.org/10.1162/dint_a_00033\">FAIR Computational Workflows</a>, published in <em>Data Intelligence</em>. The paper argues that FAIR principles for workflows need to address their specific nature in terms of their composition of executable software steps, their provenance, and their development.</p>\n\n<p>Presented at <a href=\"https://eccb2020.info/programme-at-a-glance/\">ECCB 2020</a> Workshop on <a href=\"http://FAIR Computational Workflows\">FAIR Computational Workflows</a>.</p>", 
  "author": [
    {
      "family": "Sarah COHEN-BOULAKIA"
    }
  ], 
  "id": "4025295", 
  "event-place": "virtual", 
  "type": "speech", 
  "event": "19th European Conference on Computational Biology (ECCB)"
}
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