{
  "@type": "dcat:Dataset",
  "accessLevel": "public",
  "accrualPeriodicity": "irregular",
  "bureauCode": [
    "006:55"
  ],
  "contactPoint": {
    "fn": "Robert D. McMichael",
    "hasEmail": "mailto:robert.mcmichael@nist.gov"
  },
  "description": "Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters.  Given an parametric model - analogous to a fitting function - Bayesian inference uses each measurement 'data point' to refine model parameters.  Using this information, the software suggests measurement settings that are likely to efficiently reduce uncertainties.   A TCP socket interface allows the software to be used from experimental control software written in other programming languages. Code is developed in Python, and shared via GitHub's USNISTGOV organization.",
  "distribution": [
    {
      "description": "Special instructions for reviewers",
      "downloadURL": "https://data.nist.gov/od/ds/mds2-2908/Review%20README.txt",
      "format": "plain text",
      "mediaType": "text/plain",
      "title": "README"
    },
    {
      "description": "Zip file of ORE Repo",
      "downloadURL": "https://data.nist.gov/od/ds/mds2-2908/obe-repo.zip",
      "format": "ZIP",
      "mediaType": "application/gzip",
      "title": "ORE Repo Files"
    },
    {
      "description": "Zip with files from NIST pages",
      "downloadURL": "https://data.nist.gov/od/ds/mds2-2908/nist-pages.zip",
      "format": "ZIP",
      "mediaType": "application/gzip",
      "title": "NIST Pages Files"
    }
  ],
  "identifier": "ark:/88434/mds2-2908",
  "issued": "2023-02-22",
  "keyword": [
    "Bayesian",
    "GitHub pages template",
    "adaptive measurement",
    "experimental design",
    "optbayesexpt",
    "python"
  ],
  "landingPage": "https://pages.nist.gov/optbayesexpt/",
  "language": [
    "en"
  ],
  "license": "https://www.nist.gov/open/license",
  "modified": "2023-01-10 00:00:00",
  "programCode": [
    "006:045"
  ],
  "publisher": {
    "@type": "org:Organization",
    "name": "National Institute of Standards and Technology"
  },
  "theme": [
    "Mathematics and Statistics:Experiment design"
  ],
  "title": "Optimal Bayesian Experimental Design Version 1.2.0"
}