{
  "abstract": "The growing demand for accessible, high-quality and privacy-preserving health data has led to increased interest in synthetic health data as a promising solution to overcome data scarcity and legal barriers.1 Synthetic data refer to information that has been created artificially to mimic real-world observations. This is particularly relevant in the context of rare diseases, where real-world data are often fragmented, siloed or insufficient for robust artificial intelligence (AI) development and clinical research.2 This paper summarises the outcomes of a multidisciplinary Sandpit workshop involving experts with lived experiences in rare diseases, as well as experts in clinical medicine, data science, cybersecurity and medical informatics. The goal was to define a shared vision and roadmap for a synthetic health data repository (SHARE).",
  "authors": [
    {
      "affiliations": [
        "Goethe University Frankfurt, University Medicine Frankfurt, Institute of Medical Informatics, Frankfurt, Germany"
      ],
      "name": "Richard Noll"
    },
    {
      "affiliations": [
        "German Research Center for Artificial Intelligence, Lübeck, Germany"
      ],
      "name": "Philipp Koch"
    },
    {
      "affiliations": [
        "Hasso Plattner Institute, Chair of Digital Health, Economics and Policy, Potsdam, Germany"
      ],
      "name": "Benedikt Langenberger"
    },
    {
      "affiliations": [
        "Chair of Digital Health, Hasso Plattner Institute, Chair of Digital Health, Economics and Policy, Potsdam, Germany",
        "Department of Hepatology and Gastroenterology, Charité -Universitätsmedizin Berlin, Berlin, Germany"
      ],
      "name": "Philipp C Stoffers"
    },
    {
      "affiliations": [
        "ARVC-Selbsthilfe e.V, Unterschleissheim, Germany"
      ],
      "name": "Ruth Biller"
    },
    {
      "affiliations": [
        "Goethe University Frankfurt, University Medicine Frankfurt, Institute for Occupational, Social and Environmental Medicine, Frankfurt am Main, Germany"
      ],
      "name": "Andreas Goldschmidt"
    },
    {
      "affiliations": [
        "Medical Imaging & AI, Bayer AG, Leverkusen, Germany"
      ],
      "name": "Sadegh Mohammadi"
    },
    {
      "affiliations": [
        "Institute for Medical Informatics and Biometry, TUD Dresden University of Technology, Dresden, Germany"
      ],
      "name": "Michele Zoch"
    },
    {
      "affiliations": [
        "Open Innovation in Science Center, Ludwig Boltzmann Gesellschaft, Vienna, Austria"
      ],
      "name": "Gabriela Gan"
    },
    {
      "affiliations": [
        "Data4Trust AG, Maisprach, Switzerland"
      ],
      "name": "Benjamin Szilagyi"
    },
    {
      "affiliations": [
        "Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark"
      ],
      "name": "Nicolai Dinh Khang Truong"
    },
    {
      "affiliations": [
        "Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark"
      ],
      "name": "Richard Röttger"
    },
    {
      "affiliations": [
        "Institute of Medical Informatics, D4L Data4Life gGmbH, Potsdam, Germany"
      ],
      "name": "Gennadi Rabinovitch"
    },
    {
      "affiliations": [
        "SBA Research, Vienna, Austria",
        "Research Group Security and Privacy, ³ University of Vienna, Vienna, Germany"
      ],
      "name": "Andreas Ekelhart"
    },
    {
      "affiliations": [
        "SBA Research, Vienna, Austria"
      ],
      "name": "Daniela Martinez-Duarte"
    },
    {
      "affiliations": [
        "SBA Research, Vienna, Austria"
      ],
      "name": "Rudolf Mayer"
    },
    {
      "affiliations": [
        "Goethe University Frankfurt, University Medicine Frankfurt, Institute of Medical Informatics, Frankfurt, Germany"
      ],
      "name": "Holger Storf"
    },
    {
      "affiliations": [
        "Goethe University Frankfurt, University Medicine Frankfurt, Institute of Medical Informatics, Frankfurt, Germany"
      ],
      "name": "Jannik Schaaf"
    }
  ],
  "title": "SHARE: towards usable, trustworthy and interoperable synthetic health data for rare diseases",
  "uid": "f7674aaa-a93e-56c6-b9be-fefd94747198"
}