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<title>Daniel de Oliveira - Featured Book</title>
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    <h1>Featured Book</h1>
    <p>I would like to highlight the book <strong><a href="https://link.springer.com/book/10.1007/978-3-031-01872-5" target="_blank">Provenance and Data Management for Scientific Workflows</a></strong>, co-authored by <strong>Daniel de Oliveira, Ji Liu, and Esther Pacitti</strong>. This work provides a thorough exploration of managing data-intensive workflows in scientific research, focusing on reproducibility, transparency, and efficiency.</p>

    <h2>Key Topics Covered</h2>
    <ul>
      <li>Workflow management principles and best practices</li>
      <li>Workflow Execution in a Single-Site Cloud</li>
      <li>Workflow Execution in a Multi-Site Cloud</li>
      <li>Real-world case studies in bioinformatics, astronomy, and engineering</li>
      <li>Workflow Execution in DISC Environments</li>
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    <p>This book is a valuable resource for researchers, data scientists, and professionals interested in practical and theoretical insights on scientific workflow management.</p>
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