signac-a-python-framework-for-data-and-workflow-management-scipy-2018-vyas-ramasubramani.json

{
  "copyright_text": null,
  "description": "Computational studies in physics, chemistry, and materials science are\nfrequently characterized by well-parameterized but constantly evolving\ndata schemas. Poor management of these dynamic schemas can significantly\nimpede computational research. Our talk showcases the signac framework,\nan open- source Python package designed for simple data and workflow\nmanagement, particularly in high performance computing environments. The\nframework's flexible data model allows easy adaptation into pre-existing\nfile-based workflows while also providing critical database\nfunctionality such as filtering, searching, and grouping data. signac\nalso provides tools to develop complex workflows operating on its data\nspaces, enabling the simple, efficient, and reproducible execution of\ncomputational studies.Presenter(s): Speaker: Vyas Ramasubramani,\nUniversity of Michigan Author: Carl Adorf, University of Michigan\nAuthor: Paul M. Dodd, University of Michigan Author: Bradley Dice,\nUniversity of Michigan Author: Sharon C. Glotzer, University of Michigan\n",
  "duration": 1488,
  "language": "eng",
  "recorded": "2018-07-13",
  "related_urls": [
    {
      "label": "Conference schedule",
      "url": "https://scipy2018.scipy.org/ehome/299527/721463/"
    },
    {
      "label": "Conference slides",
      "url": "https://github.com/deniederhut/Slides-SciPyConf-2018"
    }
  ],
  "speakers": [
    "Vyas Ramasubramani"
  ],
  "tags": [],
  "thumbnail_url": "https://i.ytimg.com/vi/CCKQH1M2uR4/maxresdefault.jpg",
  "title": "signac: A Python Framework for Data and Workflow Management",
  "videos": [
    {
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=CCKQH1M2uR4"
    }
  ]
}