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The signac framework helps users manage and scale file-based workflows, facilitating data reuse, sharing, and reproducibility. It provides a simple and robust data model to create a well-defined indexable storage layout for data and metadata. This makes it easier to operate on large data spaces, streamlines post-processing and analysis and makes data collectively accessible.
Development and deployment supported by MICCoM, as part of the Computational Materials Sciences Pro- gram funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, under Subcontract No. 6F-30844. Project conceptualization and implementation supported by the National Science Foundation, Award # DMR 1409620.
python, data, scientific computing, workflow, sharability, data management, reproducibility
python, data, scientific computing, workflow, sharability, data management, reproducibility
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 6 |

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