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IPython Notebook, originally developed by Fernando Perez of University of Berkeley (where the core development team is currently based) is a browser-based environment for interactive computing. Users can write, edit and re-run Python scripts. IPython Notebook has support for interactive data visualization and report presentation. A notebook can be saved and shared. The code saved in notebooks can be modified and re-run using the same or different data. The record of a notebook “run” can be saved and displayed in a static Notebook Viewer. IPython Notebooks with embedded workflows can be saved and shared; their static version can be viewed in the IPython Notebook Viewer. Taverna is a suite of open source tools that allow the design and execution of scientific workflows. The running of Taverna Workflows within IPython Notebook allows users to include existing workflows as part of their interactive computing. This provides IPython users with access to functionality that has been developed for a significant amount of time and to the large number of shared workflows. In addition, use of workflows provides access to functionality within workflows that may not be readily available within the Python environment. For workflow developers, calling the workflows from IPython Notebook allows: pre-processing of input data, the chaining of workflow executions with data transformations in Python, and the presentation of results and report generation using IPython’s extensive capabilities.
python, notebook, taverna, iPython
python, notebook, taverna, iPython
| 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). | 0 | |
| 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. | Average | |
| 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. | Average |
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