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75	75
76	76	* **Run the notebook**
77	77	In the jupyter hub, navigate to //drive/My Libraries/My Library/pipeline/showcase_notebooks/run_snakemake_in_collab.ipynb//, or where you copied the //pipeline// folder to.
78		-Follow the notebook to install the required packages into your Python kernel, set the output path, and execute the pipeline with snakemake
	78	+Follow the notebook to install the required packages into your Python kernel, set the output path, and execute the pipeline with snakemake.
	79	+
	80	+* **Coming soon**
	81	+** Use of KnowledgeGraph API
	82	+** Provenance Tracking
	83	+** HPC support
79	79
80	80	=== ii) Local execution ===
81	81
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114	114
115	115	All results are stored in the path specified in the //settings.py// file. The folder structure reflects the structuring of the pipeline into stages and blocks. All intermediate results are stored as //.nix// files using the [[Neo data format>>https://neo.readthedocs.io/en/stable/]] and can be loaded with ##neo.NixIO('/path/to/file.nix').read_block()##. Additionally, most blocks produce a figure, and each stage a report file, to give an overview of the execution log, parameters, intermediate results, and to help with debugging. The final stage (//stage05_wave_characterization//) stores the results as[[ //pandas.DataFrames//>>https://pandas.pydata.org/]] in //.csv// files, separately for each measure as well as in a combined dataframe for all measures.
116	116
117		-== Outlook ==
118		-
119		-* Using the **KnowledgeGraph API **to insert data directly from the Knowledge Graph into the pipeline and also register and store the corresponding results as Analysis Objects. Such Analysis Objects are to incorporate **Provenance Tracking, **using [[fairgraph>>https://github.com/HumanBrainProject/fairgraph]],** **to record the details of the processing and analysis steps.
120		-* Adding support for the pipeline to make use of **HPC** resources when running on the collab.
121		-* Further extending the available **methods** to address a wider variety of analysis objectives and support the processing of other datatypes. Additional documentation and guides should also make it easier for non-developers to contribute new method blocks.
122		-* Extending the **application** of the pipeline to the analysis of other types of activity waves and oscillations.
123		-* Integrating and co-developing new features of the underlying **software tools **[[Elephant>>https://elephant.readthedocs.io/en/latest/]], [[Neo>>https://neo.readthedocs.io/en/stable/]], [[Nix>>https://github.com/G-Node/nix]], [[Snakemake>>https://snakemake.readthedocs.io/en/stable/]].
124		-
125	125	== References ==
126	126
127	127	* [[Celotto, Marco, et al. "Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques." //Methods and Protocols// 3.1 (2020): 14.>>https://doi.org/10.3390/mps3010014]]
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132	132
133	133	== License (to discuss) ==
134	134
135		-All text and example data in this collab is licensed under Creative Commons CC-BY 4.0 license. Software code is licensed under GNU General Public License v3.0.
	132	+All text and example data in this collab is licensed under Creative Commons CC-BY 4.0 license. Software code is licensed under a modified BSD license.
136	136
137	137	[[image:https://i.creativecommons.org/l/by/4.0/88x31.png||style="float:left"]]
138	138
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147	147	)))
148	148
149	149
150		-== ==
	147	+== Executing the pipeline ==
151	151
152	152	(% class="col-xs-12 col-sm-4" %)
153	153	(((