Name: cq-notebooks
Owner: NCATS Data Translator Project - Tangerine Team
Description: Notebooks for answering competency questions
Created: 2017-03-10 19:27:39.0
Updated: 2017-12-06 18:30:28.0
Pushed: 2018-01-14 22:39:54.0
Homepage: null
Size: 9322
Language: Jupyter Notebook
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Notebooks for answering competency questions
Our goal here is to create a catalog of working examples that demonstrate how to access, transform, integrate and visualize the diverse data sources we intend to use for projects like Translator.
We are currently using Jupyter notebooks as our means of documenting, prototyping, and sharing code. As some of these experiments mature into working prototype pipelines, we intend to extract this functionality from the notebooks and migrate it into a production pipeline.
Orange team queries are initially collected in the spreadsheet here, with tabs for different collections of notebooks (e.g. demonstrator-driven queries, general benchmarking queries). From this staging area, select queries are implemented in Jupyter or Zeppelin notebooks. A detailed overview of spreadsheet contents and the workflow for CQ development can be found in the documents here and here.
Notebooks under active development each have an associated directory in this repo that includes the notebook itself, a descriptive README, and any associated code or data. For each notebook, a Github ticket is also created and tagged with a notebook-status label to track its status, ownership, and outcomes. These tickets enable a dashboard-like overview of progress notebooks to be generated here.
You will need Python (e.g., Python 3.5.2).
ualenv env
ce env/bin/activate
install jupyter ipython pandas requests
ce env/bin/activate
ter notebook
TODO: we should aim to drive this list from Smart API registry