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describe.html
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<!DOCTYPE html>
<html lang="en">
<head>
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<title>Describe - ReproNim</title>
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<section class="section-1">
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<div class="col-sm-4 col-xs-8">
<h1 class="logo"><a href="index.html">ReproNim</a></h1>
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<li><a href="discover.html">Discover</a></li>
<li><a href="describe.html">Describe</a></li>
<li><a href="do.html">Do</a></li>
<li><a href="teach.html">Teach</a></li>
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<div class="col-md-12">
<h1 class="main-page-header">Describe</h1>
<h3 class="main-sub-header">Enable reproducibility by design!</h3>
</div>
</div>
<div class="row">
<div class="col-md-12">
<p>To provide the tools necessary for reproducible analyses. The analyses must
also generate queryable, machine-readable data and results using
interoperable and standardized data models. We aim to:
</p>
<ul>
<li>Design interoperable Data Models, Workflows and Linked Results</li>
<li>Create reusable workflows with provenance</li>
<li>Test computational reproducibility and robustness</li>
<li>Integrate tools in Brainverse</li>
</ul>
<p>Neuroimaging data have become richer, with larger cohorts of participants,
and a greater variety of acquisitions. A large number of useful analysis
methods are now available, and many pipeline tools make such analysis
efficient.
</p>
<ul>
<li>Interpreting and comparing scientific results and enabling reusable analysis require understanding provenance, i.e. how the data were generated and processed.</li>
<li>To be useful, the provenance must be understandable, easily communicated, and captured automatically in machine accessible form.</li>
<li>The <a href="http://nidm.nidash.org/">NIDM</a> specification captures data, analyses details across software and workflow tools, and results. </li>
</ul>
<p>Currently we are focused on the following projects. You can help us by trying them, contributing to them, or by sharing your ideas on how to improve them.</p>
</div>
</div>
</div>
</section>
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<div class="container">
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<h3><a href="http://nidm.nidash.org">NIDM</a></h3>
<p>
Describe experiment setup and data, analysis details, and results in a structured manner.
This is a collaboration with the Neuroimaging Data Sharing Working group, to develop
and maintain data models and software to support rich and structured description
of research workflows.
</p>
<ul>
<li>To create and support a community using standards</li>
<li>Tools to help researchers describe their data, software, and results</li>
<li>Tools to help developers integrate structured description into software</li>
</ul>
<p>
These tools will include publishing, visualizing, and validating data
described using NIDM. It will enable interoperability with existing efforts
(e.g., <a href="https://bids.neuroimaging.io/">BIDS</a>, <a href="https://www.datalad.org/">DataLad</a>, <a href="https://nipype.readthedocs.io/en/latest/">Nipype</a>).
<a href="http://doi.org/10.5334/dsj-2017-045">Example: Keator et al., 2017</a>
</p>
<ul>
<li><a href="github.com/incf-nidash/PyNIDM">Python-based API</a> following the
simple organizational structure of NIDM-Experiment documents.
Functions to create, query, export, import, and transform NIDM documents.
</li>
<li>
<b>NIDM Terminology / Ontology: </b> NIDM ontology reuses existing terms from
several other where appropriate definitions exist. Current work is focused on
data descriptions, DICOM ontology, and a scientific workflow ontology.
</li>
</ul>
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<h3><a href="https://github.com/ReproNim/brainverse">BrainVerse</a></h3>
<p>ReproNim is developing <strong>BrainVerse</strong> to help researchers manage, track
and share information in a comprehensive format. Brainverse is an open-source,
cross-platform desktop application to enable researchers add to reproducible
practices into every project.
</p>
<ul>
<li>An electronic laboratory notebook built as a cross platform desktop application</li>
<li>Enables users to plan experiments, collect, analyze and reuse data, and collaborate</li>
<li>Adds semantic annotation to data with relevant metadata based on NeuroImaging data Model
(NIDM) making experimental neuroimaging study more reproducible, and making data FAIR</li>
<li>Intercept the research workflow at planning stage, curating (raw, processed, results)
data at the source and helping users to annotate every step of the process.</li>
</ul>
<p>We are looking for beta users of the software and JavaScript developers to
extend BrainVerse.
</p>
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<div class="col-sm-4">
<h3><a href="https://github.com/ReproNim/regtests">Testkraut</a></h3>
<p>Create a comprehensive framework for robustness testing. This will enable continuous
evaluation of algorithms under different operating system environments. Neuroimaging
relies on numerical computations and results can depend on:
<ul>
<li>workflow used by scientist</li>
<li>data used as input</li>
<li>external software used in the analysis</li>
<li>computational environment</li>
</ul>
</p>
<p>
Testing analysis in various computational environments allows to:
<ul>
<li>learn about the analysis limitations</li>
<li>increase confidence in the analysis before publishing the results</li>
<li>check the results obtained using a newer versions of external software</li>
<li>or computational environment any time after publishing</li>
</ul>
</p>
<p>
ReproNim's Testkraut implementation will allow researchers to continuously evaluate
the performance of algorithms developed in the community and to choose the most
appropriate tools for a given analysis task.
</p>
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