330 lines
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330 lines
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<title>VAMP it up!</title>
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<meta name="description" content=" some description ">
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<meta name="author" content="Michael Hanke">
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<!-- Any section element inside of this container is displayed as a slide -->
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<div class="slides">
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<section>
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<h2>VAMP it up!<br><small>A pragmatic approach to reusable research outputs</small></h2>
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<p>Michael Hanke</p>
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<p>
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<small>Institute of Neuroscience and Medicine, Brain & Behavior (INM-7),
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Research Center Jülich</small><br>
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<small>Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf</small></br>
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<a href="http://psychoinformatics.de">http://psychoinformatics.de</a></p>
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<p style="margin-top:50px"><img style="height:100px;margin-right:100px" data-src="../pics/fzj_logo.svg" />
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<img style="height:100px" data-src="../pics/hhu_logo.svg" /></p>
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</section>
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<section>
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<section data-markdown data-transition="none"><script type="text/template">
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<note><a href="http://pymvpa.org">http://pymvpa.org</a></note>
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Note:
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open-source neuroimaging ML toolbox, In my Phd
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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<note><a href="http://neuro.debian.org">http://neuro.debian.org</a></note>
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Note:
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largest repository of readily usable open-source neuro-software
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</script></section>
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<section>
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<h2 style="font-size:150%"><em>Open</em>, "naturalistic" data: studyforrest.org</h2>
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<img style="width:45%" data-src="../pics/forrest_gump_xlg.jpg" />
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<img style="margin-bottom:8%" data-src="../pics/forrest_data_records.png" />
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<note>Hanke, Baumgartner, Ibe, Kaule, Pollmann, Speck, Zinke, & Stadler (2014)
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<em>A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie</em>. Scientific Data, 1:140003.
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<a href="http://www.nature.com/articles/sdata20143">http://www.nature.com/articles/sdata20143</a>
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</note>
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<aside class="notes">
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ongoing open-data experiment
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</aside>
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</section>
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</section>
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<section>
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<section>
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<ul style="list-style-type:none">
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<li><h1 style="display:inline">F</h1>indable</li>
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<li><h1 style="display:inline">A</h1>ccessible</li>
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<li><h1 style="display:inline">I</h1>nteroperable</li>
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<li><h1 style="display:inline">R</h1>eusable</li>
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</ul>
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<note><a href="https://www.go-fair.org/fair-principles">https://www.go-fair.org/fair-principles</a></note>
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<aside class="notes">
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since 2016 (five years), no way around it, declared "done"
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</aside>
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</section>
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<section>
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<ul style="list-style-type:none">
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<li><h1 style="display:inline">F?</h1> I already have it, it's right here!</li>
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<li><h1 style="display:inline">A?</h1> I am working with it already, I made it!</li>
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<li><h1 style="display:inline">I?</h1> With what?</li>
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<li><h1 style="display:inline">R?</h1> First let me finish this PhD and then we talk, OK?</li>
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</ul>
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<aside class="notes">
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individual/limited perspective less clear, tendency to delay and make expensive
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</aside>
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</section>
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<section data-markdown data-transition="none"><script type="text/template">
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<!-- .element: height="1000px" -->
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<imgcredit>Divebomb Records</imgcredit>
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Note:
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My proposal: Let's think about VAMP instead
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</script></section>
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<section>
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<ul style="list-style-type:none">
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<li><h1 style="display:inline">V</h1>ersion-controlled</li>
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<li><h1 style="display:inline">A</h1>ctionable metadata</li>
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<li><h1 style="display:inline">M</h1>odular</li>
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<li><h1 style="display:inline">P</h1>portable</li>
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</ul>
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<aside class="notes">
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not the band, but...
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</aside>
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</section>
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</section>
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<section>
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<section data-markdown data-transition="none"><script type="text/template">
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## Exhaustive tracking of research components
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<!-- .element: width="100%" -->
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Well-structured datasets (using community standards), and portable computational environments — and their evolution — are the precondition for reproducibility
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Note:
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your community could be really small (your lab), when data are precious resources
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will be spent to understand it, but information must be capture to make this possible
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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## Capture computational provenance
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<!-- .element: width="100%" -->
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Which data was needed at which version, as input into which code, running with what parameterization in which
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computional environment, to generate an outcome?
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Note:
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The missing link: even when everything is shared, we still don't know how to start.
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README is minimum, but executable prov-records are much better.
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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## Exhaustive capture enables portability
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<!-- .element: width="100%" -->
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Precise identification of data and computational environments, combined for provenance records form a comprehensive and portable data structure, capturing all aspects of an investigation.
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Note:
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Does it fly? Can you give it to someone? Or can you take it with you to your new lab?
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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## Reproducibility strengthens trust
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<!-- .element: width="100%" -->
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Outcomes of computational transformations can be validated by authorized 3rd-parties. This enables audits, promotes accountability, and streamlines automated "upgrades" of outputs
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Note:
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Goal is automated reproducibility, enables assessment of robustness and benchmarking algorithmic developments
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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## Ultimate goal: (re-)usability
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Verifiable, portable, self-contained data structures that track all aspects of an investigation exhaustively can be (re-)used as modular components in larger contexts — propagating their traits
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Note:
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With these in place, re-usability is a small(er) step
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</script></section>
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</section>
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<section>
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<section data-markdown><script type="text/template">
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## DataLad: manage evolution of digital objects
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<!-- .element: width="1000" style="margin-bottom:-50px" -->
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Consume, create, curate, analyze, publish, and query data with full provenance capture and "universal" metadata support.
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<p style="font-size:80%">
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DataLad is free and open source (MIT-licensed).
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</p>
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http://datalad.org
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Note:
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DataLad implements al these features. Go get it at URL
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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## Advantages of the VAMP attitude
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- *Overlay data structure* hides away peculiarities of (current) environment choices for storage and computation<br>
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— focus on content, not infrastructure
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- Self-contained units that are *valid and complete without any external services*<br>
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— federation-ready for improved resilience
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- Metadata plurality puts *focus on metadata validity* (for your own work) without becoming a problem for global standardization efforts<br>
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— ability to verify detailed metadata is more useful than today's
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choice of terminology and minimal description standard
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- Promotes *long-term curation and stewardship* for flexibly reusable unit<br>
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— yields proven and trusted resources for incremental science
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</script></section>
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<section data-markdown data-transition="none"><script type="text/template">
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### "Automatic" interoperability with 3rd-party solutions
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<!-- .element: width="600px" style="margin-bottom:-30px;margin-top:-10px"-->
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- Technology directly used by OpenNeuro, CBRAIN platform, BrainLife.io,
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and compatible with AWS/S3, GIN, Dropbox, etc. (optional strong encryption)
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- 100+TB of research data, homogenously accessible regardless of hosting choices
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(datasets.datalad.org)
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Note:
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Interoperability is now an orthogonal aspect that can be improved collaboratively
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</script></section>
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<section data-markdown><script type="text/template">
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## Reproducible paper - a Magic trick?
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<!-- .element: width="1000" -->
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- See for yourself: https://youtu.be/_I3JFhJJtW0?t=861
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- Get step-by-step instructions: http://handbook.datalad.org/usecases/reproducible-paper.html
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Note:
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No time to explain, see for yourself
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</script></section>
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<section data-markdown><script type="text/template">
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## Open science education
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<!-- .element: class="ackimg" -->
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<!-- .element: width="950" style="margin-top:-20px;margin-bottom:-10px" -->
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http://handbook.datalad.org
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- **educational materials** on technologies — **targeting scientists**, not developers (executable paper,
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student surpervisor workflow, ...)
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- handbook with 400+ pages on concepts, workflows, and use cases (work in progress, led by Adina Wagner)
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Note:
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RDM Education is key. Handbook helps people be more productive, yielding more FAIR resources as an outcome, but not as the main goal.
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</script></section>
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</section>
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<section>
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<h2>Acknowledgements</h2>
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<table>
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<tr style="vertical-align:middle">
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<td style="vertical-align:middle">
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<ul style="font-size:80%">
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<li>Yaroslav Halchenko</li>
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<li>Benjamin Poldrack</li>
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<li>Kyle Meyer</li>
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<li>Adina Wagner</li>
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<li>30+ Datalad contributors</li>
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</ul>
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</td>
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<td style="vertical-align:middle">
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<img style="height:150px;margin-right:50px" data-src="../pics/nsf.png" />
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<img style="height:150px;margin-right:50pxi;margin-left:50px" data-src="../pics/binc.png" />
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<img style="height:150px;margin-left:50px" data-src="../pics/bmbf.png" />
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<br />
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<img style="height:80px;margin-top:-40px;margin-left:auto;margin-right:auto;width:100%" data-src="../pics/fzj_logo.svg" />
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<div style="margin-top:-20px">
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<img style="height:60px;margin-right:200px" data-src="../pics/erdf.png" />
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<img style="height:60px" data-src="../pics/LSA-Logo.png" />
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</div>
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<div style="margin-top:-20px">
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<img style="height:100px;margin:20px" data-src="../pics/vbc_logo.png" />
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</div>
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<div style="margin-top:-40px">
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<img style="height:120px;margin:20px" data-src="../pics/openneuro_logo.png" />
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<img style="height:120px;margin:20px" data-src="../pics/cbrain_logo.png" />
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<img style="height:140px;margin:20px" data-src="../pics/brainlife_logo.png" />
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</div>
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</td>
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</tr>
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</table>
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<p>Website: <a href="http://datalad.org">http://datalad.org</a><br />
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Documentation: <a href="http://handbook.datalad.org">http://handbook.datalad.org</a><br />
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Open data: <a href="http://datasets.datalad.org">http://datasets.datalad.org</a></p>
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</section>
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