<div dir="ltr"><div><div>Ted had also contributed some of those HDF5 materials to data carpentry last year:<br><a href="https://github.com/datacarpentry/datacarpentry/blob/master/lessons/R/materials/09-hdf5-R.Rmd">https://github.com/datacarpentry/datacarpentry/blob/master/lessons/R/materials/09-hdf5-R.Rmd</a><br><br></div>They're pretty hidden at the moment, which we should definitely fix.<br><br></div>Ethan<br></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Feb 11, 2015 at 8:56 AM, Leah Wasser <span dir="ltr"><<a href="mailto:lwasser@neoninc.org" target="_blank">lwasser@neoninc.org</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hey Data Carpentry folks,<br>
I've been working on some materials that teach the basics of working with HDF5. Some of these were created in collaboration with Ted Hart :) for a workshop we gave at ESA last year. I've built out a full set of materials starting with what the file format is, viewing it in a free viewer, creating a file and then working with data saved within a file that will simulate what NEON might provide in the future (and what other organizations provide). The second "batch" of materials dives into hyperspectral remote sensing which is a very common data types that utilizes HDF5. This gets more into the spatial data end of things.<br>
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<a href="http://neondataskills.org/HDF5/" target="_blank">http://neondataskills.org/HDF5/</a><br>
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I'd really appreciate any and all feedback on these materials as we refine them. The goal will be to use them again this august at our ESA workshop but also to build them into a larger set of materials that support working with larger datasets, spatial data, etc. And then we'll build a Python parallel.<br>
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Thank you for any and all constructive, critical feedback! This is a work in progress and I greatly appreciate the expertise housed in this group!<br>
Leah<br>
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