Added "OSG User School 2018" article & assets

_posts/2018-10-25-osg-user-school.md

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+---
+title: "OSG User School 2018"
+date: 2018-10-25 12:00:00 -0600
+categories: School
+---
+
+The OSG User School 2018 was held at the University of Wisconsin–Madison on July 9–13.  This year’s event set a new
+record with 65 participants in total, up from 56 participants in 2017.  And due to the large and record-setting number
+of applicants, 140, it was also one of the most selective offerings of the School.
+
+Participants included mostly graduate students, post-doctoral researchers, a couple of advanced undergraduates, some
+faculty, and some research staff from research institutions in the United States (and one each from Brazil, South Korea,
+and Uganda).  The range of scholarly domains was very diverse, including physics, biology, chemistry, medicine, several
+branches of engineering, statistics, earth sciences, animal sciences, plant sciences, neuroscience, and economics.
+Participants were selected by demonstrating need for large-scale computing and by being in a position to transform their
+scholarly work through computation.  The instructors this year were Brian Lin, and Derek Weitzel from the OSG; Bala
+Desinghu, from Rutgers University (and formerly OSG staff); plus Christina Koch and Lauren Michael from the UW–Madison’s
+Center for High Throughput Computing.
+
+This year’s curriculum continued the tradition of focusing on hands-on practice with a wide variety of user tools,
+providing a solid grounding for advanced and theoretical topics later in the School as well as further learning
+afterward.  Much of the curriculum was carried over from 2017, with minor updates to stay current.  This year, though,
+there was more discussion about accessing different kinds of computing resources, such as graphics-processing units
+(GPUs), and about expanding resource pools using commercial clouds, such as Amazon EC2.  The larger changes reflected
+both changes in the technologies involved plus improved pedagogical approaches based on experiences with past OSG User
+Schools and other science end-user engagements.
+
+All of the training materials from the School remain available online after the event, to be available to others around
+the world and to serve as reference material.  Participants also received several clear options for getting ongoing help
+with their large-scale computing needs.  Plus, every participant left the School with at least two ways to run jobs — an
+account on a UW–Madison HTCondor submit node and an OSG Connect account — so that there are as few barriers to computing
+and storage resources as possible.
+
+
+<figure class="figure">
+  <img src="/assets/images/osg-user-school-2018.png" class="figure-img img-fluid rounded" alt="Participants of the OSG User School 2018">
+  <figcaption class="figure-caption">Participants of the OSG User School 2018.</figcaption>
+</figure>
+
+From formal training evaluations to informal comments and emails, the School was clearly a success.  Participants were
+happy with the program, with how much they learned, and with the new paths that are now open to them.  Further, many
+participants completed a final written assignment after the event, describing a research computing challenge and their
+plans for applying material from the School to handle the challenge using distributed high throughput computing.  From
+these assignments, it is clear that most participants have concrete, realistic plans to advance their research through
+computing, and many have already begun doing so.
+
+As it takes time for the full effect of the School training to be realized&nbsp;— for research and computing plans to be
+made, for planned work to be performed, and for results to be analyzed and written&nbsp;— we list here the known
+publications from 2017 School participants using OSG:
+
+**Patrick Forscher** (University of Arkansas) and colleagues investigated whether PI names on NIH R01 grant proposals
+could induce race or gender bias, the statistical sensitivity analysis for which used about 20,000 hours of computing on
+OSG.  The first resulting publication is:
+
+* Forscher, P. S., Cox, W. T. L., Brauer, M., & Devine, P. G. (in press).  An experiment manipulating Principal
+  Investigator names finds little to no race or gender bias in the initial reviews of NIH R01 grant proposals.  _Nature
+  Human Behaviour._  <https://doi.org/10.31234/osf.io/r2xvb>
+
+**Ariella Gladstein** (University of North Carolina at Chapel Hill) used whole-chromosome simulations to infer the
+demographic history of the Ashkenazi Jews with Approximate Bayesian Computation and, as part of that work, developed a
+tool (SimPrily) to perform such simulations and calculate population genetic summary statistics.  This work was enabled
+by using approximately 7 million hours of computing on OSG, XSEDE, University of Arizona, and University of Wisconsin
+resources.  The first two resulting publications are:
+
+* Gladstein, A. L., & Hammer, M. F. (2018).  _Substructured population growth in the Ashkenazi Jews inferred with
+  Approximate Bayesian Computation._  Manuscript submitted for publication.
+
+* Gladstein, A. L., Quinto-Cortés, C. D., Pistorius, J. L., Christy, D., Gantner, L., & Joyce, B. L. (2018).  SimPrily:
+  A Python framework to simplify high-throughput genomic simulations.  _SoftwareX, 7,_ 335–340.
+  <https://doi.org/10.1016/j.softx.2018.09.003>
+
+**Raymond Tsang** (Pacific Northwest National Laboratory) generated toy models for evaluating the suitability of various
+Bayesian priors for radioassay measurement results in projecting sensitivity of low-background experiments.  This work
+was enabled through the use of approximately 80,000 hours of computing on OSG.  The first resulting publication is:
+
+* Tsang, R. H. M., Arnquist, I. J., Hoppe, E. W., Orrell, J. L., & Saldanha, R. (2018).  _Treatment of material
+  radioassay measurements in projecting sensitivity for low-background experiments._  Manuscript submitted for
+  publication.  [arXiv:1808.05307v2](https://arxiv.org/abs/1808.05307)
+
+**Sarah Turner** (University of Wisconsin–Madison) processed hundreds of images and completed thousands of permutation
+tests for quantitative loci mapping of forty traits of carrot to help improve breeding and genetic studies.  This work
+used about 900 hours of computing on OSG, showing that it does not necessarily take a large number of computing hours to
+make a meaningful difference in research outcomes.  The first resulting publication is:
+
+* Turner, S. D., Ellison, S. L., Senalik, D. A., Simon, P. W., Spalding, E. P., & Miller, N. D. (2018).  _An automated,
+  high-throughput image analysis pipeline enables genetic studies of shoot and root morphology in carrot (Daucus carota
+  L.)._  Manuscript submitted for publication.  <https://doi.org/10.1101/384974>
+
+-- Tim Cartwright