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<!doctype html>
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<meta name="description" content="Dong Huynh">
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<title>Software // Dong Huynh</title>
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<header class="header">
<h1 class="brand-main"><a href="/">Dong Huynh</a></h1>
<p class="links"><a href="https://scholar.google.co.uk/citations?user=d92eou8AAAAJ&hl=en">Publications</a></p>
<p class="links"><a href="/software.html">Software</a></p>
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<h1 class="content-subhead">Software</h1>
<h2>PROV Python package</h2>
<p>The <a href="https://pypi.python.org/pypi/prov">PROV package</a> is a Python library for the <a href="https://www.w3.org/TR/prov-dm/">PROV Data Model (PROV-DM)</a>, <em>the</em> standard for exchanging provenance data on the Web recommended by the World Wide Web Consortium. I started developing this library since my participation in the <a href="https://www.w3.org/2011/prov/">Provenance Working Group</a> at W3C (2012) to support recording provenance in various Python applications. As far as I am aware, it is still the only PROV library in Python available. See a <a href="https://trungdong.github.io/prov-python-short-tutorial.html">short tutorial</a> to have an overview of the library.</p>
<h2>Web Applications</h2>
<p>I have been involved in the development of various web applications built on the <a href="https://www.djangoproject.com/">Django platform</a>. Below are the ones that I led.</p>
<h3>ProvStore</h3>
<p><a href="https://openprovenance.org/store/">ProvStore</a> is the first online public
provenance repository supporting W3C's PROV standards. It allows users and
applications to store and publish the provenance of their data on the Web.
Provenance documents can be transformed, visualized, and shared in various file
formats, with all the functionality also available via a RESTful API</p>
<p><a href="https://openprovenance.org/store/"><img alt="ProvStore Screenshot" src="https://trungdong.github.io/images/provstore-screenshot.png"></a></p>
<ul>
<li>Paper: <a href="https://eprints.soton.ac.uk/365509/">ProvStore: A Public Provenance Repository</a></li>
</ul>
<h3>PICASO</h3>
<p>PICASO is an online platform that crowdsources the links between related
scientific work and any other relevant entities and events such as the
dataset(s) it used, the poster or slides presenting it, the project that funded
its authors, and even the presentation activity of the work in a conference
session. PICASO encourages linking to objects residing in their own silos, such
as linking a presentation on SlideShare to the digital object identifier (DOI)
of the original paper. By so doing, PICASO provides the tool for researchers to
publicly document the origins and derivatives of their work, or its provenance.</p>
<p><img alt="PICASO Screenshot" src="https://trungdong.github.io/images/picaso-screenshot.png"></p>
<h3>CollabMap</h3>
<iframe class="embed" style="--embed-ratio: 4 / 3" title="CollabMap demonstration video" src="https://player.vimeo.com/video/22624839?color=ffffff&title=0&byline=0&portrait=0" width="640" height="480" allowfullscreen></iframe>
<ul>
<li>Paper: <a href="https://eprints.soton.ac.uk/350677/">Collabmap: Crowdsourcing Maps for Emergency Planning</a></li>
</ul>
<h2>Demonstrations</h2>
<h3>HAC-ER</h3>
<iframe class="embed" title="HAC-ER demonstration video" src="https://player.vimeo.com/video/119525848?color=ffffff&title=0&byline=0&portrait=0" width="640" height="360" allowfullscreen></iframe>
<ul>
<li>Paper: <a href="https://eprints.soton.ac.uk/374070/">HAC-ER: A disaster response system based on Human-Agent Collectives</a></li>
</ul>
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