1157 lines
44 KiB
HTML
1157 lines
44 KiB
HTML
<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<title>Embracing Uncertainty</title>
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<meta name="description" content="Mimir">
|
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<meta name="author" content="Oliver Kennedy">
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<meta name="apple-mobile-web-app-capable" content="yes" />
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<meta name="apple-mobile-web-app-status-bar-style" content="black-translucent" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, minimal-ui">
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<link rel="stylesheet" href="../reveal.js-3.1.0/css/reveal.css">
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<link rel="stylesheet" href="ubodin.css" id="theme">
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<!-- Code syntax highlighting -->
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<link rel="stylesheet" href="../reveal.js-3.1.0/lib/css/zenburn.css">
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<!-- Printing and PDF exports -->
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<script>
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var link = document.createElement( 'link' );
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link.rel = 'stylesheet';
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link.type = 'text/css';
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link.href = window.location.search.match( /print-pdf/gi ) ? '../reveal.js-3.1.0/css/print/pdf.css' : '../reveal.js-3.1.0/css/print/paper.css';
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document.getElementsByTagName( 'head' )[0].appendChild( link );
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</script>
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<!--[if lt IE 9]>
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<script src="../reveal.js-3.1.0/lib/js/html5shiv.js"></script>
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<![endif]-->
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</head>
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<body>
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<div class="reveal">
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<!-- Any section element inside of this container is displayed as a slide -->
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<div class="header">
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<!-- Any Talk-Specific Header Content Goes Here -->
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Embracing Uncertainty
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</div>
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<div class="footer">
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<!-- Any Talk-Specific Footer Content Goes Here -->
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<div style="float: left; margin-top: 15px; ">
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Exploring <u><b>O</b></u>nline <u><b>D</b></u>ata <u><b>In</b></u>teractions
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</div>
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<img src="graphics/FullText-white.png" height="40" style="float: right;"/>
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</div>
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<div class="slides">
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<section>
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<h4>Embracing uncertainty with</h4>
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<img src="graphics/mimir_logo_final.png">
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</section>
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<section>
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<h4>Joint work with:</h4>
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<p style="text-align:left;"><small>
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<b>PhD Students</b>: Ying Yang, Will Spoth, Aaron Huber, Poonam Kumari, Jon Logan<br/>
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<b>BS Students</b>: Lisa Lu, Jacob P. Verghese<br/>
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<b>Alums</b>: Arindam Nandi, Niccoló Meneghetti (HPE/Vertica), Vinayak Karuppasamy (Bloomberg)<br/>
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<b>Collabs</b>: Ronny Fehling (Airbus), Zhen-Hua Liu (Oracle), Dieter Gawlick (Oracle), Beda Hammerschmidt (Oracle),
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Boris Glavic (IIT), Wolfgang Gatterbauer (CMU), Juliana Freire (NYU), Heiko Mueller (NYU), Moises Sudit (UB-ISE)
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</small></p>
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</section>
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<section>
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<section>
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<h3>A Big Data Fairy Tale</h3>
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</section>
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<section>
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<img src="graphics/dagobert83-female-user-icon-800px.png" height="300" />
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<h4>Meet Alice</h4>
|
||
|
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<attribution>(OpenClipArt.org)</attribution>
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</section>
|
||
|
||
<section>
|
||
<img src="graphics/dagobert83-female-user-icon-800px.png" height="300" />
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||
<img src="graphics/littlestorefront-800px.png" height="300" />
|
||
<h4>Alice has a Store</h4>
|
||
|
||
<attribution>(OpenClipArt.org)</attribution>
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||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/littlestorefront-800px.png" height="300" style=" vertical-align: middle;"/>
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||
<span style="font-size: 3em; vertical-align: middle;">→</span>
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||
<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;" />
|
||
<h4>Alice's store collects sales data</h4>
|
||
|
||
<attribution>(OpenClipArt.org)</attribution>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/dagobert83-female-user-icon-800px.png" height="300" style=" vertical-align: middle;"/>
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<span style="font-size: 3em; vertical-align: middle;">+</span>
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||
<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;" />
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||
<span style="font-size: 3em; vertical-align: middle;">=</span>
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<img src="graphics/saco-800px.png" height="300" style=" vertical-align: middle;" />
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<h4>Alice wants to use her sales data to run a promotion</h4>
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<attribution>(OpenClipArt.org)</attribution>
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</section>
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||
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<section>
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||
<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;"/>
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||
<span style="font-size: 3em; vertical-align: middle;">→</span>
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||
<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
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||
<h4>So Alice loads up her sales data in her trusty database/hadoop/spark/etc... server.</h4>
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||
|
||
<attribution>(OpenClipArt.org)</attribution>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
|
||
<span style="font-size: 3em; vertical-align: middle;">+ ?</span>
|
||
<h4>... asks her question ...</h4>
|
||
|
||
<attribution>(OpenClipArt.org)</attribution>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
|
||
<span style="font-size: 3em; vertical-align: middle;">+ ? →</span>
|
||
<img src="graphics/crystalball-800px.png" height="300" style=" vertical-align: middle;" />
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||
<h4>... and basks in the limitless possibilities of big data.</h4>
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||
|
||
<attribution>(OpenClipArt.org)</attribution>
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||
</section>
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||
</section>
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||
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<section>
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||
<section>
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||
<h2>Why is this a fairy tale?</h2>
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||
</section>
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||
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||
<section>
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||
<img src="graphics/matt-icons_text-x-log-300px.png" height="300" style=" vertical-align: middle;"/>
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||
<span style="font-size: 3em; vertical-align: middle;">→</span>
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||
<img src="graphics/database-server-800px.png" height="300" style=" vertical-align: middle;" />
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||
<h4>It's never this easy...</h4>
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||
</section>
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||
</section>
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||
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<section>
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||
<section>
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||
<h2>CSV Import</h2>
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||
<h4>Run a <code>SELECT</code> on a raw CSV File</h4>
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||
<ul class="fragment">
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||
<li>File may not have column headers</li>
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||
<li>CSV does not provide "types"</li>
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||
<li>Lines may be missing fields</li>
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||
<li>Fields may be mistyped (typo, missing comma)</li>
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||
<li>Comment text can be inlined into the file</li>
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||
</ul>
|
||
<p class="fragment">
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||
<b>State of the art</b>: External Table Defn <span class="fragment">+ "Manually" edit CSV</span>
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||
</p>
|
||
</section>
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||
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<section>
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||
<h2>Merge Two Datasets</h2>
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||
<h4><code>UNION</code> two data sources</h4>
|
||
<ul class="fragment">
|
||
<li>Schema matching</li>
|
||
<li>Deduplication</li>
|
||
<li>Format alignment (GIS coordinates, $ vs €)
|
||
<li>Precision alignment (State vs County)</li>
|
||
</ul>
|
||
<p class="fragment">
|
||
<b>State of the art</b>: Manually map schema
|
||
</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>JSON Shredding</h2>
|
||
<h4>Run a <code>SELECT</code> on JSON or a Doc Store</h4>
|
||
<ul class="fragment">
|
||
<li>Separating fields and record sets:<br/>(e.g., <code>{ A: "Bob", B: "Alice" }</code>)</li>
|
||
<li>Missing fields (Records with no 'address')</li>
|
||
<li>Type alignment (Records with 'address' as an array)</li>
|
||
<li>Schema matching$^2$</li>
|
||
</ul>
|
||
<p class="fragment">
|
||
<b>State of the art</b>: DataGuide, Wrangler, etc...
|
||
</p>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Data Cleaning is Hard!</h2>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>State of the Art</h3>
|
||
|
||
<img src="graphics/BI-Analyst.jpg" height="400" />
|
||
<attribution>(skilledup.com)</attribution>
|
||
|
||
<p>Alice spends weeks cleaning her data before using it.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Newer State of the Art</h3>
|
||
<img src="graphics/iu.jpeg" height=500 />
|
||
<attribution>(azure.microsoft.com)</attribution>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/data-lake-to-data-swamp.jpg" height=500 />
|
||
<attribution>(timoelliott.com)</attribution>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
|
||
<section>
|
||
<h2>Curation is hard!</h2>
|
||
<ul>
|
||
<li class="fragment">Structured models (RelDBs) force curation during loading.
|
||
<ul><li class="fragment"><b>Problem:</b> All curation costs are upfront.</li></ul>
|
||
</li>
|
||
<li class="fragment">Unstructured models (NoSQL) force curation into queries.
|
||
<ul><li class="fragment"><b>Problem:</b> Complexity/redundancy blowup in queries.</li></ul>
|
||
</li>
|
||
</ul>
|
||
<p class="fragment" style="margin-top: 50px;">Make structure, curation effort <b>On-Demand</b></p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Let the database make guesses!</h3>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>
|
||
In the name of Codd,<br/><span class="fragment grow highlight-current-blue">thou shalt not give the user a wrong answer.</span>
|
||
</h3>
|
||
|
||
<h4 class="fragment">
|
||
... but what if we did?
|
||
</h4>
|
||
<h4 class="fragment">
|
||
What would it take for that to be ok?
|
||
</h4>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Industry says...</h2>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/maybe-screen.png" height="500px" />
|
||
|
||
<img src="graphics/maybe-detail.png" height="500px" class="fragment" /><br/>
|
||
<p class="fragment">My phone is guessing, but is letting me know that it did</p>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/Calendar_Base.png" height="500px" />
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/Calendar_Explain.png" height="500px" />
|
||
<p>Easy interactions to <i>accept</i>, <i>reject</i>, or <i>explain</i> uncertainty</p>
|
||
</section>
|
||
|
||
<section>
|
||
<img src="graphics/BingTranslate.png" height="400px" />
|
||
<p>Easy access to: Provenance, Alternatives, and Confidence</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Communication</h2>
|
||
<ul>
|
||
<li>Why is my data uncertain?</li>
|
||
<li>How bad is it?</li>
|
||
<li>What can I do about it?</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>What if a database did the same?</h2>
|
||
</section>
|
||
|
||
<section>
|
||
<ul style="width:35%; font-size: 24pt; margin-top: 50px; margin-bottom: 100px; margin-right: 10px">
|
||
<li class="fragment"><b>A:</b> Standard SQL.</li>
|
||
<li class="fragment"><b>B:</b> Annotated Output.</li>
|
||
<li class="fragment"><b>C:</b> Subway Diagram.</li>
|
||
<li class="fragment"><b>D:</b> Result Explanations.</li>
|
||
</ul>
|
||
<a href="http://localhost:9000">
|
||
<img src="graphics/UIExample.png" style="width:60%; float:right"/>
|
||
</a>
|
||
<b><a href="http://localhost:9000" class="fragment">Demo</a></b>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Mimir</h2>
|
||
<ul>
|
||
<li><b>Lenses</b>: Generic, best-guess data curation operators.</li>
|
||
|
||
<li><b>Explanations</b>: How certain <b>is</b> my data?</li>
|
||
|
||
<li><b>Provenance</b>: What issues still need to be fixed?</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h3>Lenses</h3>
|
||
<p class="fragment">Here's a problem with my data. <span class="fragment">Fix it.</span></p>
|
||
<ul>
|
||
<li class="fragment">What type is this column? (majority vote)</li>
|
||
<li class="fragment">How do the columns of these relations line up? (pick your favorite schema matching paper)</li>
|
||
<li class="fragment">How do I query heterogeneous JSON objects? (see above)</li>
|
||
<li class="fragment">What should these missing values be? (learning-based interpolation)</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<svg width=500 height=350>
|
||
<g transform="scale(1.2)">
|
||
<text x="0" y="45">View:</text>
|
||
<image xlink:href="graphics/db.svg" x="130" y="10" height="50px" width="50px"/>
|
||
<text x="225" y="20" style="font-family: courier; font-size: 60%">SELECT</text>
|
||
<polygon
|
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points="190,35 340,35 325,30 325,40 340,35"
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style="
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stroke: black;
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stroke-width: 2;
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"
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/>
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<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="350" y="10" height="50px" width="50px"/>
|
||
</g>
|
||
|
||
<g transform="translate(0,150) scale(1.2)" class="fragment">
|
||
<text x="0" y="45">Lens:</text>
|
||
<image xlink:href="graphics/db.svg" x="130" y="10" height="50px" width="50px"/>
|
||
<text x="225" y="20" style="font-family: courier; font-size: 60%">SELECT</text>
|
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<polygon
|
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points="190,35 340,35 325,30 325,40 340,35"
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style="
|
||
stroke: black;
|
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fill: black;
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||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="350" y="10" height="50px" width="50px"/>
|
||
<g class="fragment">
|
||
<text x="212" y="20" style="font-family: courier; font-size: 60%">[ ]</text>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="355" y="15" height="50px" width="50px"/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="360" y="20" height="50px" width="50px"/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="365" y="25" height="50px" width="50px"/>
|
||
<g class="fragment">
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<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="350" y="110" height="60px" width="60px"/>
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<polygon
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points="380,80 380,105 385,90 375,90 380,105"
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style="
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stroke: black;
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fill: black;
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||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<text x="220" y="142" style="font-size: 60%">(best guess)</text>
|
||
</g>
|
||
</g>
|
||
</g>
|
||
|
||
|
||
</svg>
|
||
<p class="fragment">Lenses introduce <i>uncertainty</i></p>
|
||
<attribution>(OpenClipArt.org)</attribution>
|
||
</section>
|
||
<section>
|
||
<h2>The User's View</h2>
|
||
<pre><code>
|
||
SELECT NAME, DEPARTMENT FROM PRODUCTS;
|
||
</code></pre>
|
||
<table class="fragment" data-fragment-index="1">
|
||
<tr><th>Name</th><th>Department</th></tr>
|
||
<tr><td>Apple 6s, White</td><td>Phone</td></tr>
|
||
<tr><td>Dell, Intel 4 core</td><td>Computer</td></tr>
|
||
<tr><td>HP, AMD 2 core</td><td class="fragment highlight-red" data-fragment-index="2">Computer</td></tr>
|
||
<tr><td>...</td><td>...</td></tr>
|
||
</table>
|
||
<p class="fragment" data-fragment-index="2"><b>Simple UI:</b> Highlight values that are based on guesses.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<pre><code>
|
||
SELECT NAME, DEPARTMENT FROM PRODUCTS;
|
||
</code></pre>
|
||
<small>
|
||
<table>
|
||
<tr><th>Name</th><th>Department</th></tr>
|
||
<tr><td>Apple 6s, White</td><td>Phone</td></tr>
|
||
<tr><td>Dell, Intel 4 core</td><td>Computer</td></tr>
|
||
<tr><td>HP, AMD 2 core</td><td style="color: red;">Computer</td></tr>
|
||
<tr><td>...</td><td>...</td></tr>
|
||
</table>
|
||
</small>
|
||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xl="http://www.w3.org/1999/xlink" version="1.1" viewBox="241 277 265 125" width="265pt" height="125pt" xmlns:dc="http://purl.org/dc/elements/1.1/" class="fragment" data-fragment-index="1">
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<metadata> Produced by OmniGraffle 6.2.5 <dc:date>2015-09-20 14:45:55 +0000</dc:date></metadata>
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<title>Canvas 1</title>
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<title>Layer 1</title>
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|
||
<path d="M 279 351 L 243 369 L 279 387 L 279 389 C 279 394.52285 283.47715 399 289 399 L 494 399 C 499.52285 399 504 394.52285 504 389 L 504 289 C 504 283.47715 499.52285 279 494 279 L 289 279 C 283.47715 279 279 283.47715 279 289 Z" stroke="black" stroke-linecap="round" stroke-linejoin="round" stroke-width="1"/>
|
||
<text transform="translate(293 293)" fill="black"><tspan font-family="Helvetica Neue" font-size="16" font-weight="bold" x="0" y="16" textLength="16.896" class="fragment" data-fragment-index="2">Pr</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="bold" x="16.608" y="16" textLength="69.28" class="fragment" data-fragment-index="2">obability:</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="85.888" y="16" textLength="38.24" class="fragment" data-fragment-index="2"> 95%</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="bold" x="0" y="53" textLength="62.224" class="fragment" data-fragment-index="3">Reason:</tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="62.224" y="53" textLength="144.912" class="fragment" data-fragment-index="3"> Because I guessed </tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="0" y="71" textLength="206.592" class="fragment" data-fragment-index="3">‘Computer’ for ‘Department’ </tspan><tspan font-family="Helvetica Neue" font-size="16" font-weight="500" x="0" y="89" textLength="196.16" class="fragment" data-fragment-index="3">on Row ‘3’ of ‘PRODUCTS’</tspan></text>
|
||
</g>
|
||
</g>
|
||
</svg>
|
||
<p class="fragment" data-fragment-index="1">Allow users to <code>EXPLAIN</code> uncertain outputs</p>
|
||
<p class="fragment" data-fragment-index="3">Explanations include reasons given in English</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Explanations</h3>
|
||
<ol>
|
||
<li>Mark <i>uncertain</i> data and results.</li>
|
||
<li>Upon request, provide more detail:
|
||
<ul style="font-size:80%; width: 600px">
|
||
<li>Why is my data uncertain? <span style="float:right; font-size:80%; margin-top: 5px">(provenance)</span></li>
|
||
<li>How bad is it? <span style="float:right; font-size:80%; margin-top: 5px">(confidence, entropy, bounds)</span></li>
|
||
<li>What are other possibile answers? <span style="float:right; font-size:80%; margin-top: 5px">(samples)</span></li>
|
||
<li>What can I do to fix it? <span style="float:right; font-size:80%; margin-top: 5px">(repairs)</span></li>
|
||
</ul></li>
|
||
</ol>
|
||
</section>
|
||
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Available Lenses</h2>
|
||
<ul>
|
||
<li>Missing Value Repair (using Wekka)</li>
|
||
<li>Schema Matching (merging datasets)</li>
|
||
<li>Type Inference (for CSV import)</li>
|
||
<li>Entity Extraction (for JSON import)</li>
|
||
<li>Functional-Dependency Repair</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Entity Extraction</h2>
|
||
<pre><code>
|
||
{
|
||
"grad":{"students":[
|
||
{name:"Alice",deg:"PhD",credits:"10"},
|
||
{name:"Bob",deg:"MS"}, ...]},
|
||
"undergrad":{"students":[
|
||
{name:"Carol"},
|
||
{name:"Dave",deg:"U"}, ...]}
|
||
}
|
||
</code></pre>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Entity Extraction</h2>
|
||
<img src="graphics/extracted_entities.png" />
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Entity Extraction Lens</h2>
|
||
<img src="graphics/synthesized_entities.png" />
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Shared Workspaces</h2>
|
||
<img src="graphics/workspaces.png" />
|
||
</section>
|
||
|
||
|
||
|
||
<section>
|
||
<h2>Other Efforts in Progress</h2>
|
||
<ul>
|
||
<li>Priority: Aggregate Queries</li>
|
||
<li>Data Descriptors (DataGuides++)</li>
|
||
<li>User-Interface Studies</li>
|
||
<li>Prioritization of HITL Tasks</li>
|
||
<li>Editable Query Results (<a href="http://vizierdb.info/">Vizier</a>)</li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
|
||
|
||
<section>
|
||
<section>
|
||
<img src="graphics/mimir_logo_final.png" height="200px">
|
||
<ul>
|
||
<li>On-Demand Data Curation makes data exploration easier.</li>
|
||
<li>"Best-Guess" results streamline analytics.
|
||
<div> ... if the DB communicates the resulting uncertainty.</div></li>
|
||
</ul>
|
||
<p class="fragment"><b>Questions?</b></p>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h1>Backup Slides</h1>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Mimir is a DB <u>Overlay</u></h2>
|
||
</section>
|
||
|
||
<section>
|
||
<svg width="500px" height="400px">
|
||
<g>
|
||
<g>
|
||
<image xlink:href="graphics/db.svg" x="10" y="5" height="50px" width="50px"/>
|
||
<text x="0" y="80" style="font-size:50%">(Any DB)</text>
|
||
</g>
|
||
<polygon
|
||
points="0,0 120,0 105,-5 105,5 120,0"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<g transform="translate(220,0)">
|
||
<image xlink:href="graphics/primary-queries.svg" x="0" y="5" height="50px" width="50px"/>
|
||
<text x="0" y="80" style="font-size:50%">(Lens)</text>
|
||
</g>
|
||
<polygon
|
||
points="0,0 100,0 85,-5 85,5 100,0"
|
||
transform="translate(290,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<g transform="translate(400,0)">
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="0" y="10" height="50px" width="50px"/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="5" y="15" height="50px" width="50px"/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="10" y="20" height="50px" width="50px"/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="15" y="25" height="50px" width="50px"/>
|
||
</g>
|
||
</g>
|
||
<g class="fragment">
|
||
<polygon
|
||
points="0,0 0,110 -5,95 5,95 0,110"
|
||
transform="translate(200,100)"
|
||
style="
|
||
stroke: red;
|
||
fill: red;
|
||
stroke-width: 4;
|
||
"
|
||
/>
|
||
<polygon
|
||
points="0,0 0,110 -5,95 5,95 0,110"
|
||
transform="translate(245,100)"
|
||
style="
|
||
stroke: red;
|
||
fill: red;
|
||
stroke-width: 4;
|
||
"
|
||
/>
|
||
<polygon
|
||
points="0,0 0,110 -5,95 5,95 0,110"
|
||
transform="translate(290,100)"
|
||
style="
|
||
stroke: red;
|
||
fill: red;
|
||
stroke-width: 4;
|
||
"
|
||
/>
|
||
<g transform="translate(0,200)">
|
||
<g>
|
||
<image xlink:href="graphics/db.svg" x="10" y="5" height="50px" width="50px"/>
|
||
<text x="0" y="80" style="font-size:50%">(Any DB)</text>
|
||
</g>
|
||
<polygon
|
||
points="0,0 120,0 105,-5 105,5 120,0"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<polygon
|
||
points="0,0 120,65 105,50 105,62 120,65"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<polygon
|
||
points="0,0 120,130 105,105 105,122 120,130"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<g transform="translate(210,0)">
|
||
<text x="0" y="45" style="font-size:50%; font-family: courier">SELECT</text>
|
||
<polygon
|
||
points="0,0 110,0 95,-5 95,5 110,0"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="200" y="15" height="50px" width="50px"/>
|
||
</g>
|
||
<g transform="translate(210,65)">
|
||
<text x="0" y="45" style="font-size:50%; font-family: courier">SELECT</text>
|
||
<polygon
|
||
points="0,0 110,0 95,-5 95,5 110,0"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="200" y="15" height="50px" width="50px"/>
|
||
</g>
|
||
<g transform="translate(210,130)">
|
||
<text x="0" y="45" style="font-size:50%; font-family: courier">SELECT</text>
|
||
<polygon
|
||
points="0,0 110,0 95,-5 95,5 110,0"
|
||
transform="translate(80,40)"
|
||
style="
|
||
stroke: black;
|
||
fill: black;
|
||
stroke-width: 2;
|
||
"
|
||
/>
|
||
<image xlink:href="graphics/jean-victor-balin-icon-table.svg" x="200" y="15" height="50px" width="50px"/>
|
||
</g>
|
||
</g>
|
||
</g>
|
||
<g transform="translate(220,230)" class="fragment">
|
||
<text x="0" y="48" style="font-family: courier; font-size:40%">UNION</text>
|
||
<text x="0" y="113" style="font-family: courier; font-size:40%">UNION</text>
|
||
</g>
|
||
</svg>
|
||
<p class="fragment">Mimir <i>virtualizes</i> uncertainty
|
||
<attribution>(OpenClipArt.org)</attribution>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>How?</h2>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Labeled Nulls</h3>
|
||
<p>$Var(\ldots)$ constructs new variables</p>
|
||
<ul>
|
||
<li class="fragment">$Var('X')$ constructs a new variable $X$</li>
|
||
<li class="fragment">$Var('X', 1)$ constructs a new variable $X_{1}$</li>
|
||
<li class="fragment">$Var('X', ROWID)$ evaluates $ROWID$ and then constructs a new variable $X_{ROWID}$</li>
|
||
</ul>
|
||
</section>
|
||
|
||
|
||
<section>
|
||
<h3>Lazy Evaluation</h3>
|
||
<p>Variables can't be evaluated until they are bound.<br/>So, we allow arbitrary expressions to represent data.</p>
|
||
<ul>
|
||
<li class="fragment">$X$ is a legitimate data value.</li>
|
||
<li class="fragment">$X+1$ is a legitimate data value.</li>
|
||
<li class="fragment">$1+1$ is a legitimate data value<span class="fragment">, but can be reduced to $2$.</span></li>
|
||
</ul>
|
||
<p class="fragment">A lazy value without variables is <b>deterministic</b></p>
|
||
</section>
|
||
|
||
<section>
|
||
<p>Mimir SQL allows the $Var()$ operator to inlined</p>
|
||
<pre><code>
|
||
SELECT A, VAR('X', B)+2 AS C FROM R;
|
||
</code></pre>
|
||
|
||
<center><div style="width: 600px" class="fragment">
|
||
<table style="float: left">
|
||
<thead>
|
||
<tr><th>A</th><th>B</th></tr>
|
||
</thead><tbody>
|
||
<tr><td>1</td><td>2</th></tr>
|
||
<tr><td>3</td><td>4</th></tr>
|
||
<tr><td>5</td><td>6</th></tr>
|
||
</tbody>
|
||
</table>
|
||
<table style="float: right" class="fragment">
|
||
<tr><th>A</th><th>C</th></tr>
|
||
<tr><td>1</td><td>$X_2+2$</th></tr>
|
||
<tr><td>3</td><td>$X_4+2$</th></tr>
|
||
<tr><td>5</td><td>$X_6+2$</th></tr>
|
||
</table>
|
||
</div></center>
|
||
<div style="clear: both;"> </div>
|
||
</section>
|
||
|
||
<section>
|
||
<p>Selects on $Var()$ need to be deferred too...</p>
|
||
<pre><code>
|
||
SELECT A FROM R WHERE VAR('X', B) > 2;
|
||
</code></pre>
|
||
|
||
<center><div style="width: 600px">
|
||
<table style="float: left">
|
||
<thead>
|
||
<tr><th>A</th><th>B</th></tr>
|
||
</thead><tbody>
|
||
<tr><td>1</td><td>2</th></tr>
|
||
<tr><td>3</td><td>4</th></tr>
|
||
<tr><td>5</td><td>6</th></tr>
|
||
</tbody>
|
||
</table>
|
||
<table style="float: right" class="fragment">
|
||
<tr><th>A</th><th>$\phi$</th></tr>
|
||
<tr><td>1</td><td>$X_2>2$</th></tr>
|
||
<tr><td>3</td><td>$X_4>2$</th></tr>
|
||
<tr><td>5</td><td>$X_6>2$</th></tr>
|
||
</table>
|
||
</div></center>
|
||
<div style="clear: both;"> </div>
|
||
<p class="fragment">When evaluating the table, rows where $\phi = \bot$ are dropped.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>C-Tables</h3>
|
||
<ul>
|
||
<li>Original Formulation <small>[Imielinski, Lipski 1981]</small></li>
|
||
<li class="fragment">PC-Tables <small>[Green, Tannen 2006]</small></li>
|
||
<li class="fragment">Systems<ul>
|
||
<li>Orchestra <small>[Green, Karvounarakis, Taylor, Biton, Ives, Tannen 2007]</small></li>
|
||
<li>MayBMS <small>[Huang, Antova, Koch, Olteanu 2009]</small></li>
|
||
<li>Pip <small>[Kennedy, Koch 2009]</small>
|
||
<li>Sprout <small>[Fink, Hogue, Olteanu, Rath 2011]</small></li>
|
||
</ul></li>
|
||
<li class="fragment">Generalized PC-Tables <small>[Kennedy, Koch 2009]</small></li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Labeled nulls capture a lens' uncertainty</h2>
|
||
</section>
|
||
|
||
<section>
|
||
<pre><code>
|
||
CREATE LENS PRODUCTS
|
||
AS SELECT * FROM PRODUCTS_RAW
|
||
USING DOMAIN_REPAIR(DEPARTMENT NOT NULL);
|
||
</code></pre>
|
||
|
||
<div class="fragment">
|
||
<p>is (almost) the same as the query...</p>
|
||
<pre><code>
|
||
CREATE VIEW PRODUCTS
|
||
AS SELECT ID, NAME, ...,
|
||
CASE WHEN DEPARTMENT IS NOT NULL THEN DEPARTMENT
|
||
ELSE VAR('PRODUCTS.DEPARTMENT', ROWID)
|
||
END AS DEPARTMENT
|
||
FROM PRODUCTS_RAW;
|
||
</code></pre>
|
||
</div>
|
||
|
||
<small class="fragment">
|
||
<table>
|
||
<tr><th>ID</th><th>Name</th><th>...</th><th>Department</th></tr>
|
||
<tr><td>123</td><td>Apple 6s, White</td><td>...</td><td>Phone</td></tr>
|
||
<tr><td>34234</td><td>Dell, Intel 4 core</td><td>...</td><td>Computer</td></tr>
|
||
<tr><td>34235</td><td>HP, AMD 2 core</td><td>...</td><td class="fragment">$Prod.Dept_3$</td></tr>
|
||
<tr><td>...</td><td>...</td><td>...</td><td>...</td></tr>
|
||
</table>
|
||
</small>
|
||
</section>
|
||
<section>
|
||
<pre><code>
|
||
CREATE LENS PRODUCTS
|
||
AS SELECT * FROM PRODUCTS_RAW
|
||
USING DOMAIN_REPAIR(DEPARTMENT NOT NULL);
|
||
</code></pre>
|
||
|
||
<div>
|
||
<p>Behind the scenes, a lens also creates a model...</p>
|
||
<pre class="fragment"><code>
|
||
SELECT * FROM PRODUCTS_RAW;
|
||
</code></pre>
|
||
</div>
|
||
<div class="fragment">
|
||
<div style="font-size: 1em; vertical-align: middle;">↓</div>
|
||
<div>
|
||
<img src="graphics/weka.png" />
|
||
</div>
|
||
</div>
|
||
<div class="fragment">
|
||
<div style="font-size: 1em; vertical-align: middle;">↓</div>
|
||
<div><p>An estimator for <small style="vertical-align: baseline;">$PRODUCTS.DEPARTMENT_{ROWID}$</small><p></div>
|
||
</div>
|
||
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h3>... but databases don't support labeled nulls</h3>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Labeled Nulls Percolate Up</h3>
|
||
<pre><code>
|
||
SELECT A, VAR('X', B)+2 AS C FROM R;
|
||
</code></pre>
|
||
<div class="fragment">
|
||
<p>Mimir dispatches this query to the DB:</p>
|
||
<pre><code>
|
||
SELECT A, B FROM R;
|
||
</code></pre>
|
||
</div>
|
||
<div class="fragment">
|
||
<p>And for each row of the result, evaluates:</p>
|
||
<pre><code>
|
||
SELECT A, VAR('X', B)+2 AS C FROM RESULT;
|
||
</code></pre>
|
||
</div>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Generating Explanations</h3>
|
||
<p>All uncertainty comes from labeled nulls in the expressions that Mimir evaluates for each row of the output.</p>
|
||
<dl>
|
||
<dt>Why is the data uncertain?</dt>
|
||
<dd>All relevant lenses referenced in <code>VAR('X', B)+2</code>.</dd>
|
||
|
||
<dt>How uncertain?</dt>
|
||
<dd>Estimate by sampling from <code>VAR('X', B)</code>.</dd>
|
||
|
||
<dt>How do I fix it?</dt>
|
||
<dd>Each lens fixes one well-defined type of error.</dd>
|
||
</dl>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Lazy evaluation can cause problems</h3>
|
||
<pre><code>
|
||
SELECT R.A, S.C FROM R, S WHERE VAR('X', R.B) = S.B;
|
||
</code></pre>
|
||
<div class="fragment">
|
||
<p>Mimir dispatches this query to the DB:</p>
|
||
<pre><code>
|
||
SELECT R.A, S.C, R.B AS TEMP_1, S.B AS TEMP_2 FROM R, S;
|
||
</code></pre>
|
||
</div>
|
||
<div class="fragment">
|
||
<p>And for each row of the result, evaluates:</p>
|
||
<pre><code>
|
||
SELECT A, C FROM RESULT WHERE VAR('X', TEMP_1) = TEMP_2;
|
||
</code></pre>
|
||
</div>
|
||
</section>
|
||
|
||
<section>
|
||
<p>UDFs allow the DB to interpret labeled nulls</h3>
|
||
<pre><code>
|
||
SELECT R.A, S.C FROM R, S
|
||
WHERE S.B = MIMIR_VG_BESTGUESS('VARIABLE_X', R.B);
|
||
</code></pre>
|
||
<p class="fragment">... but we lose the ability to <i>explain</i> outputs</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Provenance Recovers Explanations</h3>
|
||
<pre><code>
|
||
SELECT R.A, S.C FROM R, S WHERE VAR('X', R.B) = S.B;
|
||
</code></pre>
|
||
<p>Mimir dispatches this query to the DB:</p>
|
||
<pre><code>
|
||
SELECT R.A, S.C,
|
||
R.ROWID AS ID_1, S.ROWID AS ID_2
|
||
WHERE S.B = MIMIR_VG_BESTGUESS('VARIABLE_X', R.B);
|
||
</code></pre>
|
||
<div class="fragment">
|
||
<p>Then to explain, Mimir dispatches the query:</p>
|
||
<pre><code>
|
||
SELECT R.A, S.C, R.B AS TEMP_1, S.B AS TEMP_2
|
||
WHERE R.ROWID = ID_1 AND S.ROWID = ID_2
|
||
</code></pre>
|
||
</div>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h3>Performance</h3>
|
||
<p>PDBench: TPC-H Data, but add random FK violations.</p>
|
||
<ul>
|
||
<li><b>Query 1:</b> ~TPC-H Q3; 3-way FK Join with Predicates</li>
|
||
<li><b>Query 2:</b> ~TPC-H Q6; Table Scan with Predicates.</li>
|
||
<li><b>Query 3:</b> ~TPC-H Q7; 5-way Star Join with Predicates.</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<dl>
|
||
<dt>Partition:</dt>
|
||
<dd>Separate query fragments compute 'certain' results and one or more classes of uncertain results.</dd>
|
||
<dt>TupleBundle:</dt>
|
||
<dd>Compute and summarize 10 sampled results in parallel</dd>
|
||
<dt>Inline:</dt>
|
||
<dd>UDFs dynamically inject best guess values into the query.</dd>
|
||
</dl>
|
||
</section>
|
||
|
||
<section>
|
||
<table>
|
||
<tr><th>Strategy</th><th>Q1</th><th>Q2</th><th>Q3</th></tr>
|
||
<tr><td>Inline</td><td>85.5s</td><td>676.6s</td><td>103.3s</td></tr>
|
||
<tr><td>TupleBundle</td><td>8.2s</td><td>55.2s</td><td>9.8s</td></tr>
|
||
<tr><td>Partition</td><td>>1hr</td><td>739.7s</td><td>>1hr</td></tr>
|
||
</table>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h3>Presentation</h3>
|
||
<p>Participants were shown a table of 3 products with 3 ratings (e.g., Amazon, Best Buy, Walmart) each</p>
|
||
<p><b>Part 1</b>: The randomly generated ratings were biased to encourage a predictable, but mildly ambiguous ordering of the three products.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<p><b>Part 2</b>: We used the same randomization, but this time we marked several of the values as uncertain:
|
||
<table>
|
||
<tr><td>Red Text</td><td><span style="color: red">value</span></td></tr>
|
||
<tr><td>Red Background</td><td><span style="background-color: red">value</span></td></tr>
|
||
<tr><td>Asterisk</td><td>$value*$</td></tr>
|
||
<tr><td>Tolerance</td><td>$value \pm tolerance$</td></tr>
|
||
<tr><td>Range</td><td>$low – high$</td></tr>
|
||
</table>
|
||
</p>
|
||
</section>
|
||
|
||
|
||
<section>
|
||
<h3>Probability of Agreement With Elicited Order</h3>
|
||
<img src="graphics/interfaces.png" />
|
||
</section>
|
||
|
||
<section>
|
||
<p><b>Part 3</b>: We asked participants to verbalize their thought process and tagged specific exclamations in the transcripts.</p>
|
||
<img src="graphics/contextvsUncertainty.png" height="350px" />
|
||
<small>
|
||
<code>CONTEXT-DOMAIN</code>: The participant relied on the 0-5 range of reviews to infer an uncertain rating<br/>
|
||
<code>CONTEXT-ROW</code>: The participant used other reviews for the same product to infer an uncertain rating<br/>
|
||
<code>UNCERTAINTY-IGNORED</code>: The participant explicitly disregarded an uncertain rating<br/>
|
||
<code>UNCERTAINTY-IRRELEVANT</code>: The participant didn't need the uncertain value.<br/>
|
||
</small>
|
||
</section>
|
||
|
||
<section>
|
||
<p><b>Part 3</b>: We asked participants to verbalize their thought process and tagged specific exclamations in the transcripts.</p>
|
||
<img src="graphics/ComfortvsDiscomfort.png" height="350px" />
|
||
<small>
|
||
<code>[DIS]COMFORT-*</code>: The participant expressed a positive or negative emotional response.<br/>
|
||
<code>*-DATA</code>: The emotional response pertained to the data itself.<br/>
|
||
<code>*-UNCERTAINTY</code>: The emotional response pertained to the uncertain values or representation.<br/>
|
||
</small>
|
||
</section>
|
||
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h2>Selection (Filtering)</h2>
|
||
<pre><code>
|
||
SELECT NAME FROM PRODUCTS
|
||
WHERE DEPARTMENT='PHONE'
|
||
AND ( VENDOR='APPLE'
|
||
OR PLATFORM='ANDROID' )
|
||
</code></pre>
|
||
<p class="fragment">Row-level uncertainty is a boolean formula $\phi$.</p>
|
||
<p class="fragment">
|
||
For this query, $\phi$ can be as complex as:
|
||
<small>$$DEPT_{ROWID}='P\ldots' \wedge \left( VEND_{ROWID}='Ap\ldots' \vee PLAT_{ROWID} = 'An\ldots' \right)$$</small></p>
|
||
<p class="fragment"><b>Too many variables! Which is the most important?</b></p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>What is important?</h2>
|
||
<p class="fragment">Data Cleaning</p>
|
||
<h2 class="fragment">Which variables are important?</h2>
|
||
<p class="fragment">The ones that keep us from knowing everything</p>
|
||
</section>
|
||
|
||
<section>
|
||
<p><small>$$D_{ROWID}='P' \wedge \left( V_{ROWID}='Ap' \vee PLAT_{ROWID} = 'An' \right)$$</small></p>
|
||
<div style="font-size: 2em">⬍</div>
|
||
<p>$$A \wedge (B \vee C)$$</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Naive Approach</h3>
|
||
|
||
<p>Consider a game between a database and an impartial oracle.</p>
|
||
<ul>
|
||
<li>The DB picks a variable $v$ in $\phi$ and pays a cost $c_v$.</li>
|
||
<li>The Oracle reveals the truth value of $v$.</li>
|
||
<li>The DB updates $\phi$ accordingly and repeats until $\phi$ is deterministic.</li>
|
||
</ul>
|
||
<p class="fragment"><b>Naive Algorithm: </b> Pick all variables!</p>
|
||
<p class="fragment"><b>Less Naive Algorithm: </b> Minimize $E\left[\sum c_v\right]$.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h2>Exponential Time Bad!</h2>
|
||
</section>
|
||
</section>
|
||
|
||
<section>
|
||
<section>
|
||
<h3>The Value of What We Don't Know</h3>
|
||
<p>$$\phi = A \wedge (B \vee C)$$</p>
|
||
<ol>
|
||
<li class="fragment" data-fragment-index="1">Generate Samples for $A$, $B$, $C$</li>
|
||
<li class="fragment" data-fragment-index="2">Estimate $p(\phi)$</li>
|
||
<li class="fragment" data-fragment-index="3">Compute $H[\phi] = -\log\left(p(\phi) \cdot (1-p(\phi))\right)$</li>
|
||
</ol>
|
||
<p class="fragment" data-fragment-index="4"><b>Entropy is intuitive: </b><br/> $H = 1$ means we know nothing, <br/>$H = 0$ means we know everything.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Information Gain</h3>
|
||
<p>$$\mathcal I_{A \leftarrow \top} (\phi) = H\left[\phi\right] - H\left[\phi(A \leftarrow \top)\right]$$</p>
|
||
<p><b>Information gain of</b> $v$: The reduction in entropy from knowing the truth value of a variable $v$.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Expected Information Gain</h3>
|
||
<p>$$\mathcal I_{A} (\phi) = \left(p(A)\cdot \mathcal I_{A\leftarrow \top}(\phi)\right) + \left(p(\neg A)\cdot \mathcal I_{A\leftarrow \bot}(\phi)\right)$$</p>
|
||
<p><b>Expected information gain of</b> $v$: The probability-weighted average of the information gain for $v$ and $\neg v$.</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>The Cost of Perfect Information</h3>
|
||
<p>Combine Information Gain and Cost</p>
|
||
<p>$$f(\mathcal I_{A}(\phi), c_A)$$</p>
|
||
<p class="fragment"><b>For example: </b>$EG2(\mathcal I_{A}(\phi), c_A) = \frac{2^{\mathcal I_{A}(\phi)} - 1}{c_A}$</p>
|
||
<p class="fragment"><b>Greedy Algorithm: </b> Minimize $f(\mathcal I_{A}(\phi), c_A)$ at each step</p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Experimental Data</h3>
|
||
|
||
<ul>
|
||
<li>Start with a large dataset.</li>
|
||
<li>Delete random fields (~50%).</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Experimental Queries</h3>
|
||
|
||
<p>Simulate an analyst trying to manually explore correlations.</p>
|
||
<ul>
|
||
<li>Train a tree-classifier on the base data.</li>
|
||
<li>Convert the decision tree to a query for all rows where the tree predicts a specific value.</li>
|
||
</ul>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Cost vs Entropy: Credit Data</h3>
|
||
<img src="graphics/credit_entropy.png" height=400 />
|
||
<p><small>
|
||
<b>EG2:</b> Greedy Cost/Value Ordering<br/>
|
||
<b>NMETC:</b> Naive Minimal Expected Total Cost<br/>
|
||
<b>Random:</b> Completely Random Order
|
||
</small></p>
|
||
</section>
|
||
|
||
<section>
|
||
<h3>Cost vs Entropy: Product Data</h3>
|
||
<img src="graphics/product_entropy.png" height=400 />
|
||
<p><small>
|
||
<b>EG2:</b> Greedy Cost/Value Ordering<br/>
|
||
<b>NMETC:</b> Naive Minimal Expected Total Cost<br/>
|
||
<b>Random:</b> Completely Random Order
|
||
</small></p>
|
||
</section>
|
||
|
||
</section>
|
||
|
||
</div></div>
|
||
|
||
<script src="../reveal.js-3.1.0/lib/js/head.min.js"></script>
|
||
<script src="../reveal.js-3.1.0/js/reveal.js"></script>
|
||
|
||
<script>
|
||
|
||
// Full list of configuration options available at:
|
||
// https://github.com/hakimel/../reveal.js#configuration
|
||
Reveal.initialize({
|
||
controls: false,
|
||
progress: true,
|
||
history: true,
|
||
center: true,
|
||
slideNumber: true,
|
||
|
||
transition: 'fade', // none/fade/slide/convex/concave/zoom
|
||
|
||
// Optional ../reveal.js plugins
|
||
dependencies: [
|
||
{ src: '../reveal.js-3.1.0/lib/js/classList.js', condition: function() { return !document.body.classList; } },
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{ src: '../reveal.js-3.1.0/plugin/math/math.js',
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{ src: '../reveal.js-3.1.0/plugin/markdown/marked.js', condition: function() { return !!document.querySelector( '[data-markdown]' ); } },
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{ src: '../reveal.js-3.1.0/plugin/notes/notes.js', async: true }
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]
|
||
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|
||
|
||
</script>
|
||
|
||
</body>
|
||
</html>
|