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slides/talks/2017-5-Tour-Mimir/index.html
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<section>
<h2>The database is in the way</h2>
<h3 class="fragment">Why?</h3>
</section>
<section>
@ -395,266 +396,350 @@
</section>
<section>
<h3>On representing incomplete information in a relational data base</h3>
<h4>T. Imielinski &amp; W. Lipski Jr.<span style="margin-left: 40px">(<i>VLDB <span class="fragment highlight-current-red" data-fragment-index="1">1981</span></i>)</span></h4>
<p class="fragment" data-fragment-index="1" style="margin-top: 60px">
Incomplete and Probabilistic Databases<br/>have existed since the 1980s
</p>
<section>
<h3>On representing incomplete information in a relational data base</h3>
<h4>T. Imielinski &amp; W. Lipski Jr.<span style="margin-left: 40px">(<i>VLDB <span class="fragment highlight-current-red" data-fragment-index="1">1981</span></i>)</span></h4>
<p class="fragment" data-fragment-index="1" style="margin-top: 60px">
Incomplete and Probabilistic Databases<br/>have existed since the 1980s
</p>
</section>
<section>
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<text x="60" y="50">Q(D)</text>
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<text x="60" y="170">Q(D)</text>
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<text x="120" y="230">Probab.</text>
<text x="120" y="280">Cert. A.</text>
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<p class="fragment" data-fragment-index="6" style="font-size: smaller">
We've gotten good at query processing on uncertain data.<br/>
<span class="fragment" data-fragment-index="7">But not at "sourcing" uncertain data
<span class="fragment" data-fragment-index="8">... or communicating results.</span></span>
</p>
</section>
<section>
<h3>Challenges</h3>
<ul>
<li>Where do Probabilities/Possible Worlds Come From?</li>
<li>How do I use the output of a probablistic DB query?</li>
<li>Probablistic DB queries are sloooooow.</li>
</ul>
<p class="fragment" style="font-size: smaller;">A small shift in how we think about PDBs addresses all three points.</p>
</section>
</section>
<section>
<svg width="800" height="500">
<g transform="translate(150,0)">
<section>
<h3>It's not the data that's uncertain,<br/>it's the interpretation</h3>
</section>
<section>
<table>
<tr>
<th>Time</th><th>Sensor Reading</th><th class="fragment" data-fragment-index="2">Temp Around Sensor</th>
</tr>
<tr><td>1</td><td>31.6</td><td class="fragment" data-fragment-index="2">Roughly 31.6˚C</td></tr>
<tr><td>2</td><td>-999</td><td class="fragment" data-fragment-index="2">Around 30˚C?</td></tr>
<tr><td>4</td><td>28.1</td><td class="fragment" data-fragment-index="2">Roughly 28.1˚C?</td></tr>
<tr><td>3</td><td>32.2</td><td class="fragment" data-fragment-index="2">Roughly 32.2˚C</td></tr>
</table>
<p class="fragment" data-fragment-index="1">The <i>reading</i> is deterministic</p>
<p class="fragment" data-fragment-index="2">... but what we care about is what the reading measures</p>
</section>
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<text x="150" y="70" >Q<tspan style="font-size: smaller">1</tspan>(D)</text>
<text x="150" y="190">Q<tspan style="font-size: smaller">2</tspan>(D)</text>
<text x="150" y="310">Q<tspan style="font-size: smaller">3</tspan>(D)</text>
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<text x="60" y="170">Q(D)</text>
<text x="60" y="290">Q(D)</text>
<text x="60" y="410">Q(D)</text>
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<span class="fragment" data-fragment-index="5">But not at "sourcing" uncertain data
<span class="fragment" data-fragment-index="6">... or communicating results.</span></span>
</p>
</section>
</section>
</svg>
<p style="font-size: smaller; margin-bottom: 0px; margin-top: 0px;"><b>Insight:</b> Treat data as 100% deterministic.</p>
<p
style="font-size: smaller; margin-top: 0px;"
class="fragment" data-fragment-index="2"
>Instead, queries propose alternative interpretations.</p>
</section>
<section>
<section>
<h3>It's not the data that's uncertain,<br/>it's the interpretation</h3>
</section>
<section>
<table>
<tr>
<th>Time</th><th>Sensor Reading</th><th class="fragment" data-fragment-index="2">Temp Around Sensor</th>
</tr>
<tr><td>1</td><td>31.6</td><td class="fragment" data-fragment-index="2">Roughly 31.6˚C</td></tr>
<tr><td>2</td><td>-999</td><td class="fragment" data-fragment-index="2">Around 30˚C?</td></tr>
<tr><td>4</td><td>28.1</td><td class="fragment" data-fragment-index="2">Roughly 28.1˚C?</td></tr>
<tr><td>3</td><td>32.2</td><td class="fragment" data-fragment-index="2">Roughly 32.2˚C</td></tr>
</table>
<p class="fragment" data-fragment-index="1">The <i>reading</i> is deterministic</p>
<p class="fragment" data-fragment-index="2">... but what we care about is what the reading measures</p>
</section>
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<p class="fragment" style="font-size: smaller;"><b>Insight 1:</b> Treat data as 100% deterministic. <br/>Instead, queries propose alternative interpretations.</p>
<section>
<h3>Effects</h3>
<ol>
<li class="fragment" style="margin-top: 30px;">It's clear where uncertainty comes from.</li>
<li class="fragment" style="margin-top: 30px;">Results can be communicated through provenance.</li>
<li class="fragment" style="margin-top: 30px;">Query evaluation is decoupled from physical layout.</li>
</ol>
</section>
</section>
<section>
<section>
<h3>Non-Deterministic Queries</h3>
</section>
<section>
<p></p>
</section>
</section>
<section>
<section>
<h3>Uncertainty as Provenance</h3>
<p>
Introduce Best-Guess queries and the idea of explanations. Key points:
<ul>
<li>Best-guess queries</li>
<li>Generating explanations</li>
<li>Ranking explanations</li>
</ul>
</p>
</section>
<section>
<img src="graphics/mimir_logo_final.png">
<h2>Demo</h2>
</section>
</section>
<section>
<section>
<h3>Virtualized Uncertainty</h3>
<p>
Optimizing sampling-based query evaluation
</p>
</section>
</section>
<section>
<section>
<h3>Schema-Level Uncertainty</h3>
</section>
</section>
</div></div>