2017-09-05 09:53:04 -04:00
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< title > Embracing Uncertainty< / title >
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< meta name = "author" content = "Oliver Kennedy" >
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Embracing Uncertainty
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2017-09-05 10:05:40 -04:00
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2017-09-05 09:53:04 -04:00
Exploring < u > < b > O< / b > < / u > nline < u > < b > D< / b > < / u > ata < u > < b > In< / b > < / u > teractions
< / div >
< img src = "graphics/FullText-white.png" height = "40" style = "float: right;" / >
< / div >
< div class = "slides" >
< section >
< h4 > Embracing uncertainty with< / h4 >
< img src = "graphics/mimir_logo_final.png" / >
< / section >
< section >
2017-09-05 10:05:40 -04:00
< dl >
< dt > Student Collaborators (PhD/MS/BS)< / dt >
< dd >
Poonam Kumari, William Spoth, Aaron Huber, < br / >
Lisa Lu, Olivia Alphonce, Shivang Aggarwal
< / dd >
< dt > Alumni< / dt >
< dd >
Niccolo Meneghetti, Arindam Nandi < span style = "font-size: 14pt;" > (both HPE/Vertica)< / span > ,< br / >
Vinayak Karuppasamy < span style = "font-size: 14pt;" > (Bloomberg)< / span > , Ying Yang < span style = "font-size: 14pt;" > (Oracle)< / span >
< / dd >
< dt > Other Collaborators< / dt >
< dd >
Mike Brachmann (UB), Ronny Fehling (Airbus), < br / >
Zhen-Hua Liu (Oracle), Dieter Gawlick (Oracle), < br / >
Boris Glavic (IIT), Juliana Freire (NYU)
< / dd >
< / dl >
2017-09-05 09:53:04 -04:00
< / p > < p >
< / p > < p >
< / p >
< / section >
< section >
< section >
< h3 > A Big Data Fairy Tale< / h3 >
< / section >
< section >
< img src = "graphics/dagobert83-female-user-icon-800px.png" height = "300" / >
< h4 > Meet Alice< / h4 >
< attribution > (OpenClipArt.org)< / attribution >
< / section >
< section >
< img src = "graphics/dagobert83-female-user-icon-800px.png" height = "300" / >
< img src = "graphics/littlestorefront-800px.png" height = "300" / >
< h4 > Alice has a Store< / h4 >
< attribution > (OpenClipArt.org)< / attribution >
< / section >
< section >
< img src = "graphics/littlestorefront-800px.png" height = "300" style = " vertical-align: middle;" / >
< span style = "font-size: 3em; vertical-align: middle;" > →< / span >
< 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;" / >
< span style = "font-size: 3em; vertical-align: middle;" > +< / span >
< img src = "graphics/matt-icons_text-x-log-300px.png" height = "300" style = " vertical-align: middle;" / >
< span style = "font-size: 3em; vertical-align: middle;" > =< / span >
< img src = "graphics/saco-800px.png" height = "300" style = " vertical-align: middle;" / >
< h4 > Alice wants to use her sales data to run a promotion< / h4 >
< attribution > (OpenClipArt.org)< / attribution >
< / section >
< section >
< img src = "graphics/matt-icons_text-x-log-300px.png" height = "300" style = " vertical-align: middle;" / >
< span style = "font-size: 3em; vertical-align: middle;" > →< / span >
< img src = "graphics/database-server-800px.png" height = "300" style = " vertical-align: middle;" / >
< h4 > So Alice loads up her sales data in her trusty database/hadoop/spark/etc... server.< / 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 >
< 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;" / >
< h4 > ... and basks in the limitless possibilities of big data.< / h4 >
< attribution > (OpenClipArt.org)< / attribution >
< / section >
< / section >
< section >
< section >
< h2 > Why is this a fairy tale?< / h2 >
< / section >
< section >
< img src = "graphics/matt-icons_text-x-log-300px.png" height = "300" style = " vertical-align: middle;" / >
< span style = "font-size: 3em; vertical-align: middle;" > →< / span >
< img src = "graphics/database-server-800px.png" height = "300" style = " vertical-align: middle;" / >
< h4 > It's never this easy...< / h4 >
< / section >
< / section >
< section >
< section >
< h2 > CSV Import< / h2 >
< h4 > Run a < code > SELECT< / code > on a raw CSV File< / h4 >
< ul class = "fragment" >
< li > File may not have column headers< / li >
< li > CSV does not provide "types"< / li >
< li > Lines may be missing fields< / li >
< li > Fields may be mistyped (typo, missing comma)< / li >
< li > Comment text can be inlined into the file< / li >
< / ul >
< p class = "fragment" >
< b > State of the art< / b > : External Table Defn < span class = "fragment" > + "Manually" edit CSV< / span >
< / p >
< / section >
< section >
< h2 > Merge Two Datasets< / h2 >
< 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 > Structure 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;" > Add structure, curation effort < b > On-Demand< / b > < / p >
< / section >
< section >
< h3 > But... you still need some sort of structure?!?< / h3 >
< h3 class = "fragment" > Let the database make a guess!< / 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/Bing-Translate.png" height = "500px" / >
< p class = "fragment" > Good Explanations, Alternatives, and Feedback Vectors< / p >
< / section >
< section >
< h2 > Communication< / h2 >
< ul >
< li > What data is uncertain?< / li >
< 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;" >
< li class = "fragment" > < b > A:< / b > Standard SQL.< / li >
< li class = "fragment" > < b > B:< / b > Annotated Output.< / li >
< li class = "fragment" > < b > C:< / b > Lens Diagram.< / li >
< li class = "fragment" > < b > D:< / b > Result Explanations.< / li >
< / ul >
< img src = "graphics/UIExample.png" style = "width:60%; float:right" / >
< / section >
< / 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 >
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< 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" / >
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< text x = "212" y = "20" style = "font-family: courier; font-size: 60%" > [ ]< / text >
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< image xlink:href = "graphics/jean-victor-balin-icon-table.svg" x = "360" y = "20" height = "50px" width = "50px" / >
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< text x = "220" y = "142" style = "font-size: 60%" > (best guess)< / text >
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< / 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 >
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< 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 >
2017-09-05 10:05:40 -04:00
<!--
2017-09-05 09:53:04 -04:00
< section >
< div style = "padding: 30px;" >
< p > $PRODUCTS.DEPARTMENT_{3}$< / p >
< div style = "font-size: 2em" > ⬍< / div >
< p > "I guessed 'Computer' for 'Department' on Row '3'"< / p >
< / div >
< / section >
2017-09-05 10:05:40 -04:00
-->
2017-09-05 09:53:04 -04:00
< 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 >
< p > < b > Email:< / b > okennedy@buffalo.edu< / p >
< p > < b > Office:< / b > Davis 338H< / p >
< p > < b > Web: < / b > < a href = "https://odin.cse.buffalo.edu" > https://odin.cse.buffalo.edu< / a > < / p >
< p > < b > Mimir: < / b > < a href = "http://mimirdb.info" > http://mimirdb.info< / a > < / p >
< p class = "fragment" style = "margin-top: 100px" > Today's password is < b > Frances Allen< / b > < / p >
< / section >
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});
< / script >
< / body >
< / html >
