Merge branch 'master' of https://gitlab.odin.cse.buffalo.edu/odin-lab/Website
This commit is contained in:
Gokhan Kul
commit
3cb34e0a56
|
|
@ -5,7 +5,8 @@
|
|||
"due": "",
|
||||
"topic": "Introduction",
|
||||
"materials": {
|
||||
"slides" : "https://odin.cse.buffalo.edu/slides/cse4562sp2018/2018-01-29-Intro.html"
|
||||
"slides" : "https://odin.cse.buffalo.edu/slides/cse4562sp2018/2018-01-29-Intro.html",
|
||||
"print" : "https://odin.cse.buffalo.edu/slides/cse4562sp2018/2018-01-29-Intro.html?print-pdf"
|
||||
}
|
||||
},
|
||||
{
|
||||
|
|
@ -14,7 +15,8 @@
|
|||
"due": "",
|
||||
"topic": "SQL Overview + Physical Data Organization",
|
||||
"materials": {
|
||||
"slides" : "https://odin.cse.buffalo.edu/slides/cse4562sp2018/2018-01-31-SQL+Physical.html"
|
||||
"slides" : "https://odin.cse.buffalo.edu/slides/cse4562sp2018/2018-01-31-SQL+Physical.html",
|
||||
"print" : "https://odin.cse.buffalo.edu/slides/cse4562sp2018/2018-01-31-SQL+Physical.html?print-pdf"
|
||||
}
|
||||
},
|
||||
{
|
||||
|
|
|
|||
|
|
@ -2,6 +2,7 @@ require 'yaml'
|
|||
require 'redcarpet'
|
||||
require 'erb'
|
||||
require 'pipeline.rb'
|
||||
require 'date'
|
||||
|
||||
class Array
|
||||
def where
|
||||
|
|
|
|||
|
|
@ -43,13 +43,6 @@
|
|||
<!-- Any Talk-Specific Header Content Goes Here -->
|
||||
CSE 4/562 - Database Systems
|
||||
</div>
|
||||
<div class="footer">
|
||||
<!-- Any Talk-Specific Footer Content Goes Here -->
|
||||
<div style="float: left; margin-top: 15px; ">
|
||||
Exploring <u><b>O</b></u>nline <u><b>D</b></u>ata <u><b>In</b></u>teractions
|
||||
</div>
|
||||
<img src="graphics/LabLogo-FullText-white.png" height="40" style="float: right;"/>
|
||||
</div>
|
||||
|
||||
<div class="slides">
|
||||
|
||||
|
|
@ -502,7 +495,7 @@
|
|||
// Full list of configuration options available at:
|
||||
// https://github.com/hakimel/../reveal.js#configuration
|
||||
Reveal.initialize({
|
||||
controls: false,
|
||||
controls: true,
|
||||
progress: true,
|
||||
history: true,
|
||||
center: true,
|
||||
|
|
|
|||
|
|
@ -43,13 +43,6 @@
|
|||
<!-- Any Talk-Specific Header Content Goes Here -->
|
||||
CSE 4/562 - Database Systems
|
||||
</div>
|
||||
<div class="footer">
|
||||
<!-- Any Talk-Specific Footer Content Goes Here -->
|
||||
<div style="float: left; margin-top: 15px; ">
|
||||
Exploring <u><b>O</b></u>nline <u><b>D</b></u>ata <u><b>In</b></u>teractions
|
||||
</div>
|
||||
<img src="graphics/LabLogo-FullText-white.png" height="40" style="float: right;"/>
|
||||
</div>
|
||||
|
||||
<div class="slides">
|
||||
|
||||
|
|
@ -237,7 +230,7 @@
|
|||
SELECT tree_id FROM Trees WHERE spc_common = 'sycamore maple'
|
||||
</code></pre>
|
||||
<p style="font-size: 70%">Computes the <b>set-union</b> of any two <b>union-compatible</b> sets of tuples</p>
|
||||
<p style="font-size: 70%">Adding <code>ALL</code> preserves duplicates across the inputs.</p>
|
||||
<p style="font-size: 70%">Adding <code>ALL</code> preserves duplicates across the inputs (<b>bag-union</b>).</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -247,15 +240,13 @@
|
|||
FROM relationlist
|
||||
WHERE condition
|
||||
GROUP BY groupinglist
|
||||
HAVING group-condition
|
||||
HAVING groupcondition
|
||||
</code></pre>
|
||||
<div style="font-size: 70%">
|
||||
<p>The target-list now contains...<ol class="tight" style="margin-top: 0px; margin-left: 100px;">
|
||||
<li>grouped attributes</li>
|
||||
<li>aggregate expressions</li>
|
||||
</ol></p>
|
||||
<p>Targets of type (1) must be a subset of the grouping-list</p>
|
||||
<p>The <span color="red">targetlist</span> now contains <b>(a)</b> Grouped attributes, and <b>(b)</b>Aggregate expressions.</p>
|
||||
<p>Targets of type (a) must be a subset of the grouping-list</p>
|
||||
<p style="font-size: 70%">(intuitively each answer tuple corresponds to a single group, and each group must have a single value for each attribute)</p>
|
||||
<p style="margin-top: 20px"><span color="red">groupcondition</span> is applied <i>after</i> aggregation and may contain aggregate expressions.</p>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
|
|
@ -317,10 +308,24 @@
|
|||
</section>
|
||||
|
||||
<section>
|
||||
<h3>Record Layout 2: Delimiters</h3>
|
||||
<h3>Record Layout 2: Headers</h3>
|
||||
<svg data-src="graphics/2018-01-31-record-header.svg" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h3>Record Formats</h3>
|
||||
<dl>
|
||||
<dt>Fixed</dt>
|
||||
<dd>Constant-size fields. Field $i$ at byte $\sum_{j < i} |Field_j|$</dd>
|
||||
<dt>Delimited</dt>
|
||||
<dd>Special character or string (e.g., <code>,</code>) between fields</dd>
|
||||
<dt>Header</dt>
|
||||
<dd>Fixed-size header points to start of each field</dd>
|
||||
<dt> </dt>
|
||||
<dd> </dd>
|
||||
</dl>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<h3>File Formats</h3>
|
||||
<dl>
|
||||
|
|
@ -341,6 +346,7 @@
|
|||
|
||||
<section>
|
||||
<svg data-src="graphics/2018-01-31-mem_bulk_loading.svg" class="stretch"/>
|
||||
<imagecredits>openclipart.org</imagecredits>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -356,6 +362,19 @@
|
|||
<dd>A primitive value (for now)</dd>
|
||||
</dl>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<svg data-src="graphics/2018-01-29-db_as_mediator.svg" class="stretch"/>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<pre><code class="python">
|
||||
with db_open('Trees') as data:
|
||||
for record in data:
|
||||
if(records['BORONAME'] == 'Brooklyn'):
|
||||
print(fields['TREE_ID']);
|
||||
</code></pre>
|
||||
</section>
|
||||
</section>
|
||||
|
||||
|
||||
|
|
@ -369,7 +388,7 @@
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history: true,
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center: true,
|
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|
|
|
|||
962
slides/cse4562sp2018/graphics/2018-01-29-db_as_mediator.svg
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962
slides/cse4562sp2018/graphics/2018-01-29-db_as_mediator.svg
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|
||||
</g>
|
||||
</svg>
|
||||
|
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points="20,60 140,60 120,50 140,60 120,70 140,60"
|
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transform="translate(0,390) rotate(-60)"
|
||||
/>
|
||||
<g style="font-size: 18px; stroke-width: 0; fill: rgba(120,120,120,1); ">
|
||||
<text x="130" y="211">Probability</text>
|
||||
<text x="130" y="237">Expectation</text>
|
||||
<text x="130" y="263">Variance</text>
|
||||
<text x="130" y="289">Histogram</text>
|
||||
</g>
|
||||
<g class="fragment" data-fragment-index="7">
|
||||
<g>
|
||||
<image
|
||||
xlink:href="graphics/dagobert83-female-user-icon-800px.png"
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width="100" height="100"
|
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@ -196,7 +196,7 @@
|
|||
|
||||
<section>
|
||||
<p>We have tools that can solve these problem!</p>
|
||||
<img src="graphics/happy_alice.svg" width="200px" height="200px" />
|
||||
<img src="graphics/happy_alice.svg" width="200px" height="200px" class="fragment" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -230,7 +230,11 @@
|
|||
|
||||
<section>
|
||||
<p>
|
||||
<b>In the name of Codd</b><br/><span class="fragment grow highlight-current-blue" data-fragment-index="2">Thou shalt not give the user a wrong answer.</span>
|
||||
<b>In the name of Codd</b><br/>Thou shalt not give the user a wrong answer.
|
||||
</p>
|
||||
|
||||
<p style="margin-top: 50px;" class="fragment">
|
||||
... but this assumes that we start with perfect data.
|
||||
</p>
|
||||
</section>
|
||||
|
||||
|
|
@ -238,6 +242,10 @@
|
|||
<svg data-src="graphics/blackbox.svg" class="stretch" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/dataquality-poop.svg"/>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/obamacare_stats_fail.jpg" height="400" />
|
||||
<imagecredits>(Fox News)</imagecredits>
|
||||
|
|
@ -322,17 +330,35 @@ Sampling (x10), 300, 242.5666234549135, 300, 119.61607021316885, 162.00108394436
|
|||
|
||||
<section>
|
||||
<section>
|
||||
<p>The <img src="graphics/mimir_logo_final.png" height="150px" style="vertical-align: middle"/>Uncertainty-Aware Database</p>
|
||||
<h2>Declarative Uncertainty</h2>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/mimir_logo_final.png" height="150px" style="vertical-align: middle"/>
|
||||
<p>The Uncertainty Management System</p>
|
||||
<p><a href="http://mimirdb.info">http://mimirdb.info</a></p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>Mimir is a vehicle for research on...</p>
|
||||
<svg data-src="graphics/mimir-workflow.svg" />
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>At each step, Mimir tracks ambiguity and potential errors.</p>
|
||||
<ul>
|
||||
<li>A row that may or may not exist.</li>
|
||||
<li>An attribute value that is missing or ambiguous.</li>
|
||||
<li>A table with multiple possible schemas.</li>
|
||||
<li style="color: #999">A violated constraint.</li>
|
||||
</ul>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<p>Declarative uncertainty requires...</p>
|
||||
<ol>
|
||||
<li class="fragment" data-fragment-index="1">... uncertainty capture</li>
|
||||
<li class="fragment" data-fragment-index="2"><span class="fragment highlight-current-red" data-fragment-index="5">... query processing over uncertain data</span></li>
|
||||
<li class="fragment" data-fragment-index="3"><span class="fragment highlight-current-red" data-fragment-index="5">... intuitive and qualitative presentation of uncertainty</span></li>
|
||||
<li class="fragment" data-fragment-index="4">... other things that we can do to make Alice's life easier</li>
|
||||
<li class="fragment" data-fragment-index="2"><span class="fragment highlight-current-red" data-fragment-index="4">... query processing over uncertain data</span></li>
|
||||
<li class="fragment" data-fragment-index="3"><span class="fragment highlight-current-red" data-fragment-index="4">... intuitive and qualitative presentation of uncertainty</span></li>
|
||||
</ol>
|
||||
</section>
|
||||
|
||||
|
|
@ -398,13 +424,12 @@ Sampling (x10), 300, 242.5666234549135, 300, 119.61607021316885, 162.00108394436
|
|||
$$R(1, 2) \mapsto 1$$
|
||||
$$R(1, 3) \mapsto 1$$
|
||||
$$R(4, 3) \mapsto 1$$
|
||||
$$S(2, 5) \mapsto 1$$
|
||||
$$S(3, 6) \mapsto 2$$
|
||||
</p>
|
||||
<p class="fragment">
|
||||
$$R(4, 5) \mapsto 0$$
|
||||
</p>
|
||||
<p class="fragment">
|
||||
$$S(3, 6) \mapsto 2$$
|
||||
</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -513,19 +538,20 @@ Sampling (x10), 300, 242.5666234549135, 300, 119.61607021316885, 162.00108394436
|
|||
</section>
|
||||
|
||||
<section>
|
||||
<h3>Information Extractors</h3>
|
||||
<h3>Summarizing Possible Worlds</h3>
|
||||
|
||||
$$\mathcal K^W \rightarrow \mathcal K$$
|
||||
(plug in any $K$-Relation-compatible $\mathcal K$)
|
||||
|
||||
<dl>
|
||||
<dt class="fragment" data-fragment-index="1" style="margin-top: 50px;">Possible World Value</dt>
|
||||
<dt class="fragment" data-fragment-index="1" style="margin-top: 50px;">Annotation in World $i$</dt>
|
||||
<dd class="fragment" data-fragment-index="1">$\texttt{PW}_i(\vec k) \equiv \vec k_i$</dd>
|
||||
<dt class="fragment" data-fragment-index="2" style="margin-top: 20px;">Certain Value</dt>
|
||||
<dt class="fragment" data-fragment-index="2" style="margin-top: 20px;">Certain Annotation</dt>
|
||||
<dd class="fragment" data-fragment-index="2">$\mathcal C(\vec k) \equiv min(\vec k)$</dd>
|
||||
<dt class="fragment" data-fragment-index="3" style="margin-top: 20px;">Possible Value</dt>
|
||||
<dt class="fragment" data-fragment-index="3" style="margin-top: 20px;">Possible Annotation</dt>
|
||||
<dd class="fragment" data-fragment-index="3">$\mathcal P(\vec k) \equiv max(\vec k)$</dd>
|
||||
</dl>
|
||||
<p style="font-size: 50%" class="fragment">Correct/Possible mirrors "Correctness of SQL Queries on Databases with Nulls" [Guagliardo, Libkin 2017]</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -629,7 +655,7 @@ Sampling (x10), 300, 242.5666234549135, 300, 119.61607021316885, 162.00108394436
|
|||
<section>
|
||||
<p>Can we do the same thing for $\mathcal C(Q(\mathcal D))$?</p>
|
||||
|
||||
<p class="fragment">$$C(Q(\mathcal D)) \stackrel{?}{=} C(Q(\mathcal D))$$</p>
|
||||
<p class="fragment">$$C(Q(\mathcal D)) \stackrel{?}{=} Q(\mathcal C(\mathcal D))$$</p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -650,9 +676,10 @@ Sampling (x10), 300, 242.5666234549135, 300, 119.61607021316885, 162.00108394436
|
|||
<section>
|
||||
<table>
|
||||
<tr><th style="border-right: solid 1px">$\pi_B$R</th><th>B</th><td></td><th>$K^W$</th><th>$\mathcal C$</th></tr>
|
||||
<tr><td style="border-right: solid 1px"> </td><td>2</td><td>$\mapsto$</td><td>$[1,1]$</td><td class="fragment">$1$</td></tr>
|
||||
<tr><td style="border-right: solid 1px"> </td><td>3</td><td>$\mapsto$</td><td>$[2,2]$</td><td class="fragment">$1+0+0=1$</td></tr>
|
||||
<tr><td style="border-right: solid 1px"> </td><td>2</td><td>$\mapsto$</td><td>$[1,1]$</td><td class="fragment">$\mathcal C([1,1]) = 1$</td></tr>
|
||||
<tr><td style="border-right: solid 1px"> </td><td>3</td><td>$\mapsto$</td><td>$[2,2]$</td><td class="fragment">$\mathcal C([1,1])+\mathcal C([1,0])+\mathcal C([0,1])$</td></tr>
|
||||
</table>
|
||||
<p class="fragment">$=1+0+0=1$ <span class="fragment">$\neq C([2,2])$</span></p>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
|
|
@ -662,11 +689,11 @@ Sampling (x10), 300, 242.5666234549135, 300, 119.61607021316885, 162.00108394436
|
|||
<section>
|
||||
<h3>We can Approximate</h3>
|
||||
<dl>
|
||||
<dt>Soundness</dt>
|
||||
<dt>(C-) Soundness</dt>
|
||||
<dd class="fragment" data-fragment-index="1">$Q(\mathcal C(\mathcal D)) \leq \mathcal C(Q(\mathcal D))$</dd>
|
||||
<dd class="fragment" data-fragment-index="2">We can efficiently compute a conservative approximation of $\mathcal C$.
|
||||
|
||||
<dt>(Conditional) Completeness</dt>
|
||||
<dt>Completeness (for some queries)</dt>
|
||||
<dd class="fragment" data-fragment-index="3">$Q(\mathcal C(\mathcal D)) = \mathcal C(Q(\mathcal D))$ ...if $Q$ is <i>safe</i></dd>
|
||||
</dl>
|
||||
</section>
|
||||
|
|
@ -933,6 +960,11 @@ Tuple Bundles, 14.65919489, 300, 300
|
|||
</section>
|
||||
</section>
|
||||
|
||||
<section>
|
||||
<img src="graphics/mimir_logo_final.png" height="150px" style="vertical-align: middle"/>
|
||||
<p><a href="http://mimirdb.info">http://mimirdb.info</a></p>
|
||||
</section>
|
||||
|
||||
|
||||
<section>
|
||||
<table>
|
||||
|
|
|
|||
|
|
@ -57,6 +57,7 @@
|
|||
<image
|
||||
xlink:href="papers/p37-aggarwal.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="215.89999"
|
||||
height="279.39999"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -66,6 +67,7 @@
|
|||
<image
|
||||
xlink:href="papers/p517-shepard.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="215.89999"
|
||||
height="279.39999"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -75,6 +77,7 @@
|
|||
<image
|
||||
xlink:href="papers/p1-bhattacharya.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="215.89999"
|
||||
height="279.39999"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -84,6 +87,7 @@
|
|||
<image
|
||||
xlink:href="papers/p1483-wang.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="215.89999"
|
||||
height="279.39999"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -93,6 +97,7 @@
|
|||
<image
|
||||
xlink:href="papers/p2018-getoor.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="215.89999"
|
||||
height="279.39999"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -102,6 +107,7 @@
|
|||
<image
|
||||
xlink:href="papers/hodge.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="209.804"
|
||||
height="297.01068"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -111,6 +117,7 @@
|
|||
<image
|
||||
xlink:href="papers/btr597.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="215.73067"
|
||||
height="279.06134"
|
||||
preserveAspectRatio="none"
|
||||
|
|
@ -120,6 +127,7 @@
|
|||
<image
|
||||
xlink:href="papers/778_2008_Article_98.png"
|
||||
class="fragment"
|
||||
data-autoslide="200"
|
||||
width="209.97333"
|
||||
height="278.892"
|
||||
preserveAspectRatio="none"
|
||||
|
|
|
|||
|
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23
src/seminar/2018sp.erb
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23
src/seminar/2018sp.erb
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|
|
@ -0,0 +1,23 @@
|
|||
---
|
||||
title: The UBDB Seminar - Spring 2018
|
||||
schedule:
|
||||
- when: March 1; 1:00-2:30 PM
|
||||
what: "Data, Responsibly"
|
||||
who: Julia Stoyanovich (Drexel)
|
||||
where: Davis 113A
|
||||
details:
|
||||
abstract: |
|
||||
Data-driven algorithmic decision making promises to improve people's lives, accelerate scientific discovery and innovation, and bring about positive societal change. Yet, if not used responsibly, this same technology can reinforce inequity, limit accountability and infringe on the privacy of individuals: irreproducible results can influence global economic policy; algorithmic changes in search engines can sway elections and incite violence; models based on biased data can legitimize and amplify discrimination in the criminal justice system; algorithmic hiring practices can silently reinforce diversity issues and potentially violate the law; privacy and security violations can erode the trust of users and expose companies to legal and financial consequences.<br/>
|
||||
In this talk I will discuss our recent work on establishing a foundational new role for database technology, in which managing data in accordance with ethical and moral norms, and legal and policy considerations becomes a core system requirement. I will define properties of responsible data management, which include fairness, transparency, and data protection. I will highlight some of our recent technical advances, and will discuss the over-all framework in which these responsibility properties are managed and enforced through all stages of the data lifecycle. The broader goal of our project is to help usher in a new phase of data science, in which the technology considers not only the accuracy of the model but also ensures that the data on which it depends respect the relevant laws, societal norms, and impacts on humans. Additional information about our project is available at DataResponsibly.com.
|
||||
bio: |
|
||||
Julia Stoyanovich is Assistant Professor of Computer Science at Drexel University, and an affiliated faculty at the Center for Information Technology Policy at Princeton. She is a recipient of an NSF CAREER award and of an NSF/CRA Computing Innovations Fellowship. Julia's research focuses on responsible data management and analysis practices: on operationalizing fairness, diversity, transparency, and data protection in all stages of the data acquisition and processing lifecycle. She established the Data, Responsibly consortium, serves on the ACM task force to revise the Code of Ethics and Professional Conduct, and is active in the New York City algorithmic transparency effort. In addition to data ethics, Julia works on management and analysis of preference data, and on querying large evolving graphs. She holds M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics and Statistics from the University of Massachusetts at Amherst.
|
||||
- when: March 8; Time TBD
|
||||
what: Title TBD
|
||||
who: Bill Howe (University of Washington)
|
||||
where: Location TBD
|
||||
details:
|
||||
abstract: TBD
|
||||
bio: TBD
|
||||
---
|
||||
|
||||
<p>Subscribe to <a href="https://listserv.buffalo.edu/cgi-bin/wa?A0=cse-database-list">cse-database-list</a> for more details about the UBDB seminar.</p>
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
---
|
||||
title: The UBDB Talk Series
|
||||
redirect: 2017sp.html
|
||||
redirect: 2018sp.html
|
||||
---
|
||||
Redirecting you <a href="<%=redirect%>">here</a>...
|
||||
Loading…
Reference in a new issue