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<!DOCTYPE HTML>
<!--
Tabular Data Analysis Workshop @ VLDB 2023
Template from html5up.net | @ajlkn
Free for personal and commercial use under the CCA 3.0 license (html5up.net/license)
-->
<html>
<head>
<title>Tabular Data Analysis Workshop @ VLDB 2023</title>
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<body class="is-preload">
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<!-- Header -->
<header id="header" class="alt">
<span class="logo"><img src="images/logo.svg" alt="" /></span>
<h1 property="dc:title">Tabular Data Analysis (TaDA) Workshop @ VLDB 2023</h1>
<p>Collocated with <a href="https://vldb.org/2023/">the 49th International Conference on Very Large Data
Bases (VLDB)</a> -
Vancouver, Canada - September 1, 2023
</p>
</header>
<!-- Nav -->
<nav id="nav">
<ul>
<li><a href="#objectives" class="active">Objectives</a></li>
<li><a href="#cfp">Call for Papers</a></li>
<li><a href="#submissions">Submissions</a></li>
<li><a href="#program">Program</a></li>
<li><a href="#papers">Accepted Papers</a></li>
<li><a href="#organization">Organization</a></li>
<li><a href="video-showcase.html">Video Showcase</a></li>
</ul>
</nav>
<!-- Main -->
<div id="main">
<!-- Objectives -->
<section id="objectives" class="main">
<div class="spotlight">
<div class="content">
<header class="major">
<h2>Objectives</h2>
</header>
<p>
<a href="https://en.wikipedia.org/wiki/Data_analysis">Data Analysis</a> is described as the
process of inspecting, cleansing, transforming, and modeling data with the goal of
discovering useful information, informing conclusions, and supporting decision-
making. Performing such tasks over large and heterogeneous
collections of tabular data, as found in <b>enterprise data lakes</b> and <b>on
the Web</b>, is extremely challenging and an attractive research topic
in data management, AI, and related communities. The goal of this workshop is to bring
together researchers and practitioners in these diverse communities that work on
addressing the fundamental research challenges of tabular data analysis and
building automated solutions in this space
</p>
<p>
We aim to provide a forum for: a) exchange of ideas between two communities: 1) an active
community of data management researchers working on data integration and schema and data
matching problems over tabular data, and 2) a vibrant community of researchers in AI and
Semantic Web communities working on the core challenge of matching tabular data to Knowledge
Graphs as a part of the <a href="https://www.cs.ox.ac.uk/isg/challenges/sem-tab/">ISWC
SemTab Challenges</a>.
b) presentation of late-breaking results related to several emerging research areas such as
table representation learning and its applications, automation of data science pipelines,
and data lake and data lakehouse solutions.
c) discussion of real-world data management challenges related to implementing industrial
scale tabular data anaylsis solutions.
</p>
</div>
</div>
</section>
<!-- Call For Papers -->
<section id="cfp" class="main">
<div class="content">
<header class="major">
<h2>Call For Papers</h2>
</header>
<b>Audience:</b> Our workshop encourages participation from researchers in data management,
AI, and Semantic Web communities working on a wide range of problems relevant to tabular
data analysis. We hope that this will constitute a single reference point for the
researchers and practitioners working in that area and help form new collaborations. We also
aim to provide a venue for researchers from industry and practitioners relying on various
tabular data analysis tasks to present use cases and discuss their needs in addressing
real-world problems and large-scale solutions.
<br><br>
<b>Topics of Interest</b> include but are not limited to:
<ul>
<li> Semantic Table Annotation </li>
<li> Automated Tabular Data Understanding </li>
<li> Exploratory Data Analysis over Tabular Data </li>
<li> Table Search in Data Lakes </li>
<li> Tabular Data Discovery </li>
<li> Tabular Data Discovery in Data Lakes </li>
<li> Tabular Data Discovery for Causal Inference </li>
<li> Metadata Management for Tabular Data Analysis </li>
<li> Data Augmentation with Tabular Data </li>
<li> Integration and Matching of Tabular Data </li>
<li> Knowledge Graph Construction and Completion with Tabular Data </li>
<li> Automated Discovery of ML Features from Tabular Data </li>
<li> ML Model Development with Tabular Data </li>
<li> Visualization and Interfaces for Tabular Data Analysis </li>
<li> Data Wrangling for Tabular Data Analysis </li>
<li> Deep Learning and Representation Learning for Tabular Data Analysis </li>
<li> Foundation Models for Tabular Data Analysis </li>
<li> Extraction and Analysis of Tabular Data from (HTML/PDF) Documents and Images </li>
<li> Analysis of Tabular Data on the Web (Web Tables) </li>
<li> Practical Applications of Tabular Data Analysis </li>
<li> Benchmarking and Evaluation Frameworks for Tabular Data Analysis </li>
</ul>
<b>Call for late breaking results:</b> We are now ready to receive your poster paper (2-page,
double-column) submissions for late breaking results, until June 20, AoE.
Those submissions will go through a light review phase and accepted submissions will have the
opportunity to give a short presentation at a workshop session,
for in-person attendees only, as well as a 5-minute recorded video presentation, shared on the
workshop website.
</div>
</section>
<!-- Submissions -->
<section id="submissions" class="main">
<div class="content">
<header class="major">
<h2>Submissions</h2>
</header>
Contributions to the workshop can take the form of technical papers, posters, or statements of
interest addressing various aspects of tabular data analysis, as well as reports on SemTab
Challenge participation. <b>Long technical papers</b> should be <b>8-10 pages</b> long.
<b>Short technical papers</b> should be no more than <b>4
pages</b>
long. <b>Posters</b> should not exceed <b>2 pages</b>. References do <b>not</b> count towards the
page
limits mentioned above.
<br><br>
Submission site: <a
href="https://cmt3.research.microsoft.com/TaDA2023">https://cmt3.research.microsoft.com/TaDA2023</a><br>
Submissions should follow the double-column
<a
href="https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/wqyfdgftmcfw">CEUR-ART
template</a>
<br>
<p>
Submissions will be single-blind.
Authors of accepted papers will have the option to include their papers in the CEUR-ART
proceedings
of the workshop. At least one co-author is expected to register for the VLDB 2023 conference and
present the paper in-person.
</p>
<header>
<h3>Important Dates </h3>
</header>
<ul>
<li>Abstract submission deadline: May 23, 2023</li>
<li>Submission deadline: <s>May 15, 2023</s> <b>May 30, 2023</b></li>
<li>Late breaking results (poster) submission deadline: <b>June 20, 2023</b></li>
<li>Notification of acceptance: June 23, 2023</li>
<li>Camera-ready copy due: July 20, 2023</li>
</ul>
All Times are Anywhere on Earth (AoE).
</div>
</section>
<!-- Program -->
<section id="program" class="main">
<div class="content">
<header class="major">
<h2>Program</h2>
</header>
<table>
<tr>
<td width="150"> 10:20-10:30 </td>
<td> <b>Opening</b> </td>
</tr>
<tr>
<td>10:30-11:20 </td>
<td> <b>Keynote talk </b> - Renée Miller: <b>From Discovery to Integration of Data Lake
Tables</b>
</td>
</tr>
<td> 11:20 - 12:00 </td>
<td> <b>Session 1</b> </td>
<tr>
<td colspan="2">
<table class="viz">
<tr>
<td width="150">11:20 - 11:40</td>
<td>Keti Korini, Christian Bizer. <b>Column Type Annotation using
ChatGPT</b>
<a href="https://ceur-ws.org/Vol-3462/TADA1.pdf">[pdf]</a>
</td>
</tr>
<tr>
<td>11:40 - 11:50 </td>
<td>Viet-Phi Huynh, Yoan Chabot, Raphael Troncy. <b>Towards Generative
Semantic
Table
Interpretation</b>
<a href="https://ceur-ws.org/Vol-3462/TADA7.pdf">[pdf]</a>
</td>
<tr>
<td>11:50 - 12:00 </td>
<td>Aneta Koleva, Martin Ringsquandl, Volker Tresp.
<b>Adversarial
Attacks on
Tables with Entity
Swap</b>
<a href="https://ceur-ws.org/Vol-3462/TADA4.pdf">[pdf]</a>
</td>
</tr>
</table>
</tr>
</td>
</tr>
<tr>
<td>12:00 - 13:30 </td>
<td> <b>Lunch</b></td>
</tr>
<tr>
<td>13:30 - 14:20 </td>
<td> Keynote talk - Alon Halevy: <b>Personal Digital Data: Where LLMs Meet
Structured Data</b></td>
</tr>
<tr>
<td>14:20 - 15:00 </td>
<td> <b>Session 2</b> </td>
<tr>
<td colspan="2">
<table class="viz">
<tr>
<td width="150">14:20 - 14:30</td>
<td>Hamed Mirzaei, Davood Rafiei. <b>Table Union Search with
Preferences</b>
<a href="https://ceur-ws.org/Vol-3462/TADA2.pdf">[pdf]</a>
</td>
</tr>
<tr>
<td>14:30 - 14:40 </td>
<td>Vijay S Kumar, Varish Mulwad, Jenny Williams, Tim Finin,
Sharad Dixit, Anupam Joshi. <b>Knowledge Graph-driven Tabular Data Discovery
from Scientific
Documents</b> <a href="https://ceur-ws.org/Vol-3462/TADA6.pdf">[pdf]</a>
</td>
</tr>
<tr>
<td>14:40 - 14:50 </td>
<td> Arif Usta, Semih Salihoglu. <b>To Join or Not to Join: An
Analysis on
the
Usefulness of
Joining Tables in Open Government Data Portals</b> <a
href="https://ceur-ws.org/Vol-3462/TADA5.pdf">[pdf]</a>
</td>
</tr>
<tr>
<td>14:50 - 15:00 </td>
<td>Liane Vogel, Carsten Binnig. <b>WikiDBs: A Corpus Of
Relational
Databases
From Wikidata</b> <a
href="https://ceur-ws.org/Vol-3462/TADA3.pdf">[pdf]</a>
</td>
</tr>
</table>
</tr>
</td>
</tr>
<tr>
<td>15:00 - 15:50 </td>
<td><b> Poster session </b></td>
</tr>
<tr>
<td colspan="2">
<table class="viz">
<tr>
<td width="150"> 15:00 - 15:05</td>
<td>Davood Rafiei, Arash Dargahi Nobari, Soroush
Omidvartehrani.
<b>Discovering
and Integrating
Tabular Data</b> <a
href="https://ceur-ws.org/Vol-3462/TADA9.pdf">[pdf]</a>
</td>
</tr>
<tr>
<td>15:05 - 15:10</td>
<td>Eva Chrysostomaki, Maria Stratigi, Vasilis Efthymiou,
Kostas
Stefanidis,
Dimitris Plexousakis. <b>Fair Sequential Group Recommendations in SQUIRREL
Movies</b> <a href="https://ceur-ws.org/Vol-3462/TADA8.pdf">[pdf]</a>
</td>
</tr>
</table>
</td>
</tr>
<tr>
<td>15:50 - 16:00 </td>
<td> <b>Closing and Awards</b> </td>
</tr>
</table>
<p>
Keynote by <a href="https://www.khoury.northeastern.edu/people/renee-miller/"><b>Renée Miller,
Northeastern University</b></a> <br>
Title: <b>From Discovery to Integration of Data Lake Tables</b><br>
Abstract: We have made tremendous strides in providing tools for data scientists to discover new
tables that are useful for their analyses. But despite these advances, the proper integration of
discovered tables has been under-explored. An interesting semantics for integration, called full
disjunction, was proposed in the 1990’s, but there has been little progress in using it for data
science to integrate tables culled from data lakes. In this talk, I will overview both ALITE, a
method to integrate (possibly incomplete) tables using a new scalable implementation of full
disjunction, and DIALITE, an open discovery system that lets users discover, integrate, then
analyze a set of tables using discovery methods such as Starmie, a new table union search
method. To evaluate our systems, we developed and shared three new benchmarks for integration
that use real data lake tables. I will present open problems and challenges in developing and
evaluating scalable table search and integration methods on real data. <br><br>
The ALITE [1] work was led by Aamod Khatiwada in collaboration with Professors Roee Shraga of
the Worcester Polytechnic Institute, Renée Miller, and Wolfgang Gatterbauer of Northeastern
University in Boston. DIALTE [2} was also led by Aamod Khatiwada in collaboration with
Professors Roee Shraga and Renée Miller.
Starmie [3] was led by Grace Fan in collaboration with Megagon Labs researchers Jin Wang,
Yuliang Li and Dan Zhang.
<br />
[1] Aamod Khatiwada, Roee Shraga, Wolfgang Gatterbauer, Renée J. Miller: Integrating Data Lake
Tables. PVLDB. 16(4): 932-945 (2022).<br />
[2] Aamod Khatiwada, Roee Shraga, Renée J. Miller: DIALITE: Discover, Align and Integrate Open
Data Tables. ACM SIGMOD, 187-190 (2023).<br />
[3] Grace Fan, Jin Wang, Yuliang Li, Dan Zhang, Renée J. Miller: Semantics-aware Dataset
Discovery from Data Lakes with Contextualized Column-based Representations. PVLDB. 16(8):
1726-1739 (2023)
</p>
<p>
Keynote by <a href="https://ai.facebook.com/people/alon-halevy/"><b>Alon Halevey, Meta
AI</b></a> <br>
Title: <b>Personal Digital Data: Where LLMs Meet Structured Data</b><br>
Abstract: The important question of how companies and organizations use our data has
received a lot of attention in the technology and policy communities. An equally important
question that deserves more focus going forward is how we, as individuals, can take advantage of
the data we generate to improve our health, vitality, and productivity and our overall
well-being.
We create a variety of data throughout our days, including our photos, workout stats, locations
we’ve been
to, the stuff we buy online and the content we consume. Fusing all this data together enables us
to build a
fascinating timeline of our lives. To leverage these timelines in order to help us produce new
satisfying
experiences we need to be able to query our timelines in natural language and to share short
summaries of
it with external services. <br><br>
This talk will start by motivating the work on fusing personal digital data including its
potential pitfalls.
I will then discuss multiple approaches to the problem of querying timelines, which is an
application area that
forces us to consider deeply how language models can be used to query data that is partially
structured and partially not.
</p>
<p>
</p>
</div>
</section>
<!-- Accepted Papers -->
<section id="papers" class="main">
<div class="content">
<header class="major">
<h2>Accepted Papers</h2>
</header>
<p>The joint proceedings of VLDB 2023 workshops are available here: <a
href="https://ceur-ws.org/Vol-3462/">https://ceur-ws.org/Vol-3462/</a>.</p>
<ul>
<li>Keti Korini, Christian Bizer. <b>Column Type Annotation using ChatGPT</b> <a
href="https://ceur-ws.org/Vol-3462/TADA1.pdf">[pdf]</a>
</li>
<li>Hamed Mirzaei, Davood Rafiei. <b>Table Union Search with Preferences</b> <a
href="https://ceur-ws.org/Vol-3462/TADA2.pdf">[pdf]</a>
</li>
<li>Liane Vogel, Carsten Binnig. <b>WikiDBs: A Corpus Of Relational Databases From Wikidata</b>
<a href="https://ceur-ws.org/Vol-3462/TADA3.pdf">[pdf]</a>
</li>
<li>Aneta Koleva, Martin Ringsquandl, Volker Tresp. <b>Adversarial Attacks on Tables with Entity
Swap</b> <a href="https://ceur-ws.org/Vol-3462/TADA4.pdf">[pdf]</a>
</li>
<li>Arif Usta, Semih Salihoglu. <b>To Join or Not to Join: An Analysis on the Usefulness of
Joining Tables in Open Government Data Portals</b> <a
href="https://ceur-ws.org/Vol-3462/TADA5.pdf">[pdf]</a>
</li>
<li>Vijay S Kumar, Varish Mulwad, Jenny Williams, Tim Finin, Sharad Dixit, Anupam Joshi.
<b>Knowledge Graph-driven Tabular Data Discovery from Scientific Documents</b> <a
href="https://ceur-ws.org/Vol-3462/TADA6.pdf">[pdf]</a>
</li>
<li>Viet-Phi Huynh, Yoan Chabot, Raphael Troncy. <b>Towards Generative Semantic Table
Interpretation</b> <a href="https://ceur-ws.org/Vol-3462/TADA7.pdf">[pdf]</a>
</li>
<li>Eva Chrysostomaki, Maria Stratigi, Vasilis Efthymiou, Kostas Stefanidis, Dimitris
Plexousakis. <b>Fair Sequential Group Recommendations in SQUIRREL Movies</b> <a
href="https://ceur-ws.org/Vol-3462/TADA8.pdf">[pdf]</a>
</li>
<li>Davood Rafiei, Arash Dargahi Nobari, Soroush Omidvartehrani. <b>Discovering and Integrating
Tabular Data</b> <a href="https://ceur-ws.org/Vol-3462/TADA9.pdf">[pdf]</a>
</li>
</ul>
</div>
</section>
<!-- Organization -->
<section id="organization" class="main">
<div class="content">
<header class="major">
<h2>Organization</h2>
</header>
<b>Organizing Committee:</b>
<ul>
<li><span itemprop="name"><a href="https://sites.google.com/site/vefthym/home">Vasilis
Efthymiou</a></span> (main contact person)
</li>
<li><span itemprop="name"><a href="https://sainyamgalhotra.com/">Sainyam Galhotra</a></span>
</li>
<li><span itemprop="name"><a href="https://research.ibm.com/people/oktie-hassanzadeh">Oktie
Hassanzadeh</a></span></li>
<li><span itemprop="name"><a
href="https://www.city.ac.uk/about/people/academics/ernesto-jimenez-ruiz">Ernesto
Jiménez-Ruiz</a></span></li>
<li><span itemprop="name"><a
href="https://researcher.watson.ibm.com/researcher/view.php?person=ibm-Kavitha.Srinivas">Kavitha
Srinivas</a></span></li>
</ul>
<b>Steering Committee:</b>
<ul>
<li>Haoyu Dong (<span itemprop="affiliation">Microsoft</span>)</li>
<li>Shi Han (<span itemprop="affiliation">Microsoft</span>) </li>
<li>Madelon Hulsebos (<span itemprop="affiliation">University of Amsterdam</span>)</li>
<li>Chuan Lei (<span itemprop="affiliation">AWS</span>) </li>
<li>Fatemeh Nargesian (<span itemprop="affiliation">University of Rochester</span>)</li>
<li>Natasha Noy (<span itemprop="affiliation">Google</span>)</li>
<li>Horst Samulowitz (<span itemprop="affiliation">IBM Research</span>)</li>
</ul>
<b>Program Committee:</b>
<ul>
<li>Omar Benjelloun (Google)</li>
<li>Rafael Berlanga Llavori (University Jaume I)</li>
<li>Jiaoyan Chen (The University of Manchester)</li>
<li>Peter Christen (The Australian National University)</li>
<li>Vassilis Christophides (ENSEA)</li>
<li>Vincenzo Cutrona (SUPSI)</li>
<li>Anastasia Dimou (KU Leuven)</li>
<li>Michael R. Glass (IBM Research AI)</li>
<li>Ekaterini Ioanou (Tilburg University)</li>
<li>Asterios Katsifodimos (TU Delft)</li>
<li>Udayan Khurana (IBM Research)</li>
<li>Hongrae Lee (Google)</li>
<li>Venkata Vamsikrishna Meduri (IBM Research, Almaden)</li>
<li>Marco Mesiti (University of Milan)</li>
<li>Renée Miller (Northeastern University)</li>
<li>Carina Negreanu (Microsoft Research)</li>
<li>George Papadakis (University of Athens)</li>
<li>Paolo Papotti (EURECOM)</li>
<li>Lucian Popa (IBM Almaden Research Center)</li>
<li>Ismael Sanz (Universitat Jaume I)</li>
<li>Roee Shraga (Northeastern University)</li>
<li>Kostas Stefanidis (Tampere University)</li>
<li>Raphael Troncy (EURECOM)</li>
<li>You Wu (Google)</li>
</ul>
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