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<!doctype html>
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<title>GRADES-NDA 2025</title>
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<div id="title-container">8th Joint Workshop on Graph Data Management
Experiences & Systems (GRADES) and Network Data Analytics (NDA)
</div>
<div id="subtitle-container"> Co-located with <a href="https://2024.sigmod.org/"> SIGMOD/PODS 2025 </a> (June 27, 2025, Berlin, Germany)
</div>
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<a href="https://twitter.com/gradesnda?ref_src=twsrc%5Etfw" class="twitter-follow-button" data-show-count="false" data-size="large">Follow @gradesnda</a><script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
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<!-- <li><a href="#accepted" class="bordered">Accepted Papers</a></li> -->
<!-- <li><a href="#">Registration</a></li>-->
<li><a href="#dates">Important Dates</a></li>
<li><a href="#program" class="bordered">Program</a></li>
<!-- <li><a href="https://dl.acm.org/doi/proceedings/10.1145/3461837" class="bordered">Proceedings</a></li> -->
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<li><a href="#pc">Program Committee</a></li>
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<li><a href="#previous">Past Workshops</a></li>
<li><a href="#sponsors">Sponsors</a></li>
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<section class="row">
<div class="col-full">
<h2>Call for Papers</h2>
<p> The goal of GRADES-NDA is to bring together researchers from academia, industry, and government (1) to
create a forum for discussing recent advances in (large-scale) graph data management and graph analytics
systems, as well as propose and discuss novel methods and techniques towards (2) addressing domain-specific challenges or (3) handling noise in real-world graphs.</p>
<p>The workshop will be of interest to researchers in the development of novel data-management applications
and systems for large-scale graph analytics. More specifically, the intended audience are, but not
limited to, academic and industrial computer scientists interested in databases and data mining, machine
learning, data streaming, network science, graph theory, and algorithms. Along with novel research work, we encourage
submissions with demonstrations and case studies from real-life experiences in various domains such as
Social Networks, Biological Network Data, Marketing and Media, Business Data Analysis, Healthcare Data,
Cybersecurity etc.
</p>
<p>Topics of interest include but are not limited to the following.</p>
<ul>
<li>Graph query languages, visualization techniques and querying interfaces, and their effective realization</li>
<li>Graph platform and parallel platforms, e.g., Flink/Gelly, Titan, SPARK/GraphX, GraphLab/PowerGraph, Giraph, GraphChi etc.</li>
<li>Network data representation, storage, indexing and querying methods.</li>
<li>Experiences or techniques for graph specific operations such as traversals or inference/reasoning in the context of large data sets and on the systems that implement those operations.</li>
<li>RDF data management and analytics</li>
<li>Dynamic Graphs: managing graph updates; graph stream analytics; analyzing evolution and detection of community structures in real-world evolving graphs</li>
<li>Mining and machine learning on heterogeneous networks -- knowledge graphs etc.</li>
<li>Graph summarization and sampling</li>
<li>Game Theory, Social contagion and Information propagation on networks</li>
<li>Analytics on dirty, noisy, or uncertain graphs</li>
<li>Spatial and temporal graph analytics</li>
<li>Analytics on social, biological, retail, marketing, customer care, financial, healthcare, transportation network data sets</li>
<li> Descriptions of graph data management use cases and query workloads, and experiences with applying data management technologies in such situations</li>
<li>Vision and systems papers describing potential or real applications and benefits of graph management, in particular (but not only) in the age of large language models (LLMs)</li>
</ul>
<br>
<p> Accepted papers will be published by ACM, indexed by DBLP, and will be available in the ACM DL.</p>
</div>
</section>
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\item \emph{Graph modeling and processing}: Advances in techniques for representing, visualizing, storing, indexing, querying, and managing graph data.
\item \emph{RDF and Graph Databases:}
\begin{itemize}
\item Data and/or index structures.
\item Proposals of benchmarks for RDF and graph database workloads and their performance evaluation on diverse data management systems.
\item Query processing and optimization algorithms for RDF and graph database systems.
\item System descriptions.
\end{itemize}
\item \emph{Dynamic and temporal graphs}:
\begin{itemize}
\item Efficient and reliable change updates in graph data.
\item Managing evolving networks and their applications.
\item Analysing evolution and detection of community structures in real-world graphs.
\item Spatio-temporal graph analytics.
\end{itemize}
\item \emph{Graph metrics}: Methods for measuring graph characteristics, e.g., diameter, eigenvalues, triangle counting.
\item \emph{Scalable graph processing}: Innovations in technologies for large-scale graph analytics.
\begin{itemize}
\item \emph{Core graph platforms and parallel computing frameworks}: Exploration of graph processing platforms and parallel computing technologies, e.g., Titan, Giraph, GraphChi, SPARK/GraphX, GraphLab/PowerGraph, with a focus on scalability, performance optimization, and practical applications.
\item \emph{Mining and machine learning on heterogeneous networks}: Techniques for extracting insights and patterns from heterogeneous networks, with applications in clustering, link prediction, anomaly detection, representation learning, etc.
\item Experiences or techniques for graph-specific operations such as traversals or inference/reasoning in the context of large data sets and on the systems that implement those operations.
\item Graph summarization and sampling
\end{itemize}
\item \emph{Human-centric graph processing: Interactive} techniques and human-in-the-loop approaches to enhance graph data exploration, querying, and analytics.
\item \emph{GenAI techniques}: Integration of Knowledge Graphs and Large Language Models for information retrieval, question answering, knowledge inference, and natural language understanding.
\item \emph{Neuro-symbolic approaches}: Hybrid techniques that combine Graph Neural Networks (GNNs) with rule-based systems for reasoning and analytics.
\item \emph{Reliability and security}: Verification and validation tools and techniques for trustworthy graph data processing, as well as security aspects, such as differential privacy and blockchain/graph-based ledgers.
\item \emph{Education}: Best practices for teaching emerging graph technologies, experience reports from educators, and innovative approaches to training students and practitioners.
\item \emph{Applications}: Descriptions of graph data management use cases and query workloads, and experiences with applying data management technologies in various areas, including but not limited to:
\begin{itemize}
\item Social Networks; Citation Networks; Co-Purchase Networks
\item Game Theory, Social contagion and Information propagation on networks
\item Biological Network Data; Ecological data
\item Retail, Marketing, and Media
\item Financial Services and Business Data Analysis
\item Customer Care; Healthcare; Transportation data
\item Cybersecurity
\end{itemize}
\item \emph{Vision papers} describing potential applications and benefits of graph management.
-->
<section class="row">
<div class="col">
<h2><a id="dates"></a>Important Dates</h2>
<ul>
<li>Abstract Submission: March 17, 2025</li>
<li>Paper Submission: March 22, 2025</li>
<li>Notifications: April 18, 2025</li>
<li>Camera Ready Submission: May 2, 2025</li>
<li>Workshop Date: June 27, 2025</li>
</ul>
<p></p>
<i>All deadlines are 23:59 Hours AoE</i>
<p></p>
</div>
<div class="col">
<h2>Workshop Organizers</h2>
<ul>
<li><a href="https://dlab.epfl.ch/people/aarora/">Akhil Arora</a>, Aarhus University & Copenhagen Center for Social Data Sience, Denmark</li>
<li><a href="https://web4.ensiie.fr/~stefania.dumbrava">Stefania Dumbrava</a>, ENSIIE & Télécom SudParis, France</li>
</ul><br>
<h2>Steering Committee</h2>
<ul>
<li><a href="http://olafhartig.de/">Olaf Hartig</a>, Amazon Web Services & Linköping University, Sweden</li>
<li><a href="https://cs.uwaterloo.ca/~ssalihog/">Semih Salihoglu</a>, University of Waterloo, Canada</li>
<li><a href="https://cs-people.bu.edu/vkalavri/">Vasiliki Kalavri</a>, Boston University, US</li>
<li><a href="https://www.tue.nl/en/research/researchers/george-fletcher/">George Fletcher</a>, TU Eindhoven, The Netherlands</li>
</ul>
</div>
</section>
<section class="row">
<div class="col-full">
<h2><a id="submission"></a>Paper Submission</h2>
<p>Authors are invited to submit original, unpublished research papers (full and short), demonstrations and case-studies. </p>
<p>Submissions must follow the latest 2-column ACM Proceedings format using the latest <a href="https://www.acm.org/publications/proceedings-template">ACM Primary Article Template</a>, and have to be anonymous. </p>
<p>Reviewing will be double-anonymous, for which the submissions must be anonymized by following the same anonymity requirements as for <a href="https://2025.sigmod.org/calls_papers_sigmod_research.shtml">regular track papers at the SIGMOD 2025 conference</a>. Use the following latex command to compile your paper without author names: <code>\documentclass[sigconf, anonymous, review]{acmart}</code>.</p>
</p>
<p>Length Requirements:</p>
<ul>
<li>Full papers should be a maximum of 8 pages in length, excluding references and appendix.</li>
<li>Case studies should be a maximum of 4 pages in length, excluding references and appendix.</li>
<li>Short papers and demonstration papers should be a maximum of 4 pages in length, excluding references and appendix.</li>
</ul>
<p>Submissions that do not follow these requirements will be rejected immediately.</p>
<br/>
<p>Submissions will be handled through Easychair.
To submit click <a href="https://easychair.org/conferences/?conf=gradesnda2025">here</a>.
</p>
</div>
</section>
<!--
<section class="row">
<div class="col-full">
<h2><a id="pc"></a>Program Committee</h2>
<ul>
<li> Renzo Angles, Universidad de Talca </li>
<li> Marcelo Arenas, PUC Chile </li>
<li> Amitabha Bagchi, Indian Institute of Technology, Delhi </li>
<li> Kaustubh Beedkar, IIT Delhi </li>
<li> Yang Cao, The University of Edinburgh </li>
<li> Nathalie Charbel, Neo4j </li>
<li> Juan Colmenares, Microsoft </li>
<li> Sourav Dutta, Huawei Research </li>
<li> George H. L. Fletcher, Eindhoven University of Technology </li>
<li> Russ Harmer, CNRS & ENS Lyon </li>
<li> Jan Hidders, Birkbeck College, University of London </li>
<li> Davide Mottin, Aarhus University </li>
<li> Nikos Ntarmos, Huawei Technologies R&D (UK) Ltd </li>
<li> Evaggelia Pitoura, Univ. of Ioannina </li>
<li> Petra Selmer, Bloomberg </li>
<li> Marco Serafini, University of Massachusetts Amherst </li>
<li> Hiroaki Shiokawa, University of Tsukuba </li>
<li> Vasileios Trigonakis, Oracle Labs </li>
<li> Hannes Voigt, Neo4j </li>
<li> Yinghui Wu, Case Western Reserve University </li>
<li> Yinglong Xia, Facebook </li>
<li> Yuichi Yoshida, National Institute of Informatics </li>
<li> Shangdi Yu, MIT </li>
</ul>
</div>
</section>
<section class="row">
<div class="col-full">
<h2><a id="travel"></a>Student Travel Awards</h2>
<p>Thanks to the generous support of our Sponsors, we are offering awards for selected students to attend GRADES-NDA and SIGMOD in person.
Each awardee will receive a stipend to partially cover the expense to attend the conference in-person.
Awardees are expected to register to SIGMOD in-person full conference and attend the GRADES-NDA Workshop
and later the SIGMOD conference. Students will have to make their own arrangements for travel and accommodation.
These awards are only for students who can attend in person.
If you cannot attend in person, we advise you to check with <a href="https://2023.sigmod.org/grants.shtml">the SIGMOD travel awards committee</a>.</p>
<p><b>Eligibility:</b> Applicants need to be a full-time undergraduate or graduate student.
You do not need to have an accepted paper to GRADES-NDA (or SIGMOD) to be eligible.
We will primarily prioritize students whose advisors cannot provide financial support.
We will also prioritize students who have a GRADES-NDA accepted paper, who are not from North America and Europe,
as well as female and minority students. </p>
<p><b>Application Procedure:</b> To apply for a grant, the student must email the necessary materials to GRADES-NDA chairs
(please email both Olaf and Yuichi) by <b>April 22</b>. We will notify applicants by <b>April 29</b>.
Please submit the following information in a single PDF file with your application:</p>
<ul>
<li>Your full name, school, and email address.</li>
<li>Your advisor's full name and email address.</li>
<li>Your CV.</li>
<li>An abstract, summarizing your thesis research and its connection to graph data management or graph analytics (at most one page in single column format).</li>
<li>If you think your presence could help diversity in the GRADES-NDA or SIGMOD community (in terms of the gender, geography/origin, ethnicity or in other ways), please add an additional paragraph with an explanation (does not count towards the one-page limit for your research).</li>
</ul>
</div>
</section>
-->
<section class="row">
<h2 id="previous">Past Workshops</h2>
<p>GRADES-NDA is in its eigth edition, and had successful joint meetings co-located with ACM SIGMOD/PODS from 2018 to 2024. Specifically, it is the merger of the GRADES and NDA workshops, which were each independently organized and successfully held at previous ACM SIGMOD/PODS conferences, GRADES since 2013 and NDA since 2017. The organizers of GRADES and NDA mutually agreed upon to aim for a joint meeting from 2018 onwards.</p>
<div class="col" style="width:30%">
<h2>GRADES-NDA</h2>
<ul>
<li><a href="http://gradesnda.github.io/2024/">GRADES-NDA 2024</a></li>
<li><a href="http://gradesnda.github.io/2023/">GRADES-NDA 2023</a></li>
<li><a href="http://gradesnda.github.io/2022/">GRADES-NDA 2022</a></li>
<li><a href="http://gradesnda.github.io/2021/">GRADES-NDA 2021</a></li>
<li><a href="http://gradesnda.github.io/2020/">GRADES-NDA 2020</a></li>
<li><a href="https://sites.google.com/site/gradesnda2019/">GRADES-NDA 2019</a></li>
<li><a href="https://sites.google.com/site/gradesnda2018/">GRADES-NDA 2018</a></li>
</ul>
</div>
<div class="col" style="width:30%">
<h2>GRADES</h2>
<ul>
<li><a href="https://event.cwi.nl/grades/2017/index.shtml">GRADES 2017</a></li>
<li><a href="https://event.cwi.nl/grades/2016/index.shtml">GRADES 2016</a></li>
<li><a href="https://event.cwi.nl/grades/2015/index.shtml">GRADES 2015</a></li>
<li><a href="https://event.cwi.nl/grades/2014/index.shtml">GRADES 2014</a></li>
<li><a href="https://event.cwi.nl/grades/2013/index.shtml">GRADES 2013</a></li>
</ul>
</div>
<div class="col" style="width:30%">
<h2>NDA</h2>
<ul>
<li><a href="https://sites.google.com/site/networkdataanalytics2017/">NDA 2017</a></li>
<li><a href="https://sites.google.com/site/networkdataanalytics2016/">NDA 2016</a></li>
</ul>
</div>
</section>
<section class="row">
<div class="col-full">
<h2 id="sponsors">Sponsored by</h2>
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<!-- <a href="https://neo4j.com/" class="col-3"><img src="img/neo4j-logo.png" alt="Neo4j"></a> -->
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<a href="https://www.sap.com/index.html" class="col-3"><img src="img/sap-logo.png" alt="SAP"></a>
</div>
</div>
</section>
<section class="row">
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<h2>Get in touch</h2>
<p>
For questions, please <a href="mailto:gradesnda2024@easychair.org">email</a>. Follow us on <a href="https://twitter.com/gradesnda">X (formerly Twitter)</a> for latest updates about the workshop.
</p>
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