日本データベース学会の皆様，
阪大の鬼塚です．
SIGMODに併設のワークショップで
Simplicity in Management of Data (SiMoD)
というワークショップが始まります（第一回目）．
近年の論文でのシステムは複雑な内容になりがちであるため，逆の発想に立って
シンプルで重要なコアアイデアの論文を募集することを主眼としているそうです(simple
ideas that work well in practice)．
アイデア論文と実験論文を募集していて，特にアイデア論文は4ページと短いです．
*Novel Ideas (up to 4 pages):*Papers in this track should present
early-stage, original ideas that were not proposed in the past. The
submission should be concise and distill the core idea on specific
problems being solved, with reasonable evidence (e.g., preliminary
experimental results) showing the idea's applicability. We also
encourage the authors to include the limitations of the proposed ideas.
Submissions in this track should not exceed four pages, including
everything, such as references.
投稿締め切りは 3/15 です．詳しくはワークショップページをご確認ください．
https://sfu-dis.github.io/simod/
--
Makoto Onizuka(鬼塚 真)
E-mail:onizuka@ist.osaka-u.ac.jp
TEL: 06-6879-7750/FAX：06-6879-7743
URL:http://www-bigdata.ist.osaka-u.ac.jp/
〒565-0871 大阪府吹田市山田丘 1-5 大阪大学大学院 情報科学研究科
マルチメディア工学専攻 ビッグデータ工学講座（鬼塚研究室）
日本データベース学会の皆様，
お世話になっております．筑波大学の塩川です．
グラフデータ管理・分析に関するワークショップGRADES-NDAの
論文募集についてご案内いたします．例年と同様にSIGMOD2023
の併設ワークショップとして開催される予定です．
詳細は下記をご参照下さい．
-----------------------------------------------------------------------------
Call for submissions
GRADES-NDA 2023
6th Joint Workshop on Graph Data Management Experiences & Systems
(GRADES) and Network Data Analytics (NDA)
In conjunction with SIGMOD/PODS 2023.
Sunday June 18, Seattle, WA, USA.
Workshop Website:
https://gradesnda.github.io/
Deadlines: March 15, 2023 (Abstracts), March 22, 2023 (Papers)
-----------------------------------------------------------------------------
*** FOCUS AND GOALS ***
The GRADES-NDA workshop focuses on the application areas, usage
scenarios and open challenges in managing large-scale graph-shaped data.
The workshop is a forum for exchanging ideas and methods for mining,
querying and learning with real-world network data, developing new
common understandings of the problems at hand, sharing of data sets and
benchmarks where applicable, and leveraging existing knowledge from
different disciplines. Additionally, considering specific techniques
(e.g., algorithms, data/index structures) in the context of the systems
that implement them, rather than describing them in isolation,
GRADES-NDA aims to present technical contributions inside graph, RDF and
other data management systems on graphs of a large size (many millions
of nodes and beyond).
The goal of GRADES-NDA is to bring together researchers from academia,
industry, and government, to create a forum for discussing recent
advances in (large-scale) graph data management and analytics systems,
as well as propose and discuss novel methods and techniques towards
addressing domain specific challenges, or handling noise in real-world
graphs.
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, 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.
*** WORKSHOP TOPICS ***
Topics of interest include but are not limited to the following.
* Graph query languages, visualization techniques and querying
interfaces, and their effective realization
* Graph platform and parallel platforms, e.g., Flink/Gelly, Titan,
SPARK/GraphX, GraphLab/PowerGraph, Giraph, GraphChi etc.
* Network data representation, storage, indexing and querying methods
* 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
* RDF data management and analytics
* Dynamic Graphs: managing graph updates; graph stream analytics;
analyzing evolution and detection of community structures in real-world
evolving graphs
* Mining and machine learning on heterogeneous networks -- knowledge
graphs etc.
* Graph summarization and sampling
* Game Theory, Social contagion and Information propagation on networks
* Analytics on dirty, noisy, or uncertain graphs
* Spatial and temporal graph analytics
* Analytics on social, biological, retail, marketing, customer care,
financial, healthcare, transportation network data sets
* Descriptions of graph data management use cases and query workloads,
and experiences with applying data management technologies in such
situations
* Vision and systems papers describing potential or real applications
and benefits of graph management
*** IMPORTANT DATES ***
* Abstract Submission: March 15, 2023
* Paper Submission: March 22, 2023
* Notifications: April 19, 2023
* Camera Ready Submission: May 3, 2023
* Workshop Date: June 18, 2023
All deadlines are 23:59 Hours AoE
*** WORKSHOP ORGANIZERS ***
Olaf Hartig, Amazon Web Services & Linköping University, Sweden
Yuichi Yoshida, National Institute of Informatics, Japan
Contact email: gradesnda2023(a)easychair.org
*** STEERING COMMIITTEE ***
Semih Salihoglu, University of Waterloo, Canada
Vasiliki Kalavri, Boston University, US
Akhil Arora, EPFL, Switzerland
George Fletcher, TU Eindhoven, The Netherlands
*** FURTHER DETAILS ***
More information, including submission guidelines, can be found on the
workshop website:
https://gradesnda.github.io/
---
Hiroaki Shiokawa, Ph.D
University of Tsukuba
Email: shiokawa(a)cs.tsukuba.ac.jp
