日本データベース学会のみなさま
筑波大学の天笠です．お世話になっております．
JST CREST 「検証可能なデータエコシステム」では，DASFAA2024
国際会議に合わせて第1回シンポジウムを開催します．興味のある
方はぜひご参加ください．よろしくお願いいたします．
天笠俊之
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JST CREST 「検証可能なデータエコシステム」第1回シンポジウム
日時：2024年7月2日（火）13:00-17:50
場所：長良川国際会議場
参加費：無料
参加登録： https://forms.gle/RGQpa9t4nPzMf38T7
【概要】
Society5.0では，ビッグデータ・AI分析による問題解決が重要な役割を果た
します．その一方で，増え続けるデータとそれを処理するプログラム・機械学
習モデルは常に信頼できるとは限らず，様々な不均質性を含む多様なデータを
活用した信頼度向上，さらには，不具合・不正の原因特定およびその説明と，
不具合・不正なデータを取り除いた上でのデータ修復が求められます．
JST CREST S5基盤ソフト領域「検証可能なデータエコシステム」では，
Society5.0の情報基盤に求められる，検証可能なデータエコシステムに関する
研究開発および実証実験に取り組んでいます．本シンポジウムでは，データ
ベース分野の国際会議 DASFAA2024 https://www.dasfaa2024.org/ の会場をお
借りして，プロジェクトの概要と取り組みを紹介するとともに，Society5.0時
代の信頼できる情報システムについて意見交換を行います．
【プログラム】
13:00-13:20 開会のあいさつ・プロジェクト紹介
天笠俊之（筑波大学計算科学研究センター 教授・研究代表者）
13:20-14:20 基調講演「Visual Graph Search: Opportunities and Challenges」
Prof. Sourav S. Bhowmick (NTU, Singapore)
Abstract:
The data management community has proposed several graph query
languages for declarative formulation of graph queries. However,
can users really use these languages? Are these languages
wide-spread in the real world? In this talk, we argue that
majority of end users in the real world are reluctant to formulate
graph queries using these languages. Instead, it is significantly
more appealing for them to construct queries using visual query
interfaces (a.k.a gui). Specifically, we first discuss the need
for visual graph querying paradigm. Second, we present novel
opportunities and challenges in processing graph queries in a
visual environment. In this context, we present a novel framework
called Boomer that enables us to formulate a novel class of graph
queries visually and process them iteratively by leveraging the
latency of a gui during query formulation.
14:20-14:30 休憩
14:30-16:00 取り組み紹介(1) - システムアーキテクチャの検討・開発
1. 検証可能なデータエコシステムのためのメタデータ管理およびスマート農業実証
天笠G（筑波大学）
2. データエコシステムの高機能ストレージシステムの実現
宮崎G（東京工業大学）
3. 分散ストレージ上の高性能データ検証
小口G（お茶の水女子大学）
16:00-16:10 休憩
16:10-17:40 取り組み紹介(2) - 理論的基盤の構築と基礎技術の開発
4. 統合データモデルおよび検証処理の実現技術の開発
石川G（名古屋大学）
5. トランザクション履歴の修正・再実行によるデータベース修復・シミュレーションの実現
鬼塚G（大阪大学）
6. ヒューマンインザループによる開世界データ信頼性向上技術
森嶋G（筑波大学）
17:40-17:50 クロージング
研究代表者 天笠俊之（筑波大学）
主たる共同研究者 石川佳治（名古屋大学）
小口正人（お茶の水女子大学），鬼塚真（大阪大学）
宮崎純（東京工業大学），森嶋厚行（筑波大学）
日本データベース学会のみなさま
大阪成蹊大学 杉山と申します。
アジア-太平洋地域を中心とした情報検索に関する国際会議、SIGIR-AP 2024では、
7月5日を締め切りとして、workshop proposal を募集しております。
ACM のテンプレートで4ページ程度の内容で投稿可能です。
主な予定は、次のとおりです。
- Proposal submission: July 5, 2024
- Proposal acceptance notification: July 12, 2024
- Workshop day: December 12, 2024
以下、Call For Workshop Proposal の詳細です。
https://www.sigir-ap.org/sigir-ap-2024/call-for-workshop-proposals/
みなさまからの workshop proposal のご投稿を、お待ちしております。
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The annual SIGIR-AP conference is an annual ACM-sponsored international
forum that promotes and disseminates information retrieval research and
development within the Asia-Pacific region. The 2nd ACM SIGIR-AP conference
(SIGIR-AP 2024) will be held in Tokyo from the 9th to the 12th of December
2024.
SIGIR-AP 2024 workshops will provide a platform for presenting novel ideas
and emerging areas in IR, in a less formal and more focused way than the
conference itself. Researchers and practitioners from all areas of IR are
invited to submit workshop proposals for review.
Workshops will be on-site and in person. All workshops will require at
least one organizer to attend, as well as a (yet-to-be-determined) number
of participants.
[IMPORTANT DATES FOR WORKSHOP PROPOSALS]
Time zone: Anywhere On Earth (AOE)
- Proposal submission: July 5, 2024
- Proposal acceptance notification: July 12, 2024
- Individual workshop paper submission: October 3, 2024
- Tentative workshop overview camera ready: October 7, 2024
- Tentative workshop paper acceptance notification: October 18, 2024
- Workshop day: December 12, 2024
[TOPICS OF INTEREST]
Workshop topics typically match those identified in the SIGIR-AP 2024 call
for papers, but proposals concerned with other areas of IR are welcome. We
encourage prospective workshop organizers to submit proposals for highly
interactive workshops (half-day) focusing on either in-depth analysis or
broad-ranging approaches to information retrieval. The format of each
workshop is to be determined by the organizers. We expect workshops to
contain ample time for discussion and engagement of all participants – not
just those presenting papers. Workshops that foster collaboration,
discussion, group problem-solving and community building initiatives are
particularly encouraged. Workshops that only revolve around the
presentation of papers in a “mini conference” format are discouraged.
The organizers of approved workshops will be expected to define the
workshop’s focus, gather and review submissions, and decide upon the final
program content.
#Organizers (including co-organizers) are strongly encouraged to write an
article for the ACM SIGIR Forum summarizing the event. At least one
organizer is expected to attend the entire workshop.
[SUBMISSION GUIDELINES]
Workshop proposals, in no more than 4 pages, should include the following
information:
- Title
- Motivation for the workshop, its appropriateness for SIGIR, its
complementarity to the main SIGIR-AP 2024 conference topics, and why it
would be of interest to the IR community
- Theme and purpose of the workshop
- Planned activities and a tentative schedule of events (half-day: 90
minutes x 2)
- For each organizer, how likely they think it is that they can attend
onsite
- Special requirements and how critical they are to the success of the
workshop. Outline a contingency plan in case these requirements cannot be
met, such as potential last-minute organizers to ensure the workshop runs
onsite
- List of organizers with a short biographical sketch of each organizer,
describing relevant qualifications and experience
- Names of potential program committee (PC) members – if the workshop
requires a PC (any workshop involving written papers should have a PC)
- Selection process for participants and/or presenters
- Details of the expected target audience and how the workshop will be
advertised to reach them
- Related workshops (if applicable): if the workshop has been held
previously at SIGIR or another conference, the organizers should indicate
this and describe briefly past attendance and outcomes, and why another
workshop is needed
Workshop proposals should be prepared in the current ACM two-column
conference format. Suitable LaTeX, Word, and Overleaf templates are
available from the ACM Website (use the“sigconf”proceedings
template).Workshop proposals will be reviewed based on the quality of the
proposal, their complementarity to the main SIGIR-AP 2024 conference
topics, and the likelihood of attracting enough participants, as well as
the hosting capacity of the venue. The submissions will be reviewed by a
workshop selection committee, and final decisions will be made at the
SIGIR-AP Program Committee meeting.
Proposals should be submitted in PDF through the EasyChair system (workshop
track):
https://easychair.org/my/conference?conf=sigirap2024.
The organizers of accepted workshops will be invited to submit a
camera-ready summary of the workshop, to be included in the SIGIR-AP 2024
conference proceedings.
[Workshop Chairs]
- Kazunari Sugiyama, Osaka Seikei University, Japan
- Masaharu Yoshioka, Hokkaido University, Japan
[Contact]
For further information, please contact the SIGIR-AP 2024 Workshop
Co-chairs by email: sigirap-workshop2024(a)easychair.org
日本データベースの皆様
お世話になっております。東工大の曹です。
6月24日（月）15:30-17:00 にDuke UniversityのProf. Jian Pei
<https://sites.duke.edu/jianpei/>が東京工業大学で講演を行います。
Prof. Jian Peiはデータサイエンス分野で著名な研究者であり、
今回の講演テーマはData Marketに関連しています。
講演はZoomと現地のハイブリッド形式で行いますので、
皆様のご参加をお待ちしております。
また、興味のある学生さんがいらっしゃれば、
ぜひアナウンスをお願い致します。
Greetings. This is Yang Cao from the Department of CS, Tokyo Institute of
Technology.
On Monday, June 24th, Prof. Jian Pei from Duke University will be giving a
lecture at Tokyo Institute of Technology.
Prof. Jian Pei is a renowned researcher in the field of data science, and
the topic of this lecture will be related to Data Market.
The lecture will be held in a hybrid format, both on Zoom and in person. We
look forward to your participation.
If there are any students who might be interested, please feel free to
announce this event to them.
日時： 2024/6/24 15:30-17:00
場所: 東工大 大岡山キャンパス 西８号館7階 コレボレーションルーム
ZOOM: https://zoom.us/j/93705154649 Meeting ID: 937 0515 4649
Title:
Data and AI Markets: Grand Opportunities for Data and Model Sharing,
Discovery, and Integration
Abstract:
The markets for data and AI models are rapidly emerging and increasingly
significant in the realm and the practices of data science and artificial
intelligence. These markets are being studied from diverse perspectives,
such as e-commerce, economics, machine learning, and data management. This
talk aims to provide a brief interdisciplinary introduction to data and AI
model markets. Instead of concentrating only on the economics aspect, we
take a novel perspective and examine data and AI model markets as grand
opportunities to address the long-standing problem of data and model
sharing, discovery, and integration. We will motivate the importance of
data and model markets using practical examples, present the current
industry landscape of such markets, explore the modules and options of such
markets from multiple dimensions, including assets in the markets (e.g.,
data versus models), platforms, and participants. Furthermore, we will
summarize the latest advancements and examine the future directions of data
and AI model markets as mechanisms for enabling and facilitating sharing,
discovery, and integration.
Speaker’s Bio:
Jian Pei is the Arthur S. Pearse Distinguished Professor of Computer
Science at Duke University. He serves as the Chair of the Duke University
Department of Computer Science, Trinity College of Arts & Sciences, and
holds professorships in the Department of Biostatistics and Bioinformatics
at the School of Medicine and the Department of Electrical and Computer
Engineering at the Pratt School of Engineering.
Professor Pei is a Fellow of The Royal Society of Canada (FRSC), The
Canadian Academy of Engineering (CAE), ACM, and IEEE. He has made
significant contributions to the fields of data science, big data, data
mining, database systems, and enterprise data strategies. At Duke, he
teaches Data Science and has received a rating of 3.8 on Rate My Professor.
