[dbjapan] 10月〆切 IEEE WS on ヒューマンインザループとFuture of Work

[Atsuyuki Morishima <mori [at] slis.tsukuba.ac.jp>]

日本データベース学会の皆様

筑波大学の森嶋です．第6回HMDataへのご投稿のご案内です．
Human-in-the-loop & Data に関する幅広いトピックで投稿できます
ので何卒よろしくお願いいたします．

ポイント：
- Ming Yin (Purdue University) がKeynote
- Human-in-the-loop & Data に関する幅広いスコープ
- IEEE Xplore, DBLPに掲載されます．
- Work-in-Progress Paper もOK

以上よろしくお願い申し上げます．10月1日〆切ですが
おそらく若干伸びます．

森嶋厚行

======================================
The Sixth IEEE Workshop on
Human-in-the-Loop Methods and Future of Work
in BigData (HMData 2022) co-located with IEEE Bigdata 2022 (online)
Dec.17th or 20th (Planned)
https://humanmachinedata.org
======================================
Overview

HMData workshop, which originally started as the "Human-Machine
collaboration in BigData" workshop, will investigate the
opportunities and challenges in human machine collaboration in work
with bigdata, which are described by two terms: Human-in-the-Loop
Methods and Future of Work. Human-in-the-Loop is a term focusing on
the employer's viewpoint while Future of Work focuses more on
worker's viewpoint, in both of which the division of labor among
humans and machines is a key issue. This area is likely to be
heavily  AI driven, and we intend to invite papers covering the
following aspects, (a) Capturing human capabilities through
intelligent models and how to adapt them through changing perceptions,
needs, and skills. (2) High level tools that provide the ability for
all stakeholders in the new ecosystem, including regulators for
policies and AI workers, to specify their requirements. (3) system
design and engineering of job platforms for collection, storage,
retrieval, and analysis of data deluge about workers, jobs, and
their activities. (4) Benchmarking and the development of appropriate
metrics to measure system performance as well as human aspects,
such as satisfaction, capital advancement, and equity.

We welcome any interesting ideas and results on any relevant
topics, but this workshop encourages submitting papers the
results of which have been or will be implemented as platforms,
tools and libraries. This year, we plan to have a thematic session
on improving the interoperability of tools on Human-in-the-loop
Methods and Future-of-Work. We also solicit practitioner papers
as well as research papers, in order to facilitate discussion
among researchers have solutions and practitioners who know
problems. All papers accepted for the workshop will be included
in the Workshop Proceedings published by the IEEE Computer
Society Press, made available at the Conference.

----------------------------------------------------------------------
Topics

This workshop covers a wide range of topics of human-machine
collaboration in work with bigdata. Keywords include: crowdsourcing,
collaborative recommendation, crowdsensing, workflow model for
humans and machines, incentives, human-assisted bigdata analysis,
bigdata-human interaction, human-machine collaboration in real-world
applications (such as natural disaster response, education, and citizen
science), and ELSI in Human-in-the-  Loop systems and Future of Work.

We expect submissions to address a  Variety of research issues including:
- capturing human characteristics and capabilities,
- stakeholder requirement specification,
- social processes around the human-in-the-loop systems,
- platforms and ecosystems,
- computation capabilities, and
- benchmarks and metrics for human-in-the-loop systems and Future of Work

-----------------------------------------------------------------------
Keynote

Ming  Yin (Purdue University)

Bio: Ming Yin is an Assistant Professor in the Department of Computer
Science, Purdue University. Her research broadly connects to the
fields of human-computer interaction, applied artificial intelligence
and machine learning, computational social science, and behavioral
sciences. She uses both experimental and computational approaches to
examine how to better utilize the wisdom of crowd to enhance machine
intelligence (i.e., crowdsourcing and social computing), and how to
better design intelligent systems that people can understand, trust
and engage with effectively (i.e., human-AI interaction).
Prior to Purdue, She spent a year at Microsoft Research New York City
as a postdoctoral researcher in the Computational Social Science group.
She completed her Ph.D. in Computer Science at Harvard University, and
received her bachelor degree from Tsinghua University, Beijing, China.

-------------------------------------------------------------------------
Important Dates (Tentative)
Oct 1 (Sat), 2022: Due date for workshop papers submission
Nov 1 (Tue), 2022: Notification of paper acceptance to authors
Nov 20 (Sun), 2022: Camera-ready of accepted papers
Dec 17-20 (Sat-Tue), 2022: Workshops
------------------------------------------------------------------------
Submission
All submissions must be submitted electronically through CyberChair.
Please prefix your submission category such as [Research Paper] to
the Title of Paper field in the submission page.
For example, if you would like to submit a project-in-progress paper
"Crowd-centric Approach to Digital Archive Maintenance," you have
to put "[project-in-progress paper] Crowd-centric Approach to Digital
Archive Maintenance" into the Title of Paper field.

All papers accepted for the workshop will be included in the Workshop
Proceedings published by the IEEE Computer Society Press, made
available at the Conference.
--------------------------------------------------------------------------
Submission Categories

Research Papers (*) (long presentation): They report significant and
original results relevant to the scope of this workshop. We solicit
innovative or thought-provoking work but they do not necessarily
have to reach the level of completion. The expected length is between
4 and 6 pages. The maximum length is 10 pages, though the paper
should be commensurate with the size of the contribution.

Practitioner papers (*)(long presentation): They present interesting
problems that require human-in-the-loop solutions in a variety of
application domains, or present the interesting results of applying
existing human-in-the-loop solutions to their domains. The expected
length is between 4 and 6 pages. The maximum length is 10 pages, though
the paper should be commensurate with the size of the contribution.

Project-in-progress papers (short presentation): They present the goals,
challenges, and preliminary results of research or real-world projects
in progress. The maximum length is 3 pages.

(*) Some of the papers submitted to the research or practitioner paper
categories may be accepted as project-in-progress papers and allotted
to short presentation slots.

Format
Papers should be formatted to IEEE Computer Society Proceedings
Manuscript Formatting Guidelines in the IEEE Bigdata 2022 CFP page
-------------------------------------------------------------------------
Organization

Chairs
Senjuti Basu Roy (NJIT)
Alex Quinn (Purdue University)
Atsuyuki Morihsima (Univesity of Tsukuba)

Program Committee
TBA

Contact
hmdata.chairs [at] gmail.com
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-- 
Atsuyuki Morishima <morishima-office [at] ml.cc.tsukuba.ac.jp>
(CAUTION: I usually miss emails sent to mori [at] slis.tsukuba.ac.jp.)
(注意：mori [at] slis.tsukuba.ac.jp宛のメールは読み落としが多いです)
Faculty of Library, Information and Media Science
Associate Dean, Graduate School of Library, Information and Media Studies
Center for Artificial Intelligence Research, University of Tsukuba
Graduate School of Comprehensive Human Sciences
https://fusioncomplab.org/people/atsuyuki/
JST CREST CyborgCrowd Project
http://crowd4u.org/ja/projects/crest-cyborgcrowd
The Crowd4U Initiative
http://crowd4u.org
ISeee Project
http://crowd4u.org/projects/iseee
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