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@gmail.com --------------------------------------------------------------------------- -- Atsuyuki Morishima <morishima-office@ml.cc.tsukuba.ac.jp> (CAUTION: I usually miss emails sent to mori@slis.tsukuba.ac.jp.) (注意：mori@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 <iframe width="1024" height="576" src="https://www.youtube.com/embed/T7YB96faCxI" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>