DTW 2019 : 2019 Data Teaching Workshop – 5th Workshop on Curricula and Teaching Methods in Cloud Computing, Big Data, and Data Science
Call For Papers
DTW2019 Data Teaching Workshop – 5th Workshop on Curricula and Teaching Methods in Cloud Computing, Big Data, and Data Science
as part of 15th eScience Conference (https://escience2019.sdsc.edu/), September 24 – 27, 2019, San Diego, California, USA
The emergence of Data Science technologies that combine Cloud Computing, Big Data and Data Analytics technologies as specialized fields in computing is motivating development of new teaching methods in course design to provide education in the techniques and technologies needed to extract knowledge from large datasets in virtualized environment. In current literature there is a lack of well-articulated learning resource for beginners that would integrate administrative, programing, and algorithm design aspects of related domains. We believe it is important to allow students, researchers, and professionals to understand cross-domain aspects of these challenges before they embark on further exploration of these fields.
The workshop will be organizationally sponsored by the EDISON Initiative supported by the partners of the EDISON project, which was funded by the European Community to coordinate Data Science curricula development in Europe and internationally.
We plan to accept a small number of high-quality contributions for presentation during the workshop. At the end of the workshop, a forum discussion is planned to debate on future directions of curricula and teaching methods in Data Science, Big Data, and Cloud Computing
More information on workshop website:
The workshop invites papers discussing topics related to teaching methods, platforms and best practices in the following areas applied to one of the fields (Cloud Computing, DevOps, Big Data, Data Science) or closely related to them:
novel or updated curricula reflecting continuously developing technologies;
novel or updated teaching methods, e.g. Bloom’s taxonomy for new types of Data Science and Big Data courses, flipped classroom, etc ;
review and presentation of novel teaching materials;
review of methodologies;
characterization of domain knowledge (Body of Knowledge);
adoption as a part of institutional strategies;
review and analysis of existing practices in the design, implementation, and evaluation;
multimedia and interactive components in residential and online education, educational platforms, MOOCs and others;
cooperation between universities/academia and industry in delivering advanced education and leadership programs;
implementation reports and lessons learnt;
future trends and issues.
Paper submission: 3 June 2019
Notification of acceptance: 17 June, 2019
Camera-ready version: 29 June 2019 (please check main eScience 2019 website)
Submissions are accepted on EasyChair:
https://easychair.org/conferences/?conf=dtw2019 (open since 1 May 2019)
Authors are invited to submit papers containing unpublished, original work (not under review elsewhere) of up to 6 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per IEEE 8.5 x 11 manuscript guidelines. It might be possible to purchase additional pages from conference organizers (see details on the conference website). Templates are available from:
Authors should submit a PDF file. Papers conforming to the above guidelines can be submitted through the workshop's EasyChair submission system. At least one author of each accepted submission must attend the workshop and all workshop participants must pay at least the CloudCom 2018 workshop registration fee.
All accepted papers will be published by the IEEE. All presented papers will be subject to peer review process.
Tomasz Wiktorski, University of Stavanger, Norway (tomasz.wiktorski @uis.no)
Yuri Demchenko, University of Amsterdam, The Netherlands (y.demchenko @uva.nl)
Steve Brewer, Southampton University, UK (S.Brewer @soton.ac.uk)
Thomas J. Hacker, Purdue University, USA
Gregory Rodgers, AMD Research, USA
Bikash Agrawal, DNV-GL, Norway
Chunming Rong, University of Stavanger, Norway
Martin Gilje Jaatun, SINTEF, Norway
Aleksandra Krolak, Lodz University of Technology, Poland
Wouter Los, University of Amsterdam, Netherlands
Andrea Manieri Engineering, Italy