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DTW 2019 : 2019 Data Teaching Workshop – 5th Workshop on Curricula and Teaching Methods in Cloud Computing, Big Data, and Data Science


When Sep 24, 2019 - Sep 27, 2019
Where San Diego
Submission Deadline Jun 15, 2019
Notification Due Jun 27, 2019
Final Version Due Jul 7, 2019
Categories    data science   big data   cloud computing   instructional methodologies

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 (, 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.
Important Dates
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: (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

Yuri Demchenko, University of Amsterdam, The Netherlands (y.demchenko

Steve Brewer, Southampton University, UK (S.Brewer

Program Committee

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

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