Managing and processing large volumes of data, or “Big Data”, and gaining meaningful insights is a significant challenge facing the distributed computing community; as a consequence, many businesses are demanding large scale streaming data analytics. This has significant impact in a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing.

Despite considerable advancements on high performance, large storage, and high computation power, there are challenges in identifying, clustering, classifying, and interpreting of a large spectrum of information.

The purpose of this workshop is to provide a fertile ground for collaboration between research institutions and industries and in analytics, machine learning, and high performance computing.

Topics of interest are:
• High performance data analytics
• Machine and deep learning
• Data search and representation
• Architecture and system design
• Cloud-based big data solutions
• Software infrastructures

Submission Guidelines
Authors are invited to submit full papers to the workshop. Full papers must be submitted through the workshop submission site:
https://easychair.org/conferences/?conf=bigdaw17

Full papers should not exceed six double-column pages in ACM conference format. These limits include figures, tables, and references.
Accepted papers will be published in the workshop proceedings and in the ACM Digital Library (note that authors of these works retain their copyright rights to publish more complete versions later). As per ACM guidelines, at least one of the authors of accepted papers is required to register for the workshop.


Important Dates
Submission Deadline Extended: March 05, 2017
Decision Notification: March 30, 2017
Camera-Ready Copy: April 4, 2017


Workshop Committee

Roberta Piscitelli, EGI.eu, NL (organizer)
Giovanni Mariani, IBM Research, NL (organizer)

Sandro Fiore, Euro-Mediterranean Center on Climate Change, IT
Dimitra Gkorou, ASML, NL
Annalisa Riccardi, University of Strathclyde, UK
Mario Barbareschi, University of Naples Federico II, IT
Rik Jongerius, IBM Research, NL
Leandro Fiorin, IBM Research, NL
Mark Thompson, Leids Universitair Medisch Centrum, NL
Christian Pilato, University of Lugano, CH
Abhishek Mukherjee, Oramon Labs, NL
Emiliano Mancini, University of Amsterdam, NL