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Symposia

A Ubiquity symposium is an organized debate around a proposition or point of view. It is a means to explore a complex issue from multiple perspectives. An early example of a symposium on teaching computer science appeared in Communications of the ACM (December 1989).

To organize a symposium, please read our guidelines.

 

New in Ubiquity Symposia: 

"Big Data"

Table of Contents

  1. Big Data, Digitization, and Social Change (Opening Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic
  2. Big Data and the Attention Economy by Bernardo A. Huberman
  3. Big Data for Social Science Research by Mark Birkin
  4. Technology and Business Challenges of Big Data in the Digital Economy by Dave Penkler
  5. High Performance Synthetic Information Environments: An integrating architecture in the age of pervasive data and computing By Christopher L. Barrett, Jeffery Johnson, and Madhav Marathe
  6. Developing an Open Source "Big Data" Cognitive Computing Platform by Michael Kowolenko and Mladen Vouk
  7. When Good Machine Learning Leads to Bad Cyber Security by Tegjyot Singh Sethi and Mehmed Kantardzic (May 2018)
  8. Corporate Security is a Big Data Problem by Louisa Saunier and Kemal Delic (May 2018)
  9. Big Data: Business, technology, education, and science by Jeffrey Johnson, Luca Tesei, Marco Piangerelli, Emanuela Merelli, Riccardo Paci, Nenad Stojanovic, Paulo Leitão, José Barbosa, and Marco Amador (June 2018)
  10. Big Data or Big Brother? That is the question now (Closing Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic (June 2018)

Previous Ubiquity Symposia:

"The Internet of Things"

"The Technological Singularity"

"MOOCs and Technology to Advance Learning and Learning Research"

"The Multicore Transformation"

"The Science in Computer Science"

"Evolutionary Computation and the Processes of Life"

"What is Computation"

2018
  • When Good Machine Learning Leads to Bad Security: Big Data (Ubiquity symposium)

    While machine learning has proven to be promising in several application domains, our understanding of its behavior and limitations is still in its nascent stages. One such domain is that of cybersecurity, where machine learning models are replacing traditional rule based systems, owing to their ability to generalize and deal with large scale attacks which are not seen before. However, the naive transfer of machine learning principles to the domain of security needs to be taken with caution. Machine learning was not designed with security in mind and as such is prone to adversarial manipulation and reverse engineering. While most data based learning models rely on a static assumption of the world, the security landscape is one that is especially dynamic, with an ongoing never ending arms race between the system designer and the attackers. Any solution designed for such a domain needs to take into account an active adversary and needs to evolve over time, in the face of emerging threats. We term this as the "Dynamic Adversarial Mining" problem, and this paper provides motivation and foundation for this new interdisciplinary area of research, at the crossroads of machine learning, cybersecurity, and streaming data mining.

2017
  • Big Data and the Attention Economy: Big Data (Ubiquity symposium)

    While attention has always been prized above money, few people have had the means to attract it to themselves. But the new digital economy has provided everyone with a loudspeaker; thus efforts at getting noticed have rapidly escalated in global society. The attention economy focuses on the mechanisms that mediate the allocation of this scarce entity. Social networks and big data play a role in determining what is noticed and acted upon.

2016 2015
  • The Importance of Cross-layer Considerations in a Standardized WSN Protocol Stack Aiming for IoT: The Internet of Things (Ubiquity symposium)

    The Internet of Things (IoT) envisages expanding the current Internet with a huge number of intelligent communicating devices. Wireless sensor networks (WSNs) integrating IoT will rely on a set of the open standards striving to offer scalability and reliability in a variety of operating scenarios and conditions. Standardized protocols will tackle some of the major WSN challenges like energy efficiency, intrinsic impairments of low-power wireless medium, and self-organization. After more then a decade of tremendous standardization efforts, we can finally witness an integral IP-based WSN standardized protocol stack for IoT. Nevertheless, the current state of standards has redundancy issues and can benefit from further improvements. We would like to highlight some of the cross-layer aspects that need to be considered to bring further improvements to the standardized WSN protocol stack for the IoT.

2014 2013 2012 2011
  • Ubiquity symposium: What have we said about computation?: closing statement

    The "computation" symposium presents the reflections of thinkers from many sectors of computing on the fundamental question in the background of everything we do as computing professionals. While many of us have too many immediate tasks to allow us time for our own deep reflection, we do appreciate when others have done this for us. Peter Freeman points out, by analogy, that as citizens of democracies we do not spend a lot of time reflecting on the question, "What is a democracy," but from time to time we find it helpful to see what philosophers and political scientists are saying about the context in which we act as citizens.

  • Ubiquity symposium: Biological Computation
    In this thirteenth piece to the Ubiquity symposium discussing What is computation? Melanie Mitchell discusses the idea that biological computation is a process that occurs in nature, not merely in ...
  • Ubiquity symposium: Natural Computation
    In this twelfth piece to the Ubiquity symposium discussing What is computation? Erol Gelenbe reviews computation in natural systems, focusing mainly on biology and citing examples of the computation that ...
  • Ubiquity symposium: Computation, Uncertainty and Risk
    In this eleventh piece to the Ubiquity symposium discussing What is computation? Jeffrey P. Buzen develops a new computational model for representing computations that arise when deterministic algorithms process workloads ...
2010