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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: 

"The Internet of Things (IoT)"

The Internet of Things (IoT) Table of Contents

  1. The Third Wave (Opening Statement) by Kemal Delic
  2. Discovery in the Internet of Things by Arkady Zaslavsky and Prem Prakash Jayaraman
  3. W3C Plans for Developing Standards for Open Markets of Services for the IoT  by Dave Raggett (October 2015)
  4. Standards for Tomorrow by Dejan Milojicic, Paul Nikolich, and Barry Leiba (November 2015)
  5. A Case for Interoperable IoT Sensor Data and Meta-data Formats by Milan Milenkovic (November 2015)
  6. Programmable IoT: On The role of APIs in IoT by Maja Vukovic (November 2015)
  7. Fog Computing Distributing Data and Intelligence for Resiliency and Scale Necessary for IoT by Charles Byers and Patrick Wetterwald (November 2015)
  8. Evolution and Disruption in Network Processing for The Internet of Things by Lorenzo di Gregorio (December 2015)
  9. The Importance of Cross-Layer Considerations in a Standardized WSN Protocol Stack Aiming for IoT by Bogdan Pavkovic, Marko Batic, and Nikola Tomasevic (December 2015)
  10. Using Redundancy to Detect Security Anomalies Toward IoT Security Attack Detectors by Mladen A. Vouk and Roopak Venkatakrishnan (January 2016)
  11. Ensuring Trust and Security in the Industrial IoT by Bernardo A. Huberman (January 2016)
  12. On Resilience of IoT Systems by Kemal Delic (February 2016)
  13. IoT in Energy Efficiency by Francois Jammes(February 2016)
  14. IoT: Promises, Perils, Perspectives (Closing Statement) by Kemal Delic (February 2016)

Previous Ubiquity Symposia:

"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
  • Big data: big data for social science research

    Academic studies exploiting novel data sources are scarce. Typically, data is generated by commercial businesses or government organizations with no mandate and little motivation to share their assets with academic partners---partial exceptions include social messaging data and some sources of open data. The mobilization of citizen sensors at a massive scale has allowed for the development of impressive infrastructures. However, data availability is driving applications---problems are prioritized because data is available rather than because they are inherently important or interesting. The U.K. is addressing this through investments by the Economic and Social Research Council in its Big Data Network. A group of Administrative Data Research Centres are tasked with improving access to data sets in central government, while a group of Business and Local Government Centres are tasked with improving access to commercial and regional sources. This initiative is described. It is illustrated by examples from health care, transport, and infrastructure. In all of these cases, the integration of data is a key consideration. For social science problems relevant to policy or academic studies, it is unlikely all the answers will be found in a single novel data source, but rather a combination of sources is required. Through such synthesis great leaps are possible by exploiting models that have been constructed and refined over extended periods of time e.g., microsimulation, spatial interaction models, agents, discrete choice, and input-output models. Although interesting and valuable new methods are appearing, any suggestion that a new box of magic tricks labeled "Big Data Analytics" that sits easily on top of massive new datasets can radically and instantly transform our long-term understanding of society is naïve and dangerous. Furthermore, the privacy and confidentiality of personal data is a great concern to both the individuals concerned and the data owners.