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, Digitization, and Social Change (Opening Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic
- Big Data and the Attention Economy by Bernardo A. Huberman
- Big Data for Social Science Research by Mark Birkin
- Technology and Business Challenges of Big Data in the Digital Economy by Dave Penkler
- 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 (February 2018)
- Developing an Open Source "Big Data" Cognitive Computing Platform by Michael Kowolenko and Mladen Vouk (February 2018)
- When Good Machine Learning Leads to Bad Cyber Security by Tegjyot Singh Sethi and Mehmed Kantardzic (March 2018)
- Corporate Security is a Big Data Problem by Louisa Saunier and Kemal Delic (March 2018)
- 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 (April 2018)
- Big Data or Big Brother? That is the question now (Closing Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic (April 2018)
Previous Ubiquity Symposia:
Big data: developing an open source "big data" cognitive computing platform
by Michael Kowolenko, Mladen A. Vouk
The ability to leverage diverse data types requires a robust and dynamic approach to systems design. The needs of a data scientist are as varied as the questions being explored. Compute systems have focused on the management and analysis of structured data as the driving force of analytics in business. As open source platforms have evolved, the ability to apply compute to unstructured information has exposed an array of platforms and tools available to the business and technical community. We have developed a platform that meets the needs of the analytics user requirements of both structured and unstructured data. This analytics workbench is based on acquisition, transformation, and analysis using open source tools such as Nutch, Tika, Elastic, Python, PostgreSQL, and Django to implement a cognitive compute environment that can handle widely diverse data, and can leverage the ever-expanding capabilities of infrastructure in order to provide intelligence augmentation.
High Performance Synthetic Information Environments
An integrating architecture in the age of pervasive data and computing: Big Data (Ubiquity symposium)
by Christopher L. Barrett, Jeffrey Johnson, Madhav Marathe
March 2018The complexities of social and technological policy domains, such as the economy, the environment, and public health, present challenges that require a new approach to modeling and decision-making. ...
Technology and Business Challenges of Big Data in the Digital Economy: Big Data (Ubiquity symposium)
by Dave Penkler
January 2018The early digital economy during the dot-com days of internet commerce successfully faced its first big data challenges of click-stream analysis with map-reduce technology. Since then the digital economy has ...
Big Data for Social Science Research: Big Data (Ubiquity symposium)
by Mark Birkin
January 2018Academic 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 ...