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Showing posts with the label federal summit

2016-01-28: January 2016 Federal Cloud Computing Summit

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As I have mentioned previously , I am the MITRE chair of the Federal Cloud Computing summit . The Summits are designed to allow representatives from government agencies that would not necessarily cross paths to collaborate and learn from one another about the best practices, challenges, and recommendations for adopting emerging technologies in the federal government. The MITRE- ATARC Collaboration Symposium is a working group-style session in which academics, representatives from industry, government, and FFRDC representatives discuss potential solutions and ways-forward for the top challenges of emerging technology adoption in government. MITRE helps select the challenge areas by polling government practitioners on their top challenges, and the participants break into groups to discuss each challenge area. The Collaboration Symposium allows this heterogeneous group of cloud practitioners to collaborate across all levels, from the end users to researchers to practitioners to po

2015-01-15: The Winter 2015 Federal Cloud Computing Summit

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On January 14th-15th, I attended the  Federal Cloud Computing Summit  in Washington, D.C., a recurring event in which I have participated in the past. In my continuing role as the MITRE-ATARC Collaboration Session lead, I assisted the host organization, the  Advanced Technology And Research Center  (ATARC) in organizing and run the MITRE-ATARC Collaboration Sessions. The summit is designed to allow Government representatives to meeting and collaborate with industry, academic, and other Government cloud computing practitioners on the current challenges in cloud computing. The collaboration sessions continue to be highly valued within the government and industry. The Winter 2015 Summit had over 400 government or academic registrants and more than 100 industry registrants. The  whitepaper summarizing the Summer 2014 collaboration sessions  is now available. A discussion of  FedRAMP  and the future of the policies was held in a Government-only session at 11:00 before the collabora

2014-07-10: Federal Cloud Computing Summit

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As mention in my previous post , I attended the Federal Cloud Computing Summit on July 8th and 9th at the Ronald Reagan Building in Washington, D.C. I helped the host organization, the Advanced Technology And Research Center (ATARC) organize and run the MITRE-ATARC Collaboration Sessions that kick off the event on July 8th. The summit is designed to allow Government representatives to meeting and collaborate with industry, academic, and other Government cloud computing practitioners on the current challenges in cloud computing. A FedRAMP  primer was held at 10:00 AM on July 8th in a Government-only session. At its conclusion, we began the MITRE-ATARC Collaboration Sessions that focused on Cloud Computing in Austere Environments, Cloud Computing for the Mobile Worker, Security as a Service, and the Impact of Cloud Computing on the Enterprise. Because participants are protected by Chathan House Rule , I cannot elaborate on the Government representation or discussions in the col

2014-06-23: Federal Big Data Summit

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On June 19th and 20th, I attended the Federal Big Data Summit  at the Ronald Reagan Building in the heart of Washington, D.C. The summit is hosted by the Advanced Technology Academic Research Center (ATARC) . I participated as an employee of the  MITRE Corporation  -- we help ATARC organize a series of collaboration sessions that are designed to help identify and make recommendations for solutions to big challenges in the federal government. I lead a collaboration session between government, industry, and academic representatives on Big Data Analytics and Applications. The goal of the session was to facilitate discussions between the participants regarding the application of big data in the government and preparing for the continued growth in importance of big data. The targeted topics included access to data in disconnected environments, interoperability between data providers, parallel processing (e.g., MapReduce ), and moving from data to decision in an optimal fashion. Due