Dennis Gannon & Kristin Tolle, Microsoft Research
On April 29th and 30th, 2014 Microsoft Research hosted the eScience in the Cloud workshop. We had two days of great talks and discussion covering the critical themes that surround doing eScience in the cloud. Our goal was to explore the topics that were common to many disciplines. These included the general challenges of processing big data and machine learning, building collaborations and communities that can share resources, streaming data and its implications, the emerging academic discipline of data science, the challenges of building future massive, efficient data centers, and how to extract data from information. We were fortunate to have a great list of speaker from our academic community friends and inside Microsoft, including a great keynote from Raghu Ramakrishnan, one of Microsoft Technical Fellows and a very well-known data science researcher.
The audience consisted of about 70 local participants and several hundred remote participants who watched the live streaming. Of course because of time zone challenges, not everybody could watch the streaming at all times. Fortunately we were able to record the entire workshop from the streaming video and, for those of you that missed it, we can share it with you now. Below is the list of presentation and links to the videos for each session in the order that they appeared.
We feel that we are now entering into a time when cloud computing can truly making a difference for the way we do science. But we are just at the beginning.
Scale-Out Beyond Map-Reduce, Raghu Ramakrishnan, Microsoft Technical Fellow
Marty Humphrey and Roger Barga
Big Data and Machine Learning, Roger Barga, Microsoft
Experiences using Microsoft Azure to Analyze and Visualize Large-Scale Environmental Data Marty Humphrey, University of Virginia
Accelerating Data-Intensive Genomics Analysis in the Cloud, Wuchun Feng, Virginia Tech.
Kenji Takeda, Steven Roberts, Evelyne Viegas, Tanya Berger-Wolf, and Chaitan Baru
Collaborative Genomic Data Analyses in the Cloud Steven Roberts, University of Washington
CodaLab—Learn, Share and Collaborate, Evelyne Viegas, Microsoft Research
Ecological Information System, Tanya Berger-Wolf, University of Illinois Chicago
The EarthCube Cloud Commons Working Group, Chaitan Baru, San Diego Supercomputer Center
Jie Liu, Yung-Hsiang Lu, and John Krumm
Cloud-Offloaded GPS for Energy Efficient Localization Jie Liu, Microsoft Research
Cloud computing for analyzing many data streams, Yung-Hsiang Lu, Purdue University
What Can We Do with Your Location History? John Krumm, Microsoft Research
Dennis Gannon, Merce Crosas, Bill Howe, Gabriel Antoniu, and Alex Wade
Data Publishing and Data Analysis Tools on the Cloud, Merce Crosas, Harvard
Data Science Environment at the University of Washington eScience Institute, Bill Howe, University of Washington
Scalable Data-Intensive Processing for Science on Azure Clouds: A-Brain and Z-CloudFlow
Gabriel Antoniu, INRIA, France
Deploying a CKAN Data Repository in Azure, Alex Wade, Microsoft Research
Vani Mandava, Shahrokh Mortazavi, Geoffrey Fox, and Jeff Zhang
Moderator: Vani Mandava, Microsoft Research
Comparing Big Data and Simulation Applications and implications for software environments Geoffrey Fox, Indiana University
Extending the power of Excel with Power BI and Power MapDan Parish,
MicrosoftTools of the eScience trade (and also how to get them going on Windows!) Shahrokh Mortazavi, Microsoft
Windows Azure for Research and Beyond, Daron Green, Microsoft Research