{"id":573,"date":"2014-04-01T13:30:00","date_gmt":"2014-04-01T13:30:00","guid":{"rendered":"https:\/\/blogs.msdn.microsoft.com\/msr_er\/2014\/04\/01\/getting-back-to-first-principles-with-escience-in-the-cloud-workshop\/"},"modified":"2016-07-20T07:30:20","modified_gmt":"2016-07-20T14:30:20","slug":"getting-back-to-first-principles-with-escience-in-the-cloud-workshop","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/getting-back-to-first-principles-with-escience-in-the-cloud-workshop\/","title":{"rendered":"Getting back to first principles with eScience in the Cloud workshop"},"content":{"rendered":"

As I prepare for the upcoming eScience in the Cloud workshop (opens in new tab)<\/span><\/a>, I keeping coming back to what might sound like an obvious statement—even in these times when we’re trying to tackle hugely complex issues, like understanding climate change, and<\/em> we are coping with heterogeneous data in volumes not previously encountered: as with life, science always finds a way.<\/strong> Okay, I’m paraphrasing from Jurassic Park<\/em>, but you take my meaning.<\/span><\/p>\n

Facing these complex issues will involve working together—multiple research disciplines collaborating across multiple institutions, across multiple sectors of business, nonprofit, and government. A tall order? Certainly—but, with cooperation and communication, one that is tractable (notice I did not say easy<\/em>). I hope to see that conversation continue at this workshop.<\/span><\/p>\n

\"Further<\/p>\n

Yes, we are coping with massive data sets and have the means to collect and share them. Processing big data takes massive compute power; fortunately, compute power grows and becomes increasingly accessible every day. Visualizing data for exploration is critical—and never have I seen more tools to visualize and explore data than of late.<\/span><\/p>\n

The reason I call this blog “Getting back to first principles” is that many of the topics we will discuss at the eScience in the Cloud 2014 workshop were topics also discussed at Microsoft SciData 2004, our original eScience event, held some 10 years ago.<\/span><\/p>\n

Sure, the stakes and the availability of tools and compute resources seem higher (don’t they always?), yet the topics and goals are much the same: how we can use technology (in this case, the cloud) to expedite scientific discoveries. This is why, when my co-chair and colleague, Dennis Gannon (opens in new tab)<\/span><\/a> (formerly an academic attendee) pulled the event together, he and I reviewed feedback from previous eScience events and focused on answering these fundamental questions: how is Microsoft going to help? and what resources can we make available?<\/span><\/p>\n

Like SciData 2004, the upcoming event will feature not only academics discussing their solutions to compute problems in science, but also Microsoft researchers from a variety of disciplines talking about how you can use their tools to reach your objectives. Even the product teams are becoming involved. They will demonstrate how some of their new offerings—many freely available—can help researchers achieve their goals.<\/span><\/p>\n

I hope you will join us April 29–30, at the Microsoft Research Lab in Redmond, Washington, to find out how to further your research in the cloud-computing age. Learn more about the event and register (opens in new tab)<\/span><\/a>.<\/span><\/p>\n

If you can arrive a day earlier, we’re holding a one-day training event (opens in new tab)<\/span><\/a> that teaches how to use Windows Azure, Microsoft’s cloud-computing platform, for research. This April 28 event is part of the Windows Azure for Research program (opens in new tab)<\/span><\/a>.<\/span><\/p>\n

—<\/em>Kristin Tolle<\/em> (opens in new tab)<\/span><\/a>, Director of Environmental Science Infrastructure Development, Microsoft Research<\/em> Connections<\/em><\/span><\/p>\n

Learn more<\/strong><\/span><\/p>\n