research

For November's User of the Month, I’m happy to announce that we have selected Jin-Ho Yoon from Pacific Northwest National Laboratory.

For October's User of the Month, I’m happy to announce that we have selected Gary Bates from the National Oceanic and Atmospheric Administration (NOAA).

When people hear about Globus Online they probably think of simplified online file transfer using a GUI. And while this is certainly true, what some people don’t realize is that, in addition to the nifty Web 2.0 interface, Globus Online also provides a powerful API developers can use to integrate Globus Online into their own applications, to localize the transfer experience.

Natural Language Processing (NLP) has the potential to dramatically influence the way in which clinical care and medical research is conducted. Pilot studies have shown that NLP engines, such as MedLEE and MetaMap, and the use of community-defined medical ontologies like the Unified Medical Language System (UMLS), can help to more accurately identify disease risks and environmental factors in patient clinical narratives. In addition to helping improve disease diagnosis, NLP can help automate the analysis of patient narratives over extended visits and across a wide sampling of subjects.

Last month we launched a “User of the Month” program to draw attention to particularly impressive, innovative and/or widely applicable usage scenarios that the entire user community should know about. For our 2nd User of the Month, I’m happy to announce that we have selected Steven Gottlieb from Indiana University.

I get a kick out of seeing "ordinary" information technologies make new kinds of science possible. For example, the ability to move and share digital data is a pretty mundane topic in computer science circles. The mass market entertainment industry (think: iTunes, Netflix) has even brought streaming data and multi-megabyte files into our living rooms--for fun! Despite this dramatic adoption and transformation in some industries, there are still plenty of areas where the effects are being felt for the first time.

I think I can speak for most biologists when I say I never thought I would be worrying about file transfer.  Compute power, yes.  Storage space, maybe.  But file transfer?  Never. Unlike some other scientific disciplines, biology is not a traditionally ‘big data’ science.  Generally, biologists produce data on the scale suited to e-mail attachments.  However, seemingly overnight, biology has been propelled into the ranks of the big data sciences.  Now a biologist can easily find herself confronted with terabytes of data.  Why the change?  The answer lies in the recent quantum leaps in DNA sequencing technology.

We are very pleased to see so many of our users utilizing Globus Online to support their scientific research -- this week I heard one user had moved 6TB of data over the course of 2 days. Other users would benefit from hearing more of these stories, to see what your colleagues are achieving and to give you ideas for your own work. So, we've decided to pick a User of the Month to draw attention to particularly impressive, innovative and/or widely applicable usage scenarios that the entire user community should know about. For our inaugural selection, I'm happy to announce May's User of the Month is NERSC (National Energy Research Scientific Computing Center).

As I pondered what tone to set for this blog, I tried to put myself in the shoes of the professional researcher. While I’ve lived that life, the everyday life of the dedicated, full-time researcher today has changed (and is changing) beyond what I’ve experienced, and I feel for you all out there who are challenged day-in, day-out with getting your work done in a rapidly changing world. For many researchers today, it’s all about wrangling massive data using faster and faster computers, while also struggling to keep ahead of the crowd by forging and sustaining ever-more-ambitious interdisciplinary collaborations. Those of you who have access to the right tools for these tasks are in the minority: Sure, big science projects have capabilities for getting and working with the data they need. But the average hardworking independent researcher or smaller lab does not. So the challenge (and opportunity) is to make these capabilities accessible not just to a few “big science” projects but to every researcher everywhere.