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We are delighted to welcome Sandra back, some of you may remember her previous visits from the University of Tübingen, where she recently defended her PhD. We all congratulate her on that well deserved success. Her email address remains, firstname.lastname@example.org. She can be found in room IF5.22. We will be working together on a graphical editor for DISPEL that also forms a proof-of-concept for a really versatile web-based generic workflow editor.
David Rodrìguez now has a research post in the Brain Research Imaging Centre, http://www.bric.ed.ac.uk, led by Professor Joanna Wardlaw, http://www.ccbs.ed.ac.uk/members/profile.asp?staffID=11. This is a modest change, as he will continue to work closely with the DIR group and drop into Informatics regularly; it is an inversion of his previous modus operandi of the last three years, where he was based in Informatics and visited BRIC at least two days per week.
An overview of the achievements of the architecture and tools work package in VERCE over the last 12 months:
* the mapping of the major CPU-intensive and data-intensive use cases to he one framework,
* the provision of an integrating framework supporting both discussion and implementation,
* the support of two demonstrators: from CPU & data-intensive use cases.
The plans for the next 12 months:
* scale up and reliability
* completion of the registry and other components needed for a quality beta test of the VERCE platform
Date and time:
Thursday, 25 April, 2013 - 11:00
Institut de Physique du Globe de Paris, Paris, France
Drs Andre Luckow and Shantenu Jha from Rutgers University
This will be a talk in two parts: In the first part, we will motivate via a series of applications the concept of a scalable and general-purpose Pilot-Job. We will discuss the P* Model of Pilot-Jobs and present BigJob a SAGA-based Pilot-Job. In the second part of the talk, we focus on extension of the Pilot-Job concept to the challenge of "Big Data". Science that involves and depends upon large amounts of data, also requires overcoming various challenges, including managing large-scale data distribution and co-placement/scheduling with computing resources.
eBird is a citizen-science project that takes advantage of the human observational capacity to identify birds to species, and uses these observations to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs a global network of observers who have submitted more than 100 million observations of birds, making it one of the largest biodiversity data sources in existence. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human