Summary Development of workflow and data management systems are challenging because of the need to provide a service for users with varying degrees of expertise from novices to experts with more knowledge than the developers. We have received feedback from users and developers on the functionality and usability of the Swiss Grid Proteomics Portal, now called iPortal, during its first year of operation. Monitoring and interaction with the production system under heavy use have provided further information on how to improve efficiency and stability. In a second, highly upgraded version of iPortal, we have introduced several new concepts based on this feedback. In this paper, we detail the requirements and the improvements we have made, and also give an outlook on future directions. Copyright © 2014 John Wiley & Sons, Ltd.

The development process in large international projects with multiple partners and different lines of management is not only technically challenging; it is also an organizational and a communication issue. In this paper we summarize the experience in two large European Grid projects, describe the lessons learned, some of the measures taken and finally we give recommendations on what to consider in future large middleware development projects.

Modern biology has become a science of information, analysis and prediction, coalescing into computational biology -- a single discipline at the crossroads of life sciences, informatics, and mathematics. New developments in information and communications technology as well as high-performance computing enable researchers to address new demanding scientific problems which seemed far out of reach only a few years ago. The computational requirements of most applications in computational biology differ significantly from the requirements of other users of highthroughput computing such as high energy physics. To address these needs, the SwissBioGrid initiative, a collaboration among several partner institutions with a broad spectrum of expertise, was started over a year ago. In this paper, we report on its current status and achievements as well as the lessons learned which are of interest to the wider e-Science and Grid communities.

In wide area computing systems, it is often desirable to create remote read-only copies (replicas) of files. Replication can be used to reduce access latency, improve data locality, and/or increase robustness, scalability and performance for distributed applications. We define a replica location service (RLS) as a system that maintains and provides access to information about the physical locations of copies. An RLS typically functions as one component of a data grid architecture. This paper makes the following contributions. First, we characterize RLS requirements. Next, we describe a parameterized architectural framework, which we name Giggle (for GIGa-scale Global Location Engine), within which a wide range of RLSs can be defined. We define several concrete instantiations of this framework with different performance characteristics. Finally, we present initial performance results for an RLS prototype, demonstrating that RLS systems can be constructed that meet performance goals.

The SkyServer provides Internet access to the public Sloan Digital Sky Survey (SDSS) data for both astronomers and for science education. This paper describes the SkyServer goals and architecture. It also describes our experience operating the SkyServer on the Internet. The SDSS data is public and well-documented so it makes a good test platform for research on database algorithms and performance.

The next-generation astronomy digital archives will cover most of the sky at fine resolution in many wavelengths, from X-rays, through ultraviolet, optical, and infrared. The archives will be stored at diverse geographical locations. One of the first of these projects, the Sloan Digital Sky Survey (SDSS) is creating a 5-wavelength catalog over 10,000 square degrees of the sky (see http://www.sdss.org/). The 200 million objects in the multi-terabyte database will have mostly numerical attributes in a 100+ dimensional space. Points in this space have highly correlated distributions.