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A single notebook for the enterprise
11 February 2009
Trevor Heritage, president, Symyx Software
February/March 2009
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Driven by science
11 February 2009
Professor Marek Niezgódka, Director of the ICM Centre at the University of Warsaw, explains why the centre heads the Green Top500 list and concentrates on open systems
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Weathering well
11 February 2009
Gemma Church finds out how scientists are using HPC to predict climate and weather more accurately and efficiently
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A supercomputer chip for every man
11 February 2009
While GPUs (graphics processing units) were initially designed to accelerate video and gaming, vendors of science and engineering software are using them to accelerate their code. Paul Schreier looks at the benefits for today and tomorrow
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Illuminating optics
11 February 2009
Paul Schreier reviews a sample of the applications and breakthrough products that advanced optics software have made possible
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Criminal investigations
11 February 2009
The increase in automation in forensic science in the last few years has led to a requirement for data management systems. Greg Blackman looks at the importance of LIMS in forensic laboratories
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The human touch
11 February 2009
Computing applied to the earth sciences will save human lives, according to Felix Grant
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Finding sense in finance
11 February 2009
Dietmar Maringer, professor of computational management sciences, University of Basel
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Building a Smart Laboratory 2018 highlights the importance of adopting smart laboratory technology, as well as pointing out the challenges and pitfalls of the process
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Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory
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This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.
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This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value
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This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment