svn commit: r1655703 - /incubator/taverna/site/trunk/content/introduction/what-is-in-silico-experimentation.md

[br...@apache.org]

Author: brenninc
Date: Thu Jan 29 15:24:41 2015
New Revision: 1655703

URL: http://svn.apache.org/r1655703
Log:
Added what-is-in-silico-experimentation

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    incubator/taverna/site/trunk/content/introduction/what-is-in-silico-experimentation.md

Added: incubator/taverna/site/trunk/content/introduction/what-is-in-silico-experimentation.md
URL: http://svn.apache.org/viewvc/incubator/taverna/site/trunk/content/introduction/what-is-in-silico-experimentation.md?rev=1655703&view=auto
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+Title:     What is ‘in silico’ experimentation?
+Notice:    Licensed to the Apache Software Foundation (ASF) under one
+           or more contributor license agreements.  See the NOTICE file
+           distributed with this work for additional information
+           regarding copyright ownership.  The ASF licenses this file
+           to you under the Apache License, Version 2.0 (the
+           "License"); you may not use this file except in compliance
+           with the License.  You may obtain a copy of the License at
+           .
+             http://www.apache.org/licenses/LICENSE-2.0
+           .
+           Unless required by applicable law or agreed to in writing,
+           software distributed under the License is distributed on an
+           "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+           KIND, either express or implied.  See the License for the
+           specific language governing permissions and limitations
+           under the License.
+
+The rapid increase in the processing power of computers in the past few decades has enabled the emergence 
+of in silico experimentation across many domains, where research is conducted via computer simulations 
+with models closely reflecting the real world.
+
+In silico experimentation provides researchers with a number of significant advantages:
+
+ -   higher precision and better quality of experimental data;
+ -   better support for data-intensive research and access to vast sets of
+ -   experimental data generated by scientific communities;
+ -   more accurate simulations through more sophisticated models;
+ -   faster individual experiments;
+ -   higher work productivity.
+
+In silico experimentation nowadays suffers from an increased complexity of setting up, 
+   maintaining and making changes to the experimental simulation systems. 
+Such systems often involve a range of heterogeneous components: modules for preparation, 
+   extraction and conversion of data, program codes that perform experiment-related computations, 
+   and scripts that join the other components and make them work as a coherent system which is capable 
+   of displaying desired behaviour. 
+Interaction with such a system involves a great amount of purely computing aspects.
+
+A regular researcher (for example, a biologist or chemist) may not have enough background knowledge to 
+   configure and tune the system to his needs. 
+Insufficient computing background – which is natural for scientists as it is not the focus of their work – 
+  acts as a strong barrier in adoption and distribution of scientific applications, 
+  thus leaving these applications inaccessible for the majority of researchers.
+
+[Scientific workflows][1] offer a solution to this problem. 
+They provide an easy-to-use declarative way of specifying the tasks that have to be performed during 
+   a specific in silico experiment, whereas the technical details of workflow execution are now delegated 
+   to a [Workflow Management System][2].
+
+
+  [1]: introduction/why-use-workflows.html
+  [2]: /introduction/what-is-a-workflow-management-system.html
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