with the aim of guaranteeing the future availability of information. For example there are many different kinds of databases that use the \'science commons\' license, like the major protein database called the neurocommons and the hapmap^e^. The main aim of these this type of open licensing is to avoid that other intellectual property claims impede the access to the data by other users and to facilitate this usage (see Gitter [@CR37]).

The availability of the information is integral to the interaction of researchers with a wide range of datasets being used in the different sub-disciplines of the life sciences. This includes many examples of open source projects with users around the world like the the bio-versions of programming languages like are bio- java, bio-perl, bio-spice, bio-harvester and bio-lisp. Each of these has its own voluntary or public science support communities like the Open Bioinformatics Foundation. Elsewhere there are numerous projects in bio-informatics that aim for a wide range of open source software tools for the analysis of data. For example there is Bio-SPICE a software tool set that is specially designed for research into the modeling and simulation of \'spatio-temporal processes in living cells'. Its website describes Bio-SPICE by writing: "Bio-SPICE, an open source framework and software tool-set for Systems Biology"^f^.

Finally, these programs illustrate the significance of the ability to rewrite software programs for asking novel biological questions, which is necessary in many different kinds of experiments. The point is therefore not only that there are some software programs in the life sciences that are open source whereas most are not; open source is integral to forms of experimentation that depends on constant coordination of a \'multiplicity of techniques coordinated on an elevated surface (the screen)\' (see Mackenzie [@CR62]: 189). Crucially, the introduction of open source in the life sciences is therefore not a feature of patenting or the proliferation of exclusivity. 