Abstract
Scientific experiments are supported by activities that create, use, communicate and distribute information and whose organizational dynamics is similar to processes performed by distributed cooperative enterprise units. The aim of this chapter is to describe the approach undertaken in the Advanced Lab for Bioinformatics Agencies (ALBA) project to the design and management of cooperative scientific experiments (Bosin et al., 2006). A framework is used that defines the responsibility of computational nodes in offering services and the set of rules under which each service can be accessed by networked nodes through invocation mechanisms in the service-oriented style of computing and collaborating (COOPIS, 2005).
Key Terms in this Chapter
Cooperative Information Systems: Independent, federated information systems that can either autonomously execute locally or cooperate for some tasks toward a common organizational goal.
E-Experiment: Scientific experiment executed on an ICT distributed environment centred on cooperative tools and methods
Interoperability: Possibility of performing computation in a distributed heterogeneous environment without altering the technological and specification structure at each involved node.
Clustering: Automatic aggregation of data in classes according to a given distance (usually Euclidean). It is supervised if a subset of data is used in order to learn the classification embedded rule to be applied to the rest of the data; otherwise unsupervised.
Grid Computing: Distributed computation over a grid of nodes dynamically allocated to the process in execution.
Bioinformatics: The application of the ICT tools to advanced biological problems, like transcriptomics and proteomic, involving huge amounts of data.
Web Services: Software paradigm enabling peerto- peer computation in distributed environments based on the concept of “service” as an autonomous piece of code published in the network.
E-Science: Modality of performing experiments in silico in a cooperative way by resorting to information and communication technology (ICT)
Drug Discovery: Forecasting of the properties of a candidate new drug on the basis of a computed combination of the known properties of its main constituents.