  Motivated from the Context Aware Computing, and more particularly from the
Data-Driven Process Adaptation approach, we propose the Semantic Context Space
(SCS) Engine which aims to facilitate the provision of adaptable business
processes. The SCS Engine provides a space which stores semantically annotated
data and it is open to other processes, systems, and external sources for
information exchange. The specified implementation is inspired from the
Semantic TupleSpace and uses the JavaSpace Service of the Jini Framework
(changed to Apache River lately) as an underlying basis. The SCS Engine
supplies an interface where a client can execute the following operations: (i)
write: which inserts in the space available information along with its
respective meta-information, (ii) read: which retrieves from the space
information which meets specific meta-information constrains, and (iii) take:
which retrieves and simultaneously deletes from the space information which
meets specific meta-information constrains. In terms of this thesis the
available types of meta-information are based on ontologies described in RDFS
or WSML. The applicability of the SCS Engine implementation in the context of
data-driven process adaptation has been ensured by an experimental evaluation
of the provided operations. Ultimately, we refer to open issues which could be
addressed to enrich the proposed Engine with additional features.
