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In the past years, it has been investigated in multiple research projects how shared data spaces can be extended with concepts and technologies from the semantic web area, which led to the development of so-called semantic spaces. These semantic spaces enable clients to publish semantically annotated data at a shared repository and to react to changes of information that can be inferred from this data. The declarative description of logical dependencies and their automated evaluation through the semantic space allow for the development of simple and elegant solutions for various complex communication and coordination problems. The investigation of many space based applications as well as experience we gained during our own work have shown that there already exist several best practices for solving many of these problems. However, no standard solutions have been established yet. In this paper, we determine a set of API operations that are supported by most available semantic space implementations and employ this set of operations as a common language for the description of four generic knowledge-based interaction patterns. The paper introduces certain usage scenarios, illustrates the benefits of using semantic spaces, and should serve as a basis for further pattern descriptions.

For constantly changing businesses, it is essential that the underlying software architecture is capable of managing agile business processes and meeting future business needs. Decoupling between applications and services in distributed systems is addressed by e. g., service-oriented architectures. On the other hand, applications and its underlying middleware are still tightly coupled with respect to the middleware's architectural style. As a result of the tight coupling middleware adaptations introduced due to e. g., new business requirements can affect the application as well. In this paper we propose the concept of space-based architecture (SBA), that allows decoupling distributed applications with respect to the underlying middleware architecture by combining the characteristics and properties of state-of-the-art middleware architectural styles captured in a simple API. The benefit of our approach is minimal application adaptations in case of changing the underlying middleware architectural style, which allows for more efficient realization of new business requirements.

Location and manipulation of complex data is a difficult, challenging task in nowadays extremely complex IT systems and on the Internet, overwhelmed with a huge amount of information that develops and grows rapidly. In this paper, we propose a self-organizing approach that combines purely decentralized unstructured P2P with space based computing in order to locate effectively and filter (retrieve) information from a network. The inspiration came from swarm intelligence that possesses distributive and autonomous properties and represents a self-organizing biological system. The goal is to achieve a good query capability, which we prove by means of benchmarks.