The Smart Grid aims at making the current electricity grid more efficient, featuring an IT-layer that includes communication flows between a multitude of stakeholders. Its infrastructure is likely to be integrated with other IT-based systems. We argue that in order to enable the integration between already existing large-scale information networks (e.g., the Internet or the Web) and newly developed IT infrastructures such as Smart Cities, means for machine-understandable representation of data are required. Since these “smart” systems will exchange large volumes of highly sensitive data (billing and personal data), users should have the ability to specify their intent on how their data can be shared. Thus, systems require built-in mechanisms for protecting data. In this paper, we outline a Smart Grid architecture based on Semantic Web (Linked Data) technologies, and present mechanisms to allow for automated access control and enforcement of privacy rights on a technical level.

An increasing amount of applications build their functionality on the utilisation and manipulation of web resources. Consequently REST gains popularity with a resource-centric interaction architecture that draws its flexibility from links between resources. Linked Data offers a uniform data model for REST with self-descriptive resources that can be leveraged to avoid a manual ad-hoc development of web-based applications. For declaratively specifying interactions between web resources we introduce Data-Fu, a lightweight declarative rule language with state transition systems as formal grounding. Data-Fu enables the development of data-driven applications that facilitate the RESTful manipulation of read/write Linked Data resources. Furthermore, we describe an interpreter for Data-Fu as a general purpose engine that allows to perform described interactions with web resources by orders of magnitude faster than a comparable Linked Data processor.

The advent of the Web of Data kindled interest in link-traversal (or lookup-based) query processing methods, with which queries are answered via dereferencing a potentially large number of small, interlinked sources. While several algorithms for query evaluation have been proposed, there exists no notion of completeness for results of so-evaluated queries. In this paper, we motivate the need for clearly-defined completeness classes and present several notions of completeness for queries over Linked Data, based on the idea of authoritativeness of sources, and show the relation between the different completeness classes.

WS-Policy is a standard to express requirements and capabilities in Web service systems. Policies are based on domain-specific assertions. In this paper we present a lightweight approach to semantic annotations of policy assertions. The approach allows matching of requirements and capabilities based not only on the syntactical representation of their corresponding assertions but also on their semantic meaning. Besides vocabulary mismatches our approach can also handle granularity mismatches, e.g. if two capabilities in combination satisfy a single requirement. We present a validation of our approach consisting of a performance evaluation and the realization of a use case, both based on our implementation of the semantic policy matching algorithm. We furthermore show the advantages of our approach compared to existing related work.

Web Services provide standardized interfaces for accessing software systems and data sources over the Internet. Semantic descriptions of Web Services help to automate the discovery and invocation of new services and their integration into existing applications. However not all services are freely available for every purpose and not all data is in the public domain. Usage policies describe the terms and conditions under which services and data can be used. Current approaches to semantic Web Service description are mostly focused on functional properties and quality attributes, and do not cover usage policies. We plan to develop a formal language for usage policies with clearly defined semantics that relies on ontologies for representing domain specific terms. We will also extend service discovery and ranking algorithms to incorporate usage policies. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.