Over the last several years, the market for speech technology has seen significant developments (Pieraccini and Huerta We learned some lessons which we use as guidelines 2005) and powerful commercial off-the-shelf solutions for in the development of multimodal dialogue systems where speech recognition (ASR) or speech synthesis (TTS). Further users can combine speech and gestures when using multiple application scenarios, more diverse and dynamic information interaction devices. In earlier projects (Wahlster 2003; Reithinger sources, and more complex prototype systems need et al. 2005) we integrated different sub-components to be addressed in the context of QA. Dialogue-based QA allows to multimodal interaction systems. Other lessons served as a user to pose questions in natural speech, followed by guidelines in the development of semantic dialogue systems answers presented in a concise form (Sonntag et al. 2007).

Most social networks have implemented extensive and complex controls in order to battle the host of privacy concerns that initially plagued their online communities. These controls have taken the form of a-priori access control, which allow users to construct barriers preventing unwanted users from viewing their personal information. However, in cases in which the access restriction mechanisms are bypassed or when the access restrictions are met but the data is later misused, this system leaves users unprotected. Our framework, Respect My Privacy, proposes an alternative approach to the protection of privacy. Our strategy is similar to how legal and social rules work in our societies where the vast majority of these rules are not enforced perfectly or automatically, yet most of us follow the majority of the rules because social systems built up over thousands of years encourage us to do so and often make compliance easier than violation. Our project aims to support similar functionality in social networks. Instead of focusing on enforcing privacy policies through restricted access, we focus on helping users conform to existing policies by making them aware of the usage restrictions associated with the data. The framework has two main functions - generating privacy or usage control policies for social networks, and visualizing these policies while exploring social networks. We have implemented this functionality across three platforms: Facebook, OpenSocial and Tabulator, a Semantic Web browser. These applications enable users to specify privacy preferences for their data and then display this privacy-annotated data prominently enabling other users to easily recognize and conform to these preferences.

In this position paper, we argue that the Linked Open Data (LoD) Cloud, in its current form, is only of limited value for furthering the Semantic Web vision. Being merely a weakly linked triple collection, it will only be of very limited benefit for the AI or Semantic Web communities. We describe the corresponding problems with the LoD Cloud and give directions for research to remedy the situation.

Several solutions exist for semantically describing Web Services (WSs) from the perspective of orchestration but little is known about how semantics benefit WS choreography. The most extreme example of a choreography problem occurs in peer-to-peer systems where shared semantics of data may need to be established via services interactions. We present a solution to this problem by sharing micro-data via interaction models. No pre-unified ontology is required in our approach so peers can make use of existing heterogeneous resources having been described in the RDF data model flexibly and compatibly. The experimental results indicate that our approach semantically enhances WS choreography in a lightweight way which complies with principles of Linked Data and republished Interaction Models (IMs) can further facilitate the progress of the Web of data as well as the formation of peer communities generated through peers' interactions.

This paper examines first ideas on the applicability of Linked Data, in particular a subset of the Linked Open Drug Data (LODD), to connect radiology, human anatomy, and drug information for improved medical image annotation and subsequent search. One outcome of our ontology engineering methodology is the alignment between radiology-related OWL ontologies (FMA and RadLex). These can be used to provide new connections in the medicine-related linked data cloud. A use case scenario is provided that demonstrates the benefits of the approach by enabling the radiologist to query and explore related data, e.g., medical images and drugs. The diagnosis is on a special type of cancer (lymphoma).

A Digital Product Memory provides a digital diary of the complete product life cycle that is embedded in the product itself using smart wireless sensor technology. The data is hereby gathered by recording relevant ambient parameters in digital form. In this paper, we present the architecture and cost-efficient implementation of an autonomous digital product memory that generates and interprets its diary using rule-based reasoning methods. As we assume an open, heterogeneous sensor infrastructure, we rely on standard syntax and semantics provided by the Web Ontology Language OWL. The digital product memory collects and provides data using the OWL fragment OWL2 RL which can be processed with standard rule engines. As rule engine we use CLIPS on embedded hardware and exemplify the application of the digital product memory e.g. for predictive maintenance.

The Web of Data (WoD) is growing at an amazing rate and it will no longer be feasible to deal with it in a global way, by centralising the data or reasoning processes making use of that data. We believe that Computational Intelligence techniques provides the adaptiveness, robustness and scalability that will be required to exploit the full value of ever growing amounts of dynamic Semantic Web data.

Amongst the best practices that constitute linked data, one of the foremost is to use only HTTP-URIs as identifiers for RDF resources. This is so that the URI will resolve in a Linked Data browser to give information about the named resource. At the same time, Linked Data takes a resource-centric, as opposed to page-centric, approach to resolution. We argue that this approach can, in certain cases, obviate the need for insisting on HTTP-URIs. As a use of our “expanded” notion of Linked Data, we present as an example Life Science Identifiers.

GORT is a system that combines Linked Data from across several Semantic Web data sources to solve guesstimation problems, with user assistance. The system uses customised inference rules over the relationships in the OpenCyc ontology, combined with data from DBPedia, to reason and perform its calculations. The system is extensible with new Linked Data, as it becomes available, and is capable of answering a small range of guesstimation questions.

Time is a concept that highly depends on the socio-cultural context. Its perception by humans is primarily based on the cultures, nations and social environment they belong to. Hence, different socio-cultural contexts imply different understandings of time. This leads to communication problems when their members start interacting with each other. In a dynamic and multi-cultural environment like today’s Web, where both billions of people with different socio-cultural contexts and numerous context dependent software applications interact, similar communication and inter-operability problems are expected. Expressing socio-cultural temporal information in an unambiguous, explicit and machine processable way can, however, help reduce such communication conflicts. In this way, heterogeneous temporal Web application systems can share the same concept of time. In this paper we present an ontology of socio-cultural time expressions that attempts to formalize the notion of socio-cultural time. The resulting model can then be used in a Web based temporal applications such as automated appointment scheduling services or calendars to provide more context sensitive service to its users.