The market for Internet search engines is currently dominated by several big companies, that, with immense effort (Google uses 16000 Linux Servers), try to index all pages on the Internet. But the number of pages available on the Internet is growing faster that they can be indexed. An alternative could be domain specific (vertical) search engines that are currently under discussion. These domain specific search engines could apply algorithms to automatically recognize the topic and content of a specific page. The aim of the project is to develop existing algorithms in a marketable product. New elements to be included in the project: Optimisation of algorithms for automatic topic recognition, based on linguistic analysis Integration of new business models for defined positioning (Paid Positioning) and defined integration (Paid Inclusion) to offer new models to the customers

Der Innovationslehrgang zielt darauf ab, die digitale Kompetenz im Tourismus zu erhöhen. Zielgruppe sind IT-Verantwortliche in Tourismusunternehmen. Hierzu zählen bspw. Tour Operator, die Hotellerie, aber auch Beratungsunternehmen im Tourismus. Zudem werden auch Tourismusverbände und Landestourismusorganisationen angesprochen, ihre IT-Verantwortlichen weiterzubilden. Die Weiterbildungsinhalte richten sich nach aktuellen Forschungsinitiativen an den beteiligten Universitäten und Fachhochschulen und decken hierbei Themen wie Semantische Technologien im Web, Usability von Assistenzsystemen, Konsumentenverhalten im Buchungsprozess, Big Data Management oder Strategien zur Cyber-Sicherheit ab. Derzeit sind 15 Module zwischen 2-4 Lehrtagen eingeplant. Diese Lehrtage werden branchenspezifisch in Nebensaisonen und an Randzeiten der Arbeitswoche angeboten. Als LektorInnen stehen ForscherInnen aus (derzeit) acht Universitäten und Fachhochschulen zur Verfügung. Die angebotenen Inhalte werden in einigen Themenbereichen auf Einstiegs- und Aufbauniveau angeboten. Somit können sehr erfahrene MitarbeiterInnen, wenn gewünscht, direkt im Aufbauniveau einsteigen. Das Resultat wird zu einer erhöhten Professionalisierung des eTourismus in Österreich führen.

Many digital sound archives suffer from tremendous problems concerning access. Sound materials are often held separately from other materials and media, they cannot easily be listened to or browsed, and there is no way to search the content. Existing systems which attempt to deal with these issues are often library or content specific, of limited functionality, or difficult to use. Extending over two and a half years, the EASAIER project will enable enhanced access to sound archives by providing multiple methods of retrieval, integration with other media archives, content enrichment and enhanced access tools. It offers methods of searching content based on audio features, musical features, or speech content. EASAIER also supports cross-media retrieval, enabling access to other media besides just audio.

The goal of this project is to build an integrated leading Euro-Asian high education and research community in the field of the Semantic Web, the next generation of the Web. Direct target groups are graduate students, faculty staff and enterprises management personnel. Indirect target groups are European and Asian students, researchers and enterprises personnel at large. We plan to operate on the following three main actions: Human resources development: joint teaching and supervision of master and doctorate students; integration and collaboration among senior and young faculty; training the next generation of IT educators as well as of IT enterprises management. Distance Learning and Knowledge Management platform: to support current and future activities also after the end of the project Networking: we will foster the interaction among universities and companies in Europe and Asia in the field of Semantic Web. The European partners (Italy, Austria, Ireland, Poland) are leading institutes in the Semantic Web. The Asian partners (India, Thailand, China, and the associate partner Hong Kong) are among the best performance institutions in Asia .The duration of the project is 36 months.

Contemporary information retrieval and filtering (IRaF) systems lack the appropriate representation of user information needs and information itself. There are heterogeneous sources of information, and information usually is ambiguous. This project aims on the improvement of the IRaF system in order to better satisfy user needs by providing training in the following areas: formal models of ontologies, software and tools for ontologies, Semantic Web and Web Services, human language technology, decision making. Scientific quality of the training is assured by a co-operation with leading research centres from Austria, Germany, The Netherlands, Norway, and UK.

Taking into account the fact that buildings constitute the largest end-use energy consuming sector, the design and development of solutions targeted at reducing their energy consumption based on the adoption of energy efficient techniques and the active engagement of citizens/occupants is considered crucial. Innovative solutions have to be implemented upon properly understanding the main energy consuming factors and trends, as well as properly modeling and understanding the citizens’ behaviour and the potential for lifestyle changes.

The ENTROPY project addresses this challenge by building upon the integration of technologies that facilitate the deployment of innovative energy aware IT ecosystems for motivating end-users’ behavioural changes and namely: (1) the Internet of Things that provides the capacity for interconnecting numerous devices and applying energy-efficient communication protocols, (2) the evolution of advanced Data Modelling and Analysis techniques that support the realization of semantic models and knowledge extraction mechanisms and (3) the Recommendation and Gamification eras that can trigger interaction with relevant users in social networks, increase end users’ awareness with regards to ways to achieve energy consumption savings in their daily activities and adopt energy efficient lifestyles as well as provide a set of energy efficient recommendations and motives.

The ENVISION project provides an ENVIronmental Services Infrastructure with Ontologies that aims to support non ICT-skilled users in the process of semantic discovery and adaptive chaining and composition of environmental services. Innovations in ENVISION are: on-the-Web enabling and packaging of technologies for their use by non ICT-skilled users, support for migrating environmental models to be provided as models as a service (Maas), and the use of data streaming information for harvesting information for dynamic building of ontologies and adapting service execution.   The ENVISION Environmental Decision Portal supports the creation of web-based applications enabled for dynamic discovery and visual service chaining. The ENVISION Ontology Infrastructure provides support for visual semantic annotation tools and multilingual ontology management. The ENVISION Execution Infrastructure comprises a semantic discovery catalogue and a semantic service mediator based on a generic semantic framework and adaptive service chaining with data-driven adaptability.   Scenario requirements and pilots from the ENVISION user partners focus on landslide hazard assessment and environmental pollution (oil spills) decision support systems. The benefit of ENVISION for the wider community will be better accessibility to modelling tools using the Web and it will provide greater flexibility through improved connections to distributed sources of information.

Esperonto's objective is to bridge the gap between the actual World Wide Web and the Semantic Web by providing a service to upgrade existing content to semantic Web content. Ontologies play a key role in this effort, aiming at unifying, bridging and integrating multiple heterogeneous, international and multilingual digital content. Once having Semantic Web content, the project aims at exploiting the content through innovative graphical navigation, and prototyping distributed added value services.