Quality of life in an urban environment depends strongly on ecological, social and mobility aspects. A major innovation in that context is given by the emergence of electric vehicles. Additionally, the explosive growth of social networks has shown how the Internet can be used to maintain and create communities, thereby bringing mutual benefits to the involved participants. Combining both, there is an obvious potential for the realization of collaborative electric vehicle sharing within a city. In this paper, we investigate one of the key aspects required to realize the vision of electric vehicle sharing - a cloud infrastructure for handling the required data. We propose a distributed architecture for the realization of such data cloud. Further, we demonstrate how ISP networks and the elect ric mobility data cloud can collaborate in order to provide efficient streaming of continuous data

Open Data (OD) is an emerging trend that aims to facilitate the freedom and reuse of information. Therefore, tools, applications and platforms are required that enable the publishing and consumption of data. In this paper, we present our experience from the integration of components that should constitute an OD platform. The proposed solution is able to store datasets as linked data, to catalogue the datasets, and provides a portal with features for supporting community activities. Further, we exemplify the utilization of the proposed platform, by describing a touristic city guide web mashup that uses published Open Data. This application consumes data in machine readable format over APIs provided by the OD platform.

A key challenge for open data portals is the aggregation of metadata from various data catalogs (on different administrative level or from different application fields) also known as metadata harvesting 1 . This paper describes harvesting at the pilot of the German open government portal Gov-Data.de, which is scheduled to become the data portal for all German public administration levels.At the launch of the pilot portal in February, eleven federal, state and local data catalogs were integrated, which produced about 2,000 open data sets. In the meantime, the number of data sets increased to over 3,100 mainly due to improved harvesting capabilities of the portal. This paper discusses GovData.de metadata schema and experiences with the different harvesting techniques that are in use at Gov-Data.de: CKAN-Harvest, CKAN-API, CSW-Harvest and JSON-Dump.

This chapter covers the scientific background for the Service Level Module of the Unified Service Description Language (USDL). In addition to general service level concepts, we expand on two specific service level fields: security and trust. For that end we first review the state of the art in service level modeling, then we explain the design of the Service Level Module and position it among the rest of USDL. For security, two possible perspectives, a high level business view and a low level engineering approach, are introduced. With regards to trust, USDL is suitable to specify how a service can be rated by its consumers and to ensure that ratings of competing services are comparable, and hence to determine trustworthiness. Additionally, we present a description of non-security-related elements that can be exploited for trust estimation.

This paper proposes a common ontology for ratings, i.e. for quantitative user feedback data. Such a framework allows for semantic interoperability of data that adheres to it, which in turn enables the re-use, by making it independent from the original system.In contrast to prior attempts to establish an unambiguous vocabulary, this approach introduces two components that are in our view necessary to formally understand what a user's rating actually means. The first is the aspect or facet, i.e. the viewing angle that was chosen to look at the rated thing. The second is the meta-model of scales following the scales of measurement that are widely used in descriptive statistics. So in plain words, we allow to formally specify how many out of how many score points something gets and with regards to what.We follow the open world assumption of the Web Ontology Language (OWL) and design a vocabulary that is not specific to any domain. In turn, we rely on the premise that all domain specific concepts are available as semantic web resources with appropriate URIs.