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Existing tools for generating application programming interfaces (APIs) for ontologies lack sophisticated support for mapping the logics-based concepts of the ontology to an appropriate object-oriented implementation of the API. Such a mapping has to overcome the fundamental differences between the semantics described in the ontology and the pragmatics, i.e., structure, functionalities, and behavior implemented in the API. Typically, concepts from the ontology are mapped one-to-one to classes in the targeted programming language. Such a mapping only produces concept representations but not an API at the desired level of granularity expected by an application developer. We present a Model-Driven Engineering (MDE) process to generate customized APIs for ontologies. This API generation is based on the semantics defined in the ontology but also leverages additional information the ontology provides. This can be the inheritance structure of the ontology concepts, the scope of relevance of an ontology concept, or design patterns defined in the ontology.
The novel mobile application csxPOI (short for: collaborative, semantic, and context-aware points-of-interest) enables its users to collaboratively create, share, and modify semantic points of interest (POI). Semantic POIs describe geographic places with explicit semantic properties of a collaboratively created ontology. As the ontology includes multiple subclassiffcations and instantiations and as it links to DBpedia, the richness of annotation goes far beyond mere textual annotations such as tags. With the intuitive interface of csxPOI, users can easily create, delete, and modify their POIs and those shared by others. Thereby, the users adapt the structure of the ontology underlying the semantic annotations of the POIs. Data mining techniques are employed to cluster and thus improve the quality of the collaboratively created POIs. The semantic POIs and collaborative POI ontology are published as Linked Open Data.
We propose a new approach for mobile visualization and interaction of temporal information by integrating support for time with today's most prevalent visualization of spatial information, the map. Our approach allows for an easy and precise selection of the time that is of interest and provides immediate feedback to the users when interacting with it. It has been developed in an evolutionary process gaining formative feedback from end users.
We present the user-centered, iterative design of Mobile Facets, a mobile application for the faceted search and exploration of a large, multi-dimensional data set of social media on a touchscreen mobile phone. Mobile Facets provides retrieval of resources such as places, persons, organizations, and events from an integration of different open social media sources and professional content sources, namely Wikipedia, Eventful, Upcoming, geo-located Flickr photos, and GeoNames. The data is queried live from the data sources. Thus, in contrast to other approaches we do not know in advance the number and type of facets and data items the Mobile Facets application receives in a specific contextual situation. While developingrnMobile Facets, we have continuously evaluated it with a small group of fifive users. We have conducted a task-based, formative evaluation of the fifinal prototype with 12 subjects to show the applicability and usability of our approach for faceted search and exploration on a touchscreen mobile phone.
Semantic desktop environments aim at improving the effectiveness and efficiency of users carrying out daily tasks within their personal information management infrastructure (PIM). They support the user by transferring and exploiting the explicit semantics of data items across different PIM applications. Whether such an approach does indeed reach its aim of facilitating users" life and—if so—to which extent, however, remains an open question that we address in this paper with the first summative evaluation of a semantic desktop approach. We approach the research question exploiting our own semantic desktop infrastructure, X-COSIM. As data corpus, we have used over 100 emails and 50 documents extracted from the organizers of a conference-like event at our university. The evaluation has been carried out with 18 subjects. We have developed a test environment to evaluate COSIMail and COSIFile, two semantic PIM applications based on X-COSIM. As result, we have found a significant improvement for typical PIM tasks compared to a standard desktop environment.