Search

In cultural heritage, large virtual collections are coming into existence. Such collections contain heterogeneous sets of metadata and vocabulary concepts, originating from multiple sources. In the context of the E-Culture demonstrator we have shown earlier that such virtual collections can be effectively explored with keyword search and semantic clustering. In this paper we describe the design rationale of ClioPatria, an open-source system which provides APIs for scalable semantic graph search. The use of ClioPatria’s search strategies is illustrated with a realistic use case: searching for ”Picasso”. We discuss details of scalable graph search, the required OWL reasoning functionalities and show why SPARQL queries are insufficient for solving the search problem.

Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high quality multimedia ontology that is compatible with existing (semantic) web technologies. We explain the complexity of the problem using an annotation scenario. We then derive a number of requirements for specifying a formal multimedia ontology before we present the developed ontology, COMM, and evaluate it with respect to our requirements. We provide an API for generating multimedia annotations that conform to COMM.

Current information retrieval (IR) approaches do not formally capture the explicit meaning of a keyword query but provide a comfortable way for the user to specify information needs on the basis of keywords. Ontology-based approaches allow for sophisticated semantic search but impose a query syntax more difficult to handle. In this paper, we present an approach for translating keyword queries to DL conjunctive queries using background knowledge available in ontologies. We present an implementation which shows that this interpretation of keywords can then be used for both exploration of asserted knowledge and for a semantics-based declarative query answering process. We also present an evaluation of our system and a discussion of the limitations of the approach with respect to our underlying assumptions which directly points to issues for future work.

We present Strabon, a new RDF store that supports the state of the art semantic geospatial query languages stSPARQL and GeoSPARQL. To illustrate the expressive power offered by these query languages and their implementation in Strabon, we concentrate on the new version of the data model stRDF and the query language stSPARQL that we have developed ourselves. Like GeoSPARQL, these new versions use OGC standards to represent geometries where the original versions used linear constraints. We study the performance of Strabon experimentally and show that it scales to very large data volumes and performs, most of the times, better than all other geospatial RDF stores it has been compared with.