An Infrastructure for acquiring high quality semantic metadata

Because metadata that underlies semantic web applications is gathered from distributed and heterogeneous data sources, it is important to ensure its quality (i.e., reduce duplicates, spelling errors, ambiguities). However, current infrastructures that acquire and integrate semantic data have only marginally addressed the issue of metadata quality. In this paper we present our metadata acquisition infrastructure, ASDI, which pays special attention to ensuring that high quality metadata is derived. Central to the architecture of ASDI is a erification engine that relies on several semantic web tools to check the quality of the derived data. We tested our prototype in the context of building a semantic web portal for our lab, KMi. An experimental evaluation omparing the automatically extracted data against manual annotations indicates that the verification engine enhances the quality of the extracted semantic metadata

An infrastructure for building semantic web portals

In this paper, we present our KMi semantic web portal infrastructure, which supports two important tasks of semantic web portals, namely metadata extraction and data querying. Central to our infrastructure are three components: i) an automated metadata extraction tool, ASDI, which supports the extraction of high quality metadata from heterogeneous sources, ii) an ontology-driven question answering tool, AquaLog, which makes use of the domain specific ontology and the semantic metadata extracted by ASDI to answers questions in natural language format, and iii) a semantic search engine, which enhances traditional text-based searching by making use of the underlying ontologies and the extracted metadata. A semantic web portal application has been built, which illustrates the usage of this infrastructure

An instance mapping ontology for the semantic web

Semantic data transformation plays an important role in realizing the vision of the semantic web. It supports the transformation of data in different representations into on-tologies. In order to allow the task to be achieved effec-tively, the instructions on how to realize transformation should be well specified, preferably in a declarative and re-usable format, thus allowing the construction of robust tools which on the one hand assist users to generate and maintain mappings at design time and on the other hand perform semantic data transformation at run time. Furthermore, the transformation instructions should not only allow the gen-eration of semantic data objects but also allow the creation of rich semantic relations between them. In this context, we developed a comprehensive instance mapping ontology. One distinctive feature of the instance mapping ontology is that it provides comprehensive support for the specification of complex mappings. Another feature is that the instance mapping ontology is representation independent, which does not limit itself to data sources in particular representa-tions. This ontology has been applied in generating a se-mantic layer for the web site of the Knowledge Media Insti-tute (KMi) at the Open University