Reetta Sinkkilä

CultureSampo: A National Publication System of Cultural Heritage on the Semantic Web 2.0

CultureSampo is an application demonstration of a national level publication system of cultural heritage contents on the Web, based on ideas and technologies of the Semantic (Web and) Web 2.0. On the semantic side, the system presents new solutions to interoperability problems of dealing with multiple ontologies of different domains, and to problems of integrating multiple metadata schemas and cross-domain content into a homogeneous semantic portal. A novelty of the system is to use semantic models based on events and narrative process descriptions for modeling and visualizing cultural phenomena, and for semantic recommendations. On the Web 2.0 side, CultureSampo proposes and demonstrates a content creation process for collaborative, distributed ontology and content development including different memory organizations and citizens. The system provides the cultural heritage contents to end-users in a new way through multiple (nine) thematic perspectives, based on semantic visualizations. Furthermore, CultureSampo services are available for external web-applications to use through semantic AJAX widgets.

Elements of a National SemanticWeb Infrastructure--Case Study Finland on the Semantic Web

This article presents the vision and results of creating the basis for a national semantic Web content infrastructure in Finland in 2003-2007. The main elements of the infrastructure are shared and open metadata schemas, core ontologies, and public ontology services. Several practical applications testing and demonstrating the usefulness of the infrastructure are overviewed in the fields of eculture, ehealth, egovernment, elearning, and ecommerce.

Automatic semantic subject indexing of web documents in highly inflected languages

Structured semantic metadata about unstructured web documents can be created using automatic subject indexing methods, avoiding laborious manual indexing. A succesful automatic subject indexing tool for the web should work with texts in multiple languages and be independent of the domain of discourse of the documents and controlled vocabularies. However, analyzing text written in a highly inflected language requires word form normalization that goes beyond rule-based stemming algorithms. We have tested the state-of-the art automatic indexing tool Maui on Finnish texts using three stemming and lemmatization algorithms and tested it with documents and vocabularies of different domains. Both of the lemmatization algorithms we tested performed significantly better than a rule-based stemmer, and the subject indexing quality was found to be comparable to that of human indexers.