Anna Tordai

Semantic annotation and search of cultural-heritage collections: The MultimediaN E-Culture demonstrator

In this article we describe a Semantic Web application for semantic annotation and search in large virtual collections of cultural-heritage objects, indexed with multiple vocabularies. During the annotation phase we harvest, enrich and align collection metadata and vocabularies. The semantic-search facilities support keyword-based queries of the graph (currently 20M triples), resulting in semantically grouped result clusters, all representing potential semantic matches of the original query. We show two sample search scenarios. The annotation and search software is open source and is already being used by third parties. All software is based on established Web standards, in particular HTML/XML, CSS, RDF/OWL, SPARQL and JavaScript.

Let's agree to disagree: on the evaluation of vocabulary alignment

Gold standard mappings created by experts are at the core of alignment evaluation. At the same time, the process of manual evaluation is rarely discussed. While the practice of having multiple raters evaluate results is accepted, their level of agreement is often not measured. In this paper we describe three experiments in manual evaluation and study the way different raters evaluate mappings. We used alignments generated using different techniques and between vocabularies of different type. In each experiment, five raters evaluated alignments and talked through their decisions using the think aloud method. In all three experiments we found that inter-rater agreement was low and analyzed our data to find the reasons for it. Our analysis shows which variables can be controlled to affect the level of agreement including the mapping relations, the evaluation guidelines and the background of the raters. On the other hand, differences in the perception of raters, and the complexity of the relations between often ill-defined natural language concepts remain inherent sources of disagreement. Our results indicate that the manual evaluation of ontology alignments is by no means an easy task and that the ontology alignment community should be careful in the construction and use of reference alignments.

Aligning large SKOS-Like vocabularies: two case studies

In this paper we build on our methodology for combining and selecting alignment techniques for vocabularies, with two alignment case studies of large vocabularies in two languages. Firstly, we analyze the vocabularies and based on that analysis choose our alignment techniques. Secondly, we test our hypothesis based on earlier work that first generating alignments using simple lexical alignment techniques, followed by a separate disambiguation of alignments performs best in terms of precision and recall. The experimental results show, for example, that this combination of techniques provides an estimated precision of 0.7 for a sample of the 12,725 concepts for which alignments were generated (of the total 27,992 concepts). Thirdly, we explain our results in light of the characteristics of the vocabularies and discuss their impact on the alignments techniques.

Thesaurus and metadata alignment for a semantic e-culture application

In this paper we describe a methodological approach for porting cultural repositories to the Semantic Web, focusing on the global picture of the required mappings and alignments.