An information retrieval approach to ontology mapping

In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e., using instance information of the ontology to enrich the original ontology and calculate similarities between concepts in two ontologies. The functional settings for the mapping system are discussed and the evaluation of the prototype implementation of the approach is reported. \ud \u

Knowledge web: realising the semantic web... all the way to knowledge-enhanced multimedia documents

The semantic web and semantic web services are major efforts in order to spread and to integrate knowledge technology to the whole web. The Knowledge Web network of excellence aims at supporting their developments at the best and largest European level and supporting industry in adopting them. It especially investigates the solution of scalability, heterogeneity and dynamics obstacles to the full development of the semantic web. We explain how Knowledge Web results should benefit knowledge-enhanced multimedia applications

Data Innovation for International Development: An overview of natural language processing for qualitative data analysis

Availability, collection and access to quantitative data, as well as its limitations, often make qualitative data the resource upon which development programs heavily rely. Both traditional interview data and social media analysis can provide rich contextual information and are essential for research, appraisal, monitoring and evaluation. These data may be difficult to process and analyze both systematically and at scale. This, in turn, limits the ability of timely data driven decision-making which is essential in fast evolving complex social systems. In this paper, we discuss the potential of using natural language processing to systematize analysis of qualitative data, and to inform quick decision-making in the development context. We illustrate this with interview data generated in a format of micro-narratives for the UNDP Fragments of Impact project

SemLinker: automating big data integration for casual users

A data integration approach combines data from different sources and builds a unified view for the users. Big data integration inherently is a complex task, and the existing approaches are either potentially limited or invariably rely on manual inputs and interposition from experts or skilled users. SemLinker, an ontology-based data integration system, is part of a metadata management framework for personal data lake (PDL), a personal store-everything architecture. PDL is for casual and unskilled users, therefore SemLinker adopts an automated data integration workflow to minimize manual input requirements. To support the flat architecture of a lake, SemLinker builds and maintains a schema metadata level without involving any physical transformation of data during integration, preserving the data in their native formats while, at the same time, allowing them to be queried and analyzed. Scalability, heterogeneity, and schema evolution are big data integration challenges that are addressed by SemLinker. Large and real-world datasets of substantial heterogeneities are used in evaluating SemLinker. The results demonstrate and confirm the integration efficiency and robustness of SemLinker, especially regarding its capability in the automatic handling of data heterogeneities and schema evolutions