Towards an Adaptive Tool and Method for Collaborative Ontology Mapping

Abstract

Linked Data makes available a vast amount of data on the Semantic Web for agents, both human and software, to consume. Li nked Data datasets are made available with different ontologies, even when their domains overlap. The interoperability problem that rises when one needs to consume and com- bine two or more of such datasets to develop a Linked Data application or mashup is s till an important challenge. Ontology - matching techniques help overcome this problem. The process, however, often relies on knowledge engi- neers to carry out the tasks as they have expertise in ontologies and semantic technologies . It is reasonable to assum e that knowledge engineers should re- quire help from the domain experts, end users, etc. to contribute in the valida- tion of the results and help distilling ontology mappings from these correspond- ences. However, the current design for the ontology - mapping to ols does not take into consideration the different types of users expected to be involved in the creation of Linked Data applications or mashups. In this paper, we identify the different users and their roles in the mapping involved in the context of de- vel oping Linked Data mashups and propose a collaborative mapping method in which we prescribe where collaboration between the different stakeholders could , and should , take place. In addition , we propose a tool architecture based on bringing together an adapt ive interface, mapping services, workflow services and agreement services that will ease the collaboration between the different stakeholders. This output will be used in an ongoing study to constructing a col- laborative mapping platform