Semantic Resource Discovery in Large Scale Environments

AbstrAct: In biosciences, data mining is concerned with processing large amount of data which is characterized by hetero-geneity, ever changing and spread in different complex environments. Resource discovery from massive data poses a formidable task for many newer as well as routine applications. The issues addressed in the massive data environments so far are the hetero-geneity issues and the semantic focus is less. In the current work, we deal with the resource discovery in large-scale environments (as data grid systems) considering data semantic heterogeneity of biomedical sources. There are many benefits such as-(i) allowing a permanent access, through an addressing system, from any domain ontology DO i to another DO j (inter-domain discovery) despite peers' dynamicity, (ii) reducing the maintenance cost and (iii) taking into account the semantic heterogeneity.