System for Parallel Heterogeneity Resolution (SPHeRe) results for OAEI 2013

SPHeRe is an ontology matching system that utilizes cloud infrastructure for matching large scale ontologies and focus on alignment representation to be stored in the Mediation Bridge Ontology (MBO). MBO is the mediation ontology that stores all the alignments generated between the matched ontologies and represents it in a manner that provides maximum metadata information. SPHeRe is a new initiative therefore it only participates in the large biomedical ontologies track of the OAEI 2013 campaign. The objectives of SPHeRe system participation in OAEI is to shift focus of ontology matching community towards areas such as cloud utilization, effective mapping representation, and flexible and extendable design of the matching system. 1 Presentation of the system Ontology mappings enables accessibility of information by aligning the resources in ontologies belonging to diverse organizations [3]. These also resolves semantic heterogeneities among data sources. Mainly two steps are required to overcome semantic heterogeneity: Matching resources to determine alignments and interpreting those alignments according to application requirements [5]. We have started developing SPHeRe system in 2013 and its an ongoing project. The objectives of SPHeRe system are performance [2], accuracy, mapping representation, and flexible and extendible design of the system. 1.1 State, purpose, general statement SPHeRe system target a complete package of a system with main objectives as accuracy, mapping representation, and flexible and extendible system. Its precision is on the higher side in large biomedical ontologies track, that shows its potential of improving the accuracy. It is based on different algorithms such as String Matching Bridge, Synonym Bridge, Child Based Structural Bridge (CBSB), Property Based Structural Bridge (PBSB), and Label Bridge. We plan to include further bridge algorithms in next version of the proposed system by incorporating new matching techniques. Parallelism has been overlooked by ontology matching systems. SPHeRe avails this opportunity and provides a solution by: (i) creating and caching serialized subsets of candidate ontologies with single-step parallel loading; (ii) lightweight matcher-based and redundancy-free subsets result in smaller memory footprints and faster load time; and (iii) implementing data parallelism based distribution over subsets of candidate ontologies by exploiting the multicore distributed hardware of cloud platform for parallel ontology matching and execution [2]. Mapping representation is another aspect of SPHeRe system which is not covered in this paper. We have followed OAEI alignment representation format, but we consider mapping representation as an important dimension to be worked by ontology matching research community. The more expressive the alignments should be, the easy its expert verification and the more will be confidence level in transformation process. 1.2 Specific techniques used SPHeRe system is based on bridge algorithms run in the parallel execution environment to generate alignments to be stored in the MBO as shown in Fig. 1. Matcher Library components stores all the bridge algorithms to be run on the parallel execution environment represented by Parallel Matching Framework. Communication between these two components is regulated by SPHeRe Execution Control module that behaves as a controller. The alignments are stored in the MBO; generated by the bridge algorithms stored in Matcher Library that are run by the Parallel Matching Framework. SPHeRe Execution Control Mediation Bridge Ontology (MBO) Matcher Library Parallel Matching Framework Distributor Aggregator Parallel Hardware Interface String Matching Bridge Synonym Bridge Label Bridge