Representation of Semantic Mappings

The aim of this breakout session was to chart the landscape of existing approaches for representing mappings between heterogeneous models, identify common ideas and formulate research questions to be addressed in the future. In the session, the discussion mainly concerned three aspects: The nature of mappings, existing proposals for mappings and open research questions

Uncertainty in Semantic Schema Integration

In this paper we present a new method of semantic schema integration, based on uncertain semantic mappings. The purpose of semantic schema integration is to produce a unified representation of multiple data sources. First, schema matching is performed to identify the semantic mappings between the schema objects. Then, an integrated schema is produced during the schema merging process based on the identified mappings. If all semantic mappings are known, schema merging can be performed (semi-)automatically

Semantic mappings: out of ontology world limits

Mappings usually relate two similar knowledge representations. Thus, we can find many examples of mappings amid thesauri, databases, ontologies (domain ontologies, top-level and domain ontologies, PSM (Problem Solving Method) and domain ontologies, linguistic and domain ontologies); additionally, we can frequently find systems with mappings that relate two different knowledge representations, for instance, databases and ontologies. All these mappings are operationally different ,and are also named differently (mappings, correspondences, semantic bridges, transformations, semantic relations, functions, conversions, domain-PSM relations), but is there a single definition for these concepts? Can we find common characteristics? This paper analyzes the existing definitions and representation of the term “mapping” (and related terms) in the ontology world and its semantic neighborhood and proposes a new definition and representation of “mapping” for the Semantic Web field

OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

The business process modelling ontology

In this paper we describe the Business Process Modelling Ontology (BPMO), which is part of an approach to modelling business processes at the semantic level, integrating knowledge about the organisational context, workflow activities and Semantic Web Services. We harness knowledge representation and reasoning techniques so that business process workflows can: be exposed and shared through semantic descriptions; refer to semantically annotated data and services; incorporate heterogeneous data though semantic mappings; and be queried using a reasoner or inference engine. In this paper we describe our approach and evaluate BPMO through a use case

Semantic radical consistency and character transparency effects in Chinese: an ERP study

BACKGROUND: This event-related potential (ERP) study aims to investigate the representation and temporal dynamics of Chinese orthography-to-semantics mappings by simultaneously manipulating character transparency and semantic radical consistency. Character components, referred to as radicals, make up the building blocks used dur...postprin

Automated syntactic mediation for Web service integration

As the Web Services and Grid community adopt Semantic Web technology, we observe a shift towards higher-level workflow composition and service discovery practices. While this provides excellent functionality to non-expert users, more sophisticated middleware is required to hide the details of service invocation and service integration. An investigation of a common Bioinformatics use case reveals that the execution of high-level workflow designs requires additional processing to harmonise syntactically incompatible service interfaces. In this paper, we present an architecture to support the automatic reconciliation of data formats in such Web Service worklflows. The mediation of data is driven by ontologies that encapsulate the information contained in heterogeneous data structures supplying a common, conceptual data representation. Data conversion is carried out by a Configurable Mediator component, consuming mappings between \xml schemas and \owl ontologies. We describe our system and give examples of our mapping language against the background of a Bioinformatics use case