Derivation of OWL Ontology from XML Documents by Formal Semantic Modeling

Abstract

The extensible markup language (XML), a standard format of web information, has a clear syntax but unfortunately an ambiguous formal semantics, which results in being not used directly in semantic web applications. So it is tough job to reuse XML-based data intelligently in the semantic web. To address this problem, a new formal technique of obtaining ontology data automatically from XML documents is proposed. We provide the XML a semantical interpretation by developing a graph-based formal language, which then can be automatically mapped into web ontology language OWL with semantics preserved. The semantic validity and entailment problem are also concerned. The automatical mapping tool has also been developed.

Semantic Consistency Checking in Building Ontology from Heterogeneous Sources

“…The main idea is to execute SQL procedures to retrieve the semantic information of the database instances, transform the result sets into a Wgraph model, and then transform the model into the ontology autocompletely, which not only maps schemata to the middle model, but also populates the model with data stored in databases. This language is also used to model semantically XML documents in [5]. In [5], they provide XML documents for a semantical interpretation by the W-graph language.…”

“…This language is also used to model semantically XML documents in [5]. In [5], they provide XML documents for a semantical interpretation by the W-graph language. The W-graph model created from relationship databases or XML documents can be automatically transformed into a domain ontology (expressed in ontology web language-OWL [18]).…”

“…The legacy web data in varietal forms can be classified roughly into three types: structured data, such as relational databases; semistructured data, such as XML documents and emails; and nonstructured data, such as general text and video. Recently, technologies of automatically transforming semistructured data or structured data into a domain ontology through mediate modeling are promising [2][3][4][5][6]. In these technologies, some semantic collisions appear inevitably when the same domain ontology has been built from multiple data sources.…”

“…As for semistructured data sources, in [4][5][6], researchers employ a mediate model language for modeling semistructured data and then transform middle models into the domain ontology. The validity checking has been provided 2 Journal of Applied Mathematics while collisions happen, which is generally a syntax checking.…”

Hierarchical Modeling and Verification for High-speed Train Control Center by Time Automation

“…Therefore, different scenes of the same layer can be used interactively. Using formal methods can maximize our understanding and analysis on a system and help us find the inconsistency, fuzziness, incompleteness or more [10][11][12]. TA, as a formal description method, has complete mathematical bases, which not only provide the methods of precise definition consistency and integrity, but also offer a method to prove the properties without running the system [13,14].…”