Ontology Based Data Access

Prepared by:

Nirav U. PatelIT Department,SVMIT Bharuch

Overview of Ontology

• Ontology is a term in philosophy and its meaning is "Theory of existence".

• A definition of an ontology in AI community is "An explicit representation

of Conceptualization".

Formal, explicit specification of a shared conceptualization

commonly accepted understanding

conceptual model of a domain

(ontological theory)

unambiguous terminology definitions

machine-readability with computational

semantics

Ontology Example

Concept

conceptual entity of the domain

Attribute

property of a concept

Relation

relationship between concepts or properties

Axiom

coherent description between Concepts / Properties / Relations via logical expressions

Person

Student Professor

Lecture

isA – hierarchy (taxonomy)

name email

studentnr.

researchfield

topiclecturenr.

attends holds

Ontology Elements

• Concepts (classes) + their hierarchy

• Concept properties (slots/attributes)

• Property restrictions (type, cardinality, domain)

• Relations between concepts (disjoint, equality)

• Instances

Reasons for Developing an Ontology

• To share common understanding of the structure of information among

people or software agents.

• To enable reuse of domain knowledge. E.g If one group of researchers

develops such an ontology in detail, others can simply reuse it for their

domains.

• To separate domain knowledge from the operational knowledge.

• To analyze domain knowledge.

Ontology Development

Six basic steps are involved in ontology Development.

• Ontology scope: Identify the range of intended users. Determine the

purpose of ontology.

• Ontology capture: Identify the key concepts and relationships in domain.

• Ontology encoding: Choosing a representation language.

• Ontology integration: Existing may be useful to build a new ontology

• Ontology evaluation: Checking general criteria

Like Clarity, consistency and reusability;

• Ontology documentation: Effective knowledge sharing requires well

documentation.

Ontology Framework

Design criteria for the ontology framework:

• Clarity: Its definitions should be objective.

• Coherence: The ontology should be coherent.

• Extensibility: The ontology should anticipate the use of a shared

vocabulary.

• Minimal ontological commitment: The ontology should make as few

claims as possible about the modeled real world products.

• Web-enabled: It Should be efficiently use in distributed Internet/Intranet

environments.

Ontology Data Structures

• The data structures developed using the XML Schema specification.

• The framework is constructed in three inter-related layers as follows:

• A Core Engineering Ontology Specification Schema: provides the meta

structures for the definition of domain-specific ontologies.

• A potentially unlimited set of domain-specific ontology extension

schemas that imports the core schema and extends it with domain

concepts.

• XML-based ontology definitions that provide the details of the

identified domain concepts.

Data Access System

• Science and technology concerned with the effective and efficient retrieval

of information from an information repository.

• Fig shows information Flow in Data Access Process

Ontology-Based Data Access

• A key component for the new generation of information systems.

like Semantic Web applications

• Provides a vocabulary for user queries and high-level global schema

• The idea is to facilitate access to data by separating user from data sources.

• Provides a user oriented view of the data and make it accessible through

queries.

• It converts the user queries in to data vocabulary then representative the

actual query evaluation to the data sources.

Visualization Feature

The visualization is designed according to the following goals:

• Graphically represent a single mapping assertion.

• Graphically represent all the mapping assertions involving a given

ontology.

• Graphically represent all the mapping assertions involving a given

relational table of the source database,

• Provide the user with the capability of editing the textual representation of

a mapping assertion.

Ontology MappingsA single ontology will rarely fulfill the needs of a particular application, This

raises the problem of ontology integration (also called ontology alignment or

ontology mapping)

• Model mapping involves a procedure that is very similar to multi database

integration.

It consists of the following steps:

• Detection of schema overlaps,

• Detection of inter-schema conflicts,

• Definition of the inter-schema correspondences with the help of formal

mapping specifications,

• Use of appropriate mapping methods for the actual transformations.

Conclusion

• we are working on the semantic analysis of SQL queries in the mappings,

to discover properties and relations between them that are useful to prevent

situations which may lead to contradictions.

• we plan to also implement functionalities for the graphical editing of the

mapping, which in the current release can be modified only in textual

modality.

• We finally remark that the graphical representation of mappings presented

in this paper is independent of the ontology language used in the OBDA

specification.

Reference

[1] [Acciarri et al., 2005] A. Acciarri, D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini, M. Palmieri, and R. Rosati. QUONTO: QUerying ONTOlogies. In Proc. Of AAAI, pages 1670–1671, 2005.

[2][Apt, 1990] K. Apt. Logic programming. In Handbook of Theoretical Computer Science, Volume B: Formal Models and Sematics, pages 493–574. Elsevier, 1990.

[3][Calvanese and Rodr´ıguez-Muro, 2011] D. Calvanese and M. Rodr´ıguez-Muro, 2011. Private communication. [Calvanese et al., 2007] D. Calvanese, G. De Giacomo, D. Lembo, M. Lenzerini, and R. Rosati. Tractable reasoning and efficient query answering in description logics: The DL-Lite family. J. of Aut. Reason., 39(3):385–429, 2007.

[4][DeHaan et al., 2003] D. DeHaan, D. Toman, M. Consens, and M.T. O¨ zsu. A comprehensive XQuery to SQL translation using dynamic interval encoding. In Proc. of SIGMOD, pages 623–634, 2003. ACM.

Thank You