Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services

Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprieta...

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Main Authors: Zhu, Hongwei, Madnick, Stuart E.
Format: Article
Language:English
Published: 2004
Subjects:
Online Access:http://hdl.handle.net/1721.1/7413
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author Zhu, Hongwei
Madnick, Stuart E.
author_facet Zhu, Hongwei
Madnick, Stuart E.
author_sort Zhu, Hongwei
collection MIT
description Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions.
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spelling mit-1721.1/74132019-04-11T03:43:14Z Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services Zhu, Hongwei Madnick, Stuart E. Data integration heterogeneous sources ontology scalability Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions. Singapore-MIT Alliance (SMA) 2004-12-13T05:49:32Z 2004-12-13T05:49:32Z 2005-01 Article http://hdl.handle.net/1721.1/7413 en Computer Science (CS); 428838 bytes application/pdf application/pdf
spellingShingle Data integration
heterogeneous sources
ontology
scalability
Zhu, Hongwei
Madnick, Stuart E.
Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services
title Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services
title_full Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services
title_fullStr Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services
title_full_unstemmed Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services
title_short Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services
title_sort context interchange as a scalable solution to interoperating amongst heterogeneous dynamic services
topic Data integration
heterogeneous sources
ontology
scalability
url http://hdl.handle.net/1721.1/7413
work_keys_str_mv AT zhuhongwei contextinterchangeasascalablesolutiontointeroperatingamongstheterogeneousdynamicservices
AT madnickstuarte contextinterchangeasascalablesolutiontointeroperatingamongstheterogeneousdynamicservices