Semantic depth and markup complexity

In order to achieve interoperability among heterogeneous systems, markup languages such as XML and DAML are being used to describe distributed systems and data. The ability to successfully interoperate based on semantic markup depends on the ability to create, use and manage shared ontologies of concepts and their interrelationships. Specifically, communicating systems in a networked environment have to achieve a certain level of semantic agreement for them to understand and process exchanged data. A challenging question is how deep the semantic agreement has to be in order to satisfy the communication needs in an environment. Additionally, what is the markup complexity resulting from pursuing that depth of semantic agreement? This paper introduces the concept of semantic depth and markup complexity and proposes models to measure the markup complexity. Furthermore, it is shown that markup complexity can be reduced by employing hierarchical ontologies after partitioning the domain into smaller sub-domains.

1 Introduction

Distributed computing is migrating from tightly coupled architectures to loosely coupled distributed environments. Many new technologies such as Grid computing [6] and Web Service [1] are being developed to expedite this migration. In a loosely coupled environment, computing and data resources are located throughout networks and may not be centrally created or administered. In order to achieve interoperability among heterogeneous systems, markup languages such as Extensible Markup Language (XML) and DARPA Agent Markup Language (DAML) [2] are being used to describe distributed systems and data.