A framework for managing information from heterogeneous, distributed, and autonomous sources in the architecture, engineering, construction, and facilities management domain

This dissertation proposes a framework that allows different efforts aiming to enhance information management in the architecture, engineering, construction, and facilities management (AEC/FM) industries, to coexist and support each other by sharing resources, services, and outputs. The main motivation for this research was the lack of support for non-routine tasks and business agility in information systems serving the domain. An extensive analysis of information needs and available solutions identified the domain heterogeneity and complexity as key challenges for successful information management and efficient communication between a wide range of human and machine participants as a missing link. Suggesting that such communication needs to involve all components of human-to-human communication: syntax, semantics, and pragmatics, the existing information-management resources and approaches were analyzed within the semiotic framework, in order to identify shared simple elements that can be used to relate them. The proposed framework identifies three basic types of assertions: senses, relationships, and information, and their two properties: category and scope, as a set of basic elements that can be used to relate all kinds of semantic resources as well as information-management approaches based on linguistics, information-retrieval theory and practice, document structure, and knowledge representation. The framework enables consistent management of different types of information at any level of granularity and correlation of assertions involving information, its subject- and context-domains. A pilot implementation demonstrated on a small scale how the proposed framework can be used in practice. The envisioned system consists of numerous and diverse components that share their content via Web services using the proposed framework and a set of shared resources that include registries and specialized services offering senses (i.e. terminology mapping and resolution) and relationships (i.e. conceptualizations). The research uses a combination of constructive and exploratory method. The basic framework was validated by the ability to express all types of semantic resources and the pilot implementation by the comparison to a set of predefined requirements. However, the real benefits of the proposed framework can be proven only when it is used in combination with a variety of existing, emerging, and future techniques in complex real-world environments, as intended.