Knowledge Modeling Research Papers - Academia.edu (original) (raw)

Building Information Modelling (BIM) is a set of technologies, processes and policies enabling multiple stakeholders to collaboratively design, construct and operate a facility. There are numerous challenges attributed to BIM adoption by... more

Building Information Modelling (BIM) is a set of technologies, processes and policies enabling multiple stakeholders to collaboratively design, construct and operate a facility.
There are numerous challenges attributed to BIM adoption by industry and academia. These represent a number of knowledge gaps each warranting a focused investigation by domain researchers. This study does not isolate a single gap to address but espouses a holistic view of the knowledge problem at hand. It contributes to the discussion a set of conceptual constructs that clarify the knowledge structures underlying the BIM domain. It also introduces a number of practicable knowledge tools to facilitate BIM learning, assessment and performance improvement.
This study is delivered through complementary papers and appendices to answer two primary research questions. The first explores the knowledge structures underlying the BIM domain whilst the second probes how these knowledge structures can be used to facilitate the measurement and improvement of BIM performance across the construction industry.
To address the first question, the study identifies conceptual clusters underlying the BIM domain, develops descriptive taxonomies of these clusters, exposes some of their conceptual relationships, and then delivers a representative BIM framework. The BIM framework is composed of three-axes which represent the main knowledge structures underlying the BIM domain and support the development of functional conceptual models.
To address the second question, BIM framework structures are extended through additional concepts and tools to facilitate BIM performance assessment and development of individuals, organizations and teams. These additional concepts include competency sets, assessment workflows and measurement tools which can be used to assess and improve the BIM performance of industry stakeholders.
In addressing these research questions, a pragmatic approach to research design based on available literature and applicable theories has been adopted. By combining several research strategies, paradigms and methods, this study (1) generates several new conceptual structures (e.g. frameworks, models and taxonomies) which collectively clarify the knowledge structures underlying the BIM domain; and (2) develops a set of workflows and tools that facilitate BIM assessment, learning and performance improvement.
This study delivers an extendable knowledge structure upon which to build a host of BIM performance improvement initiatives and tools. As a set of complementary papers and appendices, the study presents a rich, unified yet multi-layered environment of conceptual constructs and practicable tools; supported by a common framework, a domain ontology and simplified visual representations. Individually, each paper introduces a new framework part or solidifies a previous one. Collectively, the papers form a cohesive knowledge engine that generates assessment systems, learning modules and performance improvement tools.

Within the (E-)Power research program a new approach for supporting the chain of processes from the creation of legal texts to the implementation of normative (juridical) information systems has been developed. According to this approach... more

Within the (E-)Power research program a new approach for supporting the chain of processes from the creation of legal texts to the implementation of normative (juridical) information systems has been developed. According to this approach cre- ating formal knowledge models starts with the analysis of the legal text. This process executed by knowledge analysts is very time consuming. Within the

Researchers in the ontology-design field have developed the content for ontologies in many domain areas. Recently, ontologies have become increasingly common on the World- Wide Web where they provide semantics for annotations in Web... more

Researchers in the ontology-design field have developed the content for ontologies in many domain areas. Recently, ontologies have become increasingly common on the World- Wide Web where they provide semantics for annotations in Web pages. This distributed nature of ontology development has led to a large number of ontologies covering overlapping domains. In order for these ontologies to be reused,

Concept maps are an effective way of representing a person’s understanding of a domain of knowledge. Technology can further help by making it easy to construct and modify that representation, to manage large representations for complex... more

Concept maps are an effective way of representing a person’s understanding of a domain of knowledge. Technology can further help by making it easy to construct and modify that representation, to manage large representations for complex domains, and to allow groups of people to share in the construction of the concept maps. CmapTools is a software environment developed at the Institute for Human and Machine Cognition (IHMC) that empowers users, individually or collaboratively, to represent their knowledge using concept maps, to share them with peers and colleagues, and to publish them. It is available for free for educational and not-for-profit organizations, and public servers have been established to promote the sharing of knowledge. The client-server architecture of CmapTools allows easy
publishing of the knowledge models in concept map servers (CmapServers), and enables concept maps to be linked to related concept maps and to other types of media (e.g., images, videos, web pages, etc.) in other servers. The collaboration features enable remote users to asynchronously and/or synchronously collaborate in the construction of concept maps, and promote comments, criticism, and peer review. Public CmapServers have resulted in a large collection of knowledge models publicly available, constructed by users of all ages in a variety of domains of knowledge and from a large number of countries.

Lean supply chain management is a relatively new concept resulting from the integration of lean philosophy into supply chain management. Decision making in a lean supply chain context is challenging because of the complexity, dynamics,... more

Lean supply chain management is a relatively new concept resulting from the integration of lean philosophy into supply chain management. Decision making in a lean supply chain context is challenging because of the complexity, dynamics, and uncertainty inherent to both supply networks and the types of waste (defined as any processes, including use of resources, which do not add value to customers). Efficient knowledge management has been identified as one of the key requirements to achieve integrated support for lean supply chain decisions. This paper proposes a decision-focused knowledge framework including a multi-layer knowledge model (to capture the know-why and know-with together with the know-what and know-how), a knowledge matrix for knowledge elicitation, and a decision tree for the design of the knowledge base. A knowledge system for lean supply chain management (KSLSCM) has been developed using artificial intelligence system shells VisiRule and Flex. The KSLSCM has five core components: a supply chain decision network manager, a waste elimination knowledge base, a knowledge refinement module, an inference engine, and a decision justifier. The knowledge framework and the KSLSCM have been evaluated through an industrial decision case. It has been demonstrated through the KSLSCM that the decision-focused knowledge framework can provide efficient and effective support for collaborative decision making in supply chain waste elimination.

An experiment manipulated source expertise, source bias, and message format. The findings reveal that expert sources are expected to quantify message claims whereas non-expert sources are not. Persuasion is greater when these expectations... more

An experiment manipulated source expertise, source bias, and message format. The findings reveal that expert sources are expected to quantify message claims whereas non-expert sources are not. Persuasion is greater when these expectations are met versus when the source and the message format are incongruent, but only when the source also has self-interest in the advocacy. It appears that source-message incongruity and source bias focus attention on the source and, in combination, lead to negative inferences about the source's manipulative intent. This interpretation is consistent with the Persuasion Knowledge Model (Friestad and Wright 1994).

Semantic interoperability, a prerequisite to eHealth projects, relies on sharing both information and knowledge models between information systems. Two of the standards of information models are HL7 v3 and the European norm,... more

Semantic interoperability, a prerequisite to eHealth projects, relies on sharing both information and knowledge models between information systems. Two of the standards of information models are HL7 v3 and the European norm, EN13606/OpenEHR. The paper compares both standards on a fragment of the prenatal medical record, the APGAR score. Two factors are compared: the formal representation of both information models, and the binding to knowledge models. The HL7v3 perinatality DMIM specification and the OpenEHR APGAR archetype were used. HL7v3 appears to be more formal than OpenEHR and able to represent in an easier way the clinical context. For both standards, the binding to reference terminologies such as LOINC is poor. We provide recommendations to improve the standards.

Ontology patterns have been pointed out as a promising approach for ontology engineering. The goal of this paper is to clarify concepts and the ter- minology used in Ontology Engineering to talk about the notion of ontology patterns... more

Ontology patterns have been pointed out as a promising approach for ontology engineering. The goal of this paper is to clarify concepts and the ter- minology used in Ontology Engineering to talk about the notion of ontology patterns taking into account already well-established notions of patterns in Software Engineering.

The situation today is quite different from what we have been used to. The globalization and the availability and use of Internet have changed our view of knowledge, learning, and examination. We will here, however, use a very old... more

The situation today is quite different from what we have been used to. The globalization and the availability and use of Internet have changed our view of knowledge, learning, and examination. We will here, however, use a very old knowledge model in our presentation, that of Aristotle with his three components: Episteme, Techne, and Fronesis. Episteme covers the most common

Groupware Task Analysis is a task analysis method that deals with the context of use of a system in the broadest sense. The task world is seen from three viewpoints that deal with different aspects of the world. The processes of GTA and... more

Groupware Task Analysis is a task analysis method that deals with the context of use of a system in the broadest sense. The task world is seen from three viewpoints that deal with different aspects of the world. The processes of GTA and their background are described in detail. In addition a task analysis tool EUTERPE is described. EUTERPE is based on GTA and allows capturing of the task models and provides some basic analysis primitives.

Abstract. The OSAM*.KBMS is a knowledge-base management system, or the so-called next-generation database management system, for non-traditional data/knowledge-intensive applications. In order to define, query, and manipulate a knowledge... more

Abstract. The OSAM*.KBMS is a knowledge-base management system, or the so-called next-generation database management system, for non-traditional data/knowledge-intensive applications. In order to define, query, and manipulate a knowledge base, as well as to write codes to implement any application system, we have developed an object-oriented knowledge-base programming language called K to serve as the high-level interface of OSAM*.KBMS. This paper presents the design of K, its implementation, and its supporting KBMS developed at the Database Systems Research and Development Center of the University of Florida.