scholarly journals A Life Cycle Stakeholder Management Framework for Enhanced Collaboration Between Stakeholders with Competing Interests

2011 ◽  
pp. 15-26
Author(s):  
Christina Scandelius ◽  
Geraldine Cohen
Keyword(s):  
Life Cycle ◽  
Stakeholder Management ◽  
Management Framework ◽  
Competing Interests

Model Based on Ontological Engineering as Support for Stakeholder Management

2020 ◽  
pp. 305-338
Author(s):  
Beitmantt Geovanni Cárdenas Quintero ◽  
Flor Nancy Díaz-Piraquive ◽  
Hilma Ximena Fonseca Ruiz
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Project Management ◽  
Information Structure ◽  
Stakeholder Management ◽  
Management Model ◽  
Ontological Engineering ◽  
Model Based ◽  
Complex Knowledge

The objective of this article is a way of working that is used as an instrument for managing the parts with semantic and conceptual elements, such as mastery of management projects, and the effects of ontological engineering techniques, which solves frequently asked questions with respect to information related to this resource. This is done in an agile, precise, and effective way, facilitating its management in the phases that make up the life cycle of the project. The research will contribute to the integration of ontological engineering and project management, enabling the construction of a stakeholder information structure with semantic components that enable it to be the input of a more complex knowledge management model.

Research on Integrated Risk Management Framework of Manufacturing Engineering Project

2011 ◽  
Vol 323 ◽  
pp. 217-221 ◽  
Author(s):  
Yun Li Gao ◽  
Qing Chun Wang
Keyword(s):  
Information System ◽  
Risk Management ◽  
Life Cycle ◽  
Risk Identification ◽  
Engineering Project ◽  
Management Framework ◽  
Risk Management Framework ◽  
Integrated Risk ◽  
Integrated Risk Management ◽  
Total Life

As the scale of investment on projects increases, manufacturing project integrated risk management becomes more important. The content and relationship of the integrated risk manufacturing management framework are discussed in the paper. The framework is composed of five parts which are the integration of risk management targets, total life cycle, processes and methods, organization and information system. In the different phase of total life cycle, depending on the risk management information system, project risk management organization who is in the form of virtue team promotes the risk management loop which is composed of the risk identification, risk evaluation, risk handling and risk monitoring (IEHM), to achieve the project targets. The integrated risk management framework is presented by the systematic method. The framework provides the basis for further development of integrated risk management.

scholarly journals An ontology-based knowledge management framework for a distributed water information system

2012 ◽  
Vol 15 (4) ◽  
pp. 1169-1188 ◽  
Author(s):  
Qing Liu ◽  
Quan Bai ◽  
Corne Kloppers ◽  
Peter Fitch ◽  
Qifeng Bai ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Domain Knowledge ◽  
Heterogeneous Systems ◽  
Semantic Knowledge ◽  
Knowledge Model ◽  
Provenance Information ◽  
Management Framework ◽  
Data Transparency ◽  
Multiple Domains

With the increasing complexity of hydrologic problems, data collection and data analysis are often carried out in distributed heterogeneous systems. Therefore it is critical for users to determine the origin of data and its trustworthiness. Provenance describes the information life cycle of data products. It has been recognised as one of the most promising methods to improve data transparency. However, due to the complexity of the information life cycle involved, it is a challenge to query the provenance information which may be generated by distributed systems, with different vocabularies and conventions, and may involve knowledge of multiple domains. In this paper, we present a semantic knowledge management framework that tracks and integrates provenance information across distributed heterogeneous systems. It is underpinned by the Integrated Knowledge model that describes the domain knowledge and the provenance information involved in the information life cycle of a particular data product. We evaluate the proposed framework in the context of two real-world water information systems.

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