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 ◽  
...  

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.

2005 ◽  
Vol 30 (4) ◽  
pp. 65-76 ◽  
Author(s):  
Sangeeta Shah Bharadwaj ◽  
Kul Bhushan C Saxena

Information technology (IT) organizations, especially software development organizations, are knowledge-intensive firms where the knowledge is mainly embedded in human beings and is largely in the form of tacit knowledge. Managing knowledge in global software teams in very critical as knowledge is a source of competitive advantage for these organizations. They have adopted emergent team-based structures as a response to changing business needs and are globally distributed. Sharing of tacit knowledge requires more people-to-people interaction which is impossible in these organizations. Due to this reason, it is essential to manage certain critical knowledge during the progress of the projects related to achieving the performance goals and the learning goals to consistently sustain and improve project performance. This study identifies the following critical knowledge areas related to the learning goals: user requirements knowledge functional domain knowledge technical knowledge project status knowledge project experience knowledge. A five-layered knowledge management framework has been applied to model the software team knowledge. This model is suggested as a process approach to team knowledge management to strengthen knowledge management in software teams. As per the knowledge management framework, all the identified knowledge related to the project are not well managed. One of the reasons for not managing well a particular type of knowledge is the absence of knowledge management processes. The global software teams share knowledge through a virtual space as against real physical platform with proper IT infrastructure in place. Due to the distributed nature of the teams, rules, conventions, and sharing of norms is already put in place. It, thus, helps in managing project status knowledge, domain knowledge, and technical knowledge. It also promotes management of requirements knowledge and project experience knowledge. However, only ad hoc processes which are immature are in place to manage the knowledge areas. The tools of team knowledge management and leadership commitment are the next two layers of the model to manage the software team knowledge. This study summarizes the status of the following critical knowledge areas related to the learning goals: The most critical knowledge area is the user requirement knowledge. Though newer processes are introduced to manage the same, managing user requirements still remains a challenge for the members of the global software teams. Functional domain knowledge and technical knowledge are managed well by companies but technology updates have put pressure in identifying the gaps and bridging it during the project execution. Project status knowledge has been well managed in the global software teams with the help of formal procedures and documentation. The Capability Maturity Model (CMM) certification requirement of IT organizations is facilitating this knowledge management area. Capturing and reusing the project experience knowledge of the existing projects and clients is still an open issue. The layered knowledge management framework will help in implementing knowledge management processes for each critical knowledge area.


2017 ◽  
Vol 108 ◽  
pp. 386-393 ◽  
Author(s):  
Minglu Wang ◽  
Mingguang Zheng ◽  
Lin Tian ◽  
Zhongming Qiu ◽  
Xiaoyan Li

2011 ◽  
Vol 20 (06) ◽  
pp. 1127-1156 ◽  
Author(s):  
MAXIM DAVIDOVSKY ◽  
VADIM ERMOLAYEV ◽  
VYACHESLAV TOLOK

Ontology instance migration is one of the complex and not fully solved problems in knowledge management. A solution is required when the ontology schema evolves in the life cycle and the assertions have to be transferred to the newer version. The problem may become more complex in distributed settings when, for example, several autonomous software entities use and exchange partial assertional knowledge in a domain that is formalized by different though semantically overlapping descriptive theories. Such an exchange is essentially the migration of the assertional part of an ontology to other ontologies belonging to or used by different entities. The paper presents our method and tool for migrating instances between the ontologies that have structurally different but semantically overlapping schemas. The approach is based on the use of the manually coded transformation rules describing the changes between the input and the output ontologies. The tool is implemented as a plug-in for the ProjectNavigator prototype software framework. The article also reports the results of our three evaluation experiments. In these experiments we evaluated the degree of complexity in the structural changes to which our approach remains valid. We also chose the ontology sets in one of the experiments to make the results comparable with the ontology alignment software. Finally we checked how well our approach scales with the increase of the quantity of the migrated ontology instances to the numbers that are characteristic to industrial ontologies. In our opinion the evaluation results are satisfactory and suggest some directions for the future work.


2011 ◽  
Vol 7 (4) ◽  
pp. 70-84
Author(s):  
Sung-kwan Kim ◽  
Joe Felan ◽  
Moo Hong Kang

Modeling approaches are gaining popularity in knowledge management (KM), especially in specifying knowledge contents. This paper addresses the enterprise knowledge modeling. An enterprise knowledge model provides users with an integrated, holistic view of organizational knowledge resources. Employing a reliable methodology is critical to building successful enterprise knowledge models. A good methodology provides an effective and efficient mechanism for developing a model. This paper first reviews the enterprise knowledge modeling (EKM) and its methodologies. An ontology-based EKM (OBEKM) methodology is proposed. Its products, procedures, and modeling language are described. The methodology is then applied to the construction of a shipping company’s knowledge model for demonstration.


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