Knowledge-based Workflow Ontology for Group Organizational Structure

Abstract

The workflow model represents the set of steps performed by different entities and their execution ordering to control and manage the carried out process on organization. In which, the structure organizational determines the division of labor in order to persons perform the organization process in an appropriated manner. In collaborative applications, this structure determines how the interaction among users, as well as between the users and the application, are carried out. For this reason, a workflow to manage the group organizational structure will be ideal. Although, workflow lacks the expressive power to represent the domain knowledge and the sequence of operations. An ontology describes the knowledge domain through concepts, relations, axioms and instances, but ontology does not specify how these entities should be used and combined. Therefore, in this paper a workflow ontology to control the group organizational structure is proposed. A case study is presented to show the use of knowledge-based workflow ontology for this structure.

A Workflow Ontology to support Knowledge Management in a Group’s organizational structure

“…CSCW systems are typically large-scale systems, which require solutions in accordance with the behavioral changes of the system, in order to facilitate the work management of the group´s members. The session management policy has been modeled by ontology [11]. On the one hand, this ontology supports and develops, satisfactorily, an organizational structure, so that the structure can adapt itself to changes of group work, and to the different working styles of several organizations or communities.…”

“…Given that knowledge is a portion of all human activities, it is necessary to store it by seizing its meaning, organize it and make it available. This leads to require a base of knowledge to represent the problem domain, as well as be able to reason and draw conclusions through an inference mechanism for the contents of such a base [11]. Therefore, it is essential to capture knowledge related to the system requirements, i.e.…”

“…Ontology is an ideal solution to represent the knowledge domain, using description logic symbols, which allow to specify it in a simple way, which is readable for both humans and machines; as well as to perform much deeper reasoning through the machine [11]. It facilitates a base of knowledge in order to provide semantic, common understanding, communication and knowledge sharing on the domain of interest and a knowledge reasoning, carrying out an inference process to reach to conclusions on this base by a reasoned, inference rules and query languages.…”