A Collaborative Framework Supporting Ontology Development Based on Agile and Scrum Model

Abstract

Ontology describes concepts and relations in a specific domain-knowledge that are important for knowledge representation and knowledge sharing. In the past few years, several tools have been introduced for ontology modeling and editing. To design and develop an ontology is one of the challenge tasks and its challenges are quite similar to software development as it requires many collaborative activities from many stakeholders (e.g. domain experts, knowledge engineers, application users, etc.) through the development cycle. Most of the existing tools do not provide collaborative feature to support stakeholders to collaborate work more effectively. In addition, there are lacking of standard process adoption for ontology development task. Thus, in this work, we incorporated ontology development process into Scrum process as used for process standard in software engineering. Based on Scrum, we can perform standard agile development of ontology that can reduce the development cycle as well as it can be responding to any changes better and faster. To support this idea, we proposed a Scrum Ontology Development Framework, which is an online collaborative framework for agile ontology design and development. Each ontology development process based on Scrum model will be supported by different services in our framework, aiming to promote collaborative activities among different roles of stakeholders. In addition to services such as ontology visualized modeling and editing, we also provide three more important features such as 1) concept/relation misunderstanding diagnosis, 2) cross-domain concept detection and 3) concept classification. All these features allow stakeholders to share their understanding and collaboratively discuss to improve quality of domain ontologies through a community consensus.

A Systematic Literature Review of The Role of Ontology in Modeling Knowledge in Software Development Processes

“…This is an inconsistency and needs further investigation. Likewise, the role of ontology is to describe the concept and relation between classes and knowledge representation [22] .…”

“…Knowledge abstraction [11] . The heterogeneous data and rapid change in software requirements [14] can make an impact on the limited understanding of software requirements [11] , and it can be handled by developing a collaborative framework ontology and scrum agile software engineering [22] .…”

“…Freq Study Modeling the Data in software development 5 Bhatia et al [2] , Valiente et al [11] , Puchianu and Bautu [18] , Rocha et al [19] , Beydoun et al [20] Database and application integration 5 Asfand-E-Yar and Ali [3] , Junior et al [4] , Petnga and Austin [21] , Takhom et al [22] , Adnan and Afzal [23] Describe the knowledge using common vocabulary 6 Asfand-E-Yar and Ali [3] , Junior et al [4] , Jannath and S [12] , Petnga and Austin [21] , Takhom et al [22] , Adnan and Afzal [23] To Resolve Requirement change in Software Development 3 Alsanad et al [14] , Gregorio et al [24] Maintenance software testing 2 Popereshnyak and Vecherkovskaya [1] , García-Peñalvo et al [13] Building the concept of software quality 1 Alsanad et al [14] Developing systems in data integration 1 John et al [25] Application pattern in software development 1 Deb et al [26] Software development model 1 De Graaf et al [27] Techniques for detecting changes to software systems 1 Peldszus et al [28] Software development process 1 Abdalazeim and Meziane [29] Software data model 1 Dahling et al [30] Software development data model process 1 Olszewska and Allison [31] Modeling software knowledge 1 Wen and Katt [32] Tools for building software 1 Stadnicki et al [33] Technical model software 1 Zou et al [34] Software engineering process 1 Murtazina and Avdeenko [35] Software development process 2 Wongthongtham et al [36] , Ortega-Ordoñez et al [37] Software measurement & systems Integration 1 Fonseca et al [38] Real-time...…”

“…This could lead to a greater effortlessness of communication by combining the approved ontology system knowledge, the domain knowledge, and the principles and best-practices of software engineering practices into a publicly accessible resource platform and let the resources to be accessible by all member of the teams within the organization. [14] Developing a multilevel ontology framework [14] Knowledge abstraction [11] The heterogeneous data and rapid change in software requirement [14] Limited understanding of software requirements [11] Developing a collaborative framework ontology and scrum agile software engineering [22] . Limited knowledge of malware detection [12] The android OS version introduces runtime permission to user privacy, so it needs more time to detect and analyze the malware behavior Consume more time detecting mobile malware Evaluation when integrating ontology with others [4] The evaluation ontology with other applications involved in two organization Limited the integration solution that has been produced…”

A conceptual model for ontology quality assessment

“…In addition to that, agile ontology development methodologies have been introduced by adopting agile principles and practices in software engineering. These include methodologies such as SAMOD [109], XD [18,30], AMOD [1] and CD-OAM framework [129]. Out of these, only SAMOD and XD discussed the evaluation (i.e., model test, data test, unit test) of ontologies at least in a nutshell.…”