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Application of Ontology in Management - Essay Example

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The paper "TApplication of Ontology in Management" goes on to identify the advantage of ontology evolution, the lack of a systematic approach for ontology evolution, and explains the motivation for this study. The chapter ends with the objectives of the study and the thesis structure…
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Application of Ontology in Management
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? Chapter Introduction 1 Introduction With the current globalisation, which has affected every aspect of human’s life has eventually affected many society and has then led to a rapid growth on technology and business competitions. Teamwork a plays significant role in business whereby there is a need to have a shared knowledge representation to ensure that business’ objectives are attained. The dynamic nature of human being means that individual knowledge is changing in a constant basis. This requires ontology to evolve accordingly. In this first chapter, an introduction to (i) Ontology definitions, (ii) Ontology Editor and (iii) Ontology Evolution is presented. The chapter goes on to identify the advantage of ontology evolution, the lack of systematic approach for ontology evolution and explains the motivation for this study. The chapter ends with the objectives of the study and thesis structure. 1.2 Ontology Definitions The term “Ontology” is derived from its usage in philosophy where it means the study of being or existence as well as the basic categories (Witmer 2004). Therefore, it is now used to refer to what exists in a system model. Definition 1: According to the Merriam-Webster Dictionary (2011), “It is a particular nature of being or the kinds of things that have existence. Definition 2: Gruber (1993), on the other hand, provides a more concrete definition of Ontology. He defines it as a study which explicitly explains concepts and relationships (Gruber 1993). The set of concepts (e.g. classes, relations, functions) are used to represent and describe domain knowledge. For example, in oil and gas industry there is an established ontology for Statoil in Norway (Association 2008) a standard library related to an oil and gas domain. 1.3 Ontology Editor Ontology Editor is an application which is developed to view and edit ontology. In the past few years many applications have been developed such as OilEd (Bechhofer, Horrocks et al. 2001), OntoEdit (Sure, Erdmann et al. 2002), Protege (Gennari, Musen et al. 2003) and Web-Protege (Tudorache, Vendetti et al. 2008). Further details are explained below about each ontology editor: - OilEd: OilEd was developed in Manchester University. It is a simple ontology editor that provides further guidance in the development of Ontology Interchange Language (OIL)-based ontologies (Bechhofer, Horrocks et al. 2001), which is basically a web-based representation of ontologies organized to make it accessible and usable (Cover, 2000). It is the one which pioneers ontology editing (Bechhofer, Horrocks et al. 2001). - OntoEdit: OntoEdit was developed by the Knowledge Management Group at University of Karsnuhe Institute AFIB. It provides an ontology development that allows collaboration and inferencing. The method involves three main steps which start with requirements specification, refinement and evaluation. The first step is where the ontology engineers and domain experts meet and work towards identifying the goal of the ontology, description of the domain, and the availability of references. Design guidelines are also established in this step. Then, the team then makes the ontology in the refinement phase. Finally, the ontology requires evaluation according to its requirements specification by identifying possible errors in the ontology and efficiency for enabling collaborative work (Sure, Erdmann et al. 2002). - Protege: Protege was developed by Mark Musen at Stanford University. It is an ontology editor which has come a long way. Protege started in 1987 as a small application, which was aimed at building knowledge acquisition tools. Protege has then been developed further, providing many new features for each version that has been released. Currently, there are hundreds of individuals and research groups are using Protege (Gennari, Musen et al. 2003). - Web-Protege: Web-Protege is a web version of Protege, also developed in Stanford University. This allows the users who have access to view and edit the ontology from the internet (Tudorache, Vendetti et al. 2008). However, this research will focus on Web-Protege due to its ease of availability where people from different locations are able to use it. 1.4 Ontology Evolution Ontology Evolution in the context of this research relates to the instances where Ontology requires a change or has changed within the lifetime of a specific domain. Evolution is considered in two senses: (i) evolution of generic (concept level), (ii) or evolution of specific project data (instances level). The concept level reflects new kinds of software, application or system being developed on broader and different understandings (Qin and Atluri, 2009). For example, in oil and gas domain, a new safety procedure has been created and introduced to the market that requires adding a new procedure into the ontology The instance level reflects project development, changes in the software requirements and in the design process to either incorporate additional functionality to software, application and system or allow incremental improvement (Qin and Atluri, 2009). For example, in manufacturing sector such as automotive industry, one type of car that is found to have faulty in production level is extracted that requires removing or moving this particular product to a different class. This includes the re-design of the ontology based on changes in the organization’s requirements or interests. These changes take the form of an understanding of the domain looked at; discovering a problem within the original concept of the domain; or, finally, developing a new product or function within the domain (Qin and Atluri, 2009). In summary, these changes can be summarized into three causes: (i) Change in Domain; (ii) Change in shared conceptualisation: and (iii) change in specification. Below are further explanations for each one of them: ? Changes in Domain: This change is quite common these days and it has been known within the area of database schema versioning (Qin and Atluri, 2009). This can apply in cases where two departments are merging, which will require a further change in the ontology (Klein and Fensel 2001). However, this research will not consider this type of change as it is out of scope of this research. ? Changes in shared conceptualisation: shared conceptualization change is mainly applied to a change of the user perspective of the concept of a domain. This applies to using the ontology for a new task or in a new domain (Klein and Fensel 2001). For example, the training materials of the students belonging to different demographics (e.g. age group). What works well for one demographic, may not work well for others. In this research, the terms of ontology evolution will look mainly at the this type of change (shared conceptualization). ? Changes in the specification: This is a kind of translation. For instance, a change in the way a conceptualization is recorded within the ontology (Klein and Fensel 2001). However, this research will not consider this type of change as it is out of scope of this research. 1.5 Advantages of Ontology Evolution The problem with ontology in an always changing business context is the fact that ontology does not evolve at the same pace as the business itself. In a particular sector, for example in the oil and gas sector, an updated ontology is crucial. Delays or even failure to transfer data and to change the ontology in a timely manner will result in great losses within an industry. Therefore, an ontology evolution platform has become a vital part in business with advantages such are: (i) Error reduction, (ii) Cost saving, (iii) Increased involvement of users (Qin and Atluri, 2009). 1.5.1 Error Reduction Due to the daily operational work an updated ontology is an imperative part for organizations to reduce errors within their daily processes as a delayed information lead to uninformed decisions. For example, information on a sudden temperature change will compel staff on offshore office to postpone drilling activities. This information is vital in keeping the safety of the offshore staff. Therefore, due to daily critical operational work, it is vital to receive the information instantaneously to reduce any errors that may occur (Thorsen and Rong 2008). 1.5.2 Cost Saving Businesses need to incorporate changes and new information on their daily business activities to decrease unnecessary costs. This is achieved by regular update of ontology. For example, there are issues related to certain proportions of oil and water during drilling processes that have to be maintained by the offshore staff to ensure high quality oil. A high percentage of water will impact on the quality of drilled oil. Pre-drilling oil discovery must thus be performed to ensure the extraction of high quality oil. If the offshore staff persists in drilling without the pre-drilling oil discovery and low quality oil is extracted, machines that have been used to drill on false information was less useful. Therefore, by allowing all the staff (Onshore and Offshore staff) to report any issues within the process will provide a huge saving to the oil and gas industries. 1.5.3. Increase Involvement of Users In an organisation, the manager will identify the need to revise ontology where an ontologist will perform the actual change, simply because the members of the hiring organization does not have the enough expertise to make the ontology. The ontologist, on the other hand, does not have the first-hand information optimally needed to change the ontology. In addition, the use of ontology by organization presents a problem because it needs to be agreed upon amongst the members. 1.6. Lack of Systematic Approach for Ontology Evolution There are two approaches available in the field of ontology evolution which have contrasting viewpoint. The first approach perceives an active role of users # ADDIN EN.CITE # ADDIN EN.CITE.DATA #(Klein 2004; Stojanovic 2004; Vrandecic, Pinto et al. 2005; Noy, Chugh et al. 2006) whereby a modification of the existing ontology is a result of collaborative efforts among ontology developers, engineers, editors and experts. On the other hand, the second approach delegates the task of ontology evolution to machines where collaborative efforts are performed in an automated manner (Alani, Harris et al. 2006; Bloehdorn, Haase et al. 2006; Novacek, Laera et al. 2007). Although human-based ontology evolution is preferred, there are two issues need to be addressed with regard to expertise and geographic boundary. The first issue occurs when ontology is modified manually and it requires people with sound knowledge of ontology to perform the actual modification. This means Ontologist, or someone with the same expertise, has to be employed by an organisation. In real-world situation, it is safe to assume that many organisations find this to be impractical. The second issue relates to the different locations from which business activities are carried out. Nowadays, companies are operating in various countries and regions. In many cases, different segments of business are performed in different parts of the world. For example, Australian-based clothing company Bonds has a Head Office in New South Wales but has a factory in China where clothing is produced (Sharp and Zappone 2009). Some business sectors even have to operate in dispersed locations as part of their business. The geographic distance between offices, different time zones and business environment on which the company has to operate will influence organisation’s approach in conducting their business. One example of such sectors is oil and gas. Business activities within oil and gas industry are managed by staff that are working from offshore and onshore offices. In addition, these offices are most likely to be dispersed around the globe creating issues such as delayed transfer of information. 1.7 Motivation of Study on Ontology Evolution As described earlier, ontology evolution brings monetary as well as non-monetary advantages for businesses. The importance of an updated ontology in business context is indisputable especially to particular type of business where activities are managed from dispersed locations. Within this context, a failure to manage these diversities will create disadvantage to the companies. Moreover, due to the wide and distributed location of the staff, it is vital to have an updated ontology to process the work on updated data. The following motivations have initiated the search for possible answers in this study. 1.7.1 Updated Ontology Ontology is a vital part of the daily activities of business organisations, for example, in oil and gas industry. Within this particular business sector, ontology needs to be updated all the time in order to increase the productivity and reduce operational errors and maintenance costs, which saves a company millions of dollars (Thorsen and Rong 2008). Furthermore, due to the involvement of all staff in updating the ontology as described in previous section, ontology evolution will occur more frequently. Therefore, the changes in the instance level in oil and gas ontology are an important part in enabling onshore and offshore staff to operate in a more efficient and effective way. 1.7.2 Improve Collaborative Communication As briefly explained in previous sections, business activities are not bounded by geographical facet. Companies are known to have offices established in many areas within the world with many branches to operate. This makes the communication between staff much harder than if they are working on the same location. Staff who works in different conditions will have a different reaction to different issues resulting in different perceptions and knowledge. Furthermore, the information between geographically-dispersed branches is not fully integrated. This leads to a loss of vital information that can be transformed into useful knowledge. In order to overcome the loss, companies should enhance the communication between scattered offices. Within this context, a platform will provide further opportunities to enhance the much needed communication to develop and change ontology when required. 1.8 Research Objectives In the above sections, a description of the need for ontology evolution has been explained. By developing a platform that allows better communication amongst staffs, the company will benefit from reduction in errors, economic benefits, higher productivity, and systematic information. Therefore, there are two main research objectives for this study: Objective 1: To develop an approach to enhance the collaborative communication between different participants who are working from scattered offices. Objective 2: To engage increasing numbers of participants in ontology evolution so that staffs are more aware of changes and more actively involved in the change. Both objectives will help to increase the involvement of staff who is working from diverse locations to enable ontology evolution process. The platform will help the staff to understand and to participate in resolving the outdated ontology. Also, the objectives address the problems and issues associated with geographically-dispersed staff and the best ways to communicate with one another. 1.9 Thesis Structure The thesis is then structured as follows: Chapter 1 – Introduction which is this chapter. Chapter 2 – A review of the literature related to Ontology Evolution, Ontology Editor and Plug-ins, Knowledge Management, Formal Social Networking - Wiki and Informal Social Networking is presented. At the end of the chapter, a critical evaluation is made to provide an integrated perspective. Chapter 3 – The chapter starts by describing the problem overview. Two main problems facing a Community Support and Platform for Ontology Evolution are discussed, and this corresponds to the two main research issues. The first research issue is the Lightweight Community Support, which refers to a lack of communication between remote users. The second issue is the Ontology Evolution Platform which supports the users to allow ontology to evolve. The chapter continues by presenting two main solution requirements for these problems. A case of oil and gas industry is introduced, and at the end of the chapter, an engineering based research approach is presented. Chapter 4 – This chapter outlines the proposed solution. It starts by giving an overview of the solution and strategy of the proposed solution. Then the conceptual framework for Lightweight Community Driven Approach is explained, wherein the three layers are discussed in detail. The three layers are: (i) Social Networking Layer, (ii) Permission Layer, and (iii) Ontology Evolution Layer. The chapter continues discussing the advantages and disadvantages of Lightweight Community Driven Approach. Next, the chapter describes the Lightweight Community Driven Approach as a Solution for communication. Finally, the platform as a Solution for ontology evolution is presented. The discussion includes roles of responsibilities, Ticketing Support System and the differences and similarities between Community Forums and Ticketing Support Systems. Chapter 5 – (will be added once pseudo codes are ready) Chapter 6 – This chapter describes the proof of concepts of the proposed platform. It starts with platform requirements for Lightweight Community Support and Ontology Evolution Platform. An illustration of the proposed solution is given. This includes how the platform is populated, modified and deleted. The features discussed include Login, Issue, Project, Vote, Vote Results. The chapter further presents the sample of Oil and Gas Ontology which has been created for demonstrating the evolution process of ontology in oil and gas domain. This includes classes, properties and individuals. The chapter ends with a conclusion. Chapter 7 – The final chapter presents the issues and corresponding solutions for Lightweight Community Support and Ontology Evolution Platform. Finally, i also discusses the suggestions for future work. 1.10 Conclusion In this chapter, an introduction of ontology definition, ontology editor and ontology evolution are given. It continues with identifying the advantage of ontology evolution as well as acknowledgement of the lack of a systematic approach towards ontology evolution. This chapter then enumerates the motivation of this research and objectives. In conclusion, the thesis structure is presented. In the next chapter, a review of literature relating existing ontology editors and plug-ins and two main types of social network is discussed. 1.11 References Alani, H., S. Harris, et al. (2006). Winnowing ontologies based on application use. Proceedings of 3rd European Semantic Web Conference. Association, P. C. (2008). "POS Caesar Association." Retrieved March 16, 2010, from http://projects.dnv.com/reference_data/RD4Browser/default.aspx. Bechhofer, S., I. Horrocks, et al. (2001). OilEd: A Reason-able Ontology Editor for the Semantic Web. KI 2001, Vienna, Austria Bloehdorn, S., P. Haase, et al. (2006). Ontology Evolution, John Wiley & Sons. Cover, Robin ed. (2000). Ontology Interchange Language (OIL). Available at: http://xml.coverpages.org/oil.html. Date accessed: May 15, 2011. Flouris, G., D. Plexousakis, et al. (2006). Evolving ontology Evolution. SOFSEM 2006. Merin, Czech Republic. 3831/2006: 14-29. Gennari, J. H., M. A. Musen, et al. (2003). "The evolution of Protege : an environment for knowledge-based systems development." International Journal of Human-Computer Studies 58(2003): 89 - 123. Gruber, T. (1993). Toward Principles for the Design of Ontologies Used for Knowledge Sharing. International Workshop on Formal Ontology, Padova, Italy. Klein, M. (2004). Change management for distributed ontologies. Amsterdam, Vrije Universiteit. PhD Thesis. Klein, M. and D. Fensel (2001). Ontology versioning on the Semantic Web. International Semantic Web Working Symposium (SWWS), Stanford University, California, USA. Merriam-Webster Dictionary (2011). Ontology. Available at: http://www.merriam webster.com/dictionary/ontology. Date accessed: May 15, 2011. Novacek, V., L. Laera, et al. (2007). Semi-automatic integration of learned ontologies into a collaborative framework. IWOD. Noy, N. F., A. Chugh, et al. (2006). A Framework for Ontology Evolution in Collaborative Environments. 5th International Semantic Web Conference 2006, Athens, USA. Qin, L. and Atluri V. (2009). “Evaluating the Validity of Data Instances Against Ontology Evolution Over the Semantic Web.” Information and Software Technology 51: 83-97. Sharp, A. and C. Zappone. (2009). "West End factory to close as Bonds goes offshore." Retrieved December, 4 2009, from http://www.brisbanetimes.com.au/articles/2009/02/25/1235237708475.html. Stojanovic, L. (2004). Methods and Tools for Ontology Evolution. Karslruhe, FZI - Research Center for Information Technologies. PhD Thesis. Sure, Y., M. Erdmann, et al. (2002). OntoEdit: Collaborative Ontology Development for the Semantic Web. International Semantic Web Conference 2002 (ISWC'02), Sardinia, Italy Thorsen, K. and C. Rong (2008). Data Integration in Oil and Gas at Norwegian Continental Shelf. 22nd International on Advanced Information Networking and Applications - Workshop, Okinawa, Japan. Tudorache, T., J. Vendetti, et al. (2008). Web-Protege: A Lightweight OWL Ontology Editor for the Web. OWL: Experiences and Direction (OWLED) Workshop, Karslruhe, Germany. Ventrone, V. and S. Heiler (1991). "Semantic Heterogeneity as a Result of Domain Evolution." SIGMOD Record (ACM Special Interest Group on Management of Data) 20(4): 16 - 20. Vrandecic, D., H. S. Pinto, et al. (2005). "The diligent knowledge processes." Journal of Knowledge Management 9: 85 - 96. Read More
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