Ontology Exemplification for aspocms in the Semantic Web

Ontology Exemplification for aspocms in the Semantic Web Anand Kumar Department of Computer Science Babasaheb Bhimrao Ambedkar University Lucknow-226025, India e-mail: anand_smsvns@yahoo.co.in Sanjay K. Dwivedi Department of Computer Science Babasaheb Bhimrao Ambedkar University Lucknow-226025, India e-mail: skd200@yahoo.com Abstract Explicit modeling of administrative workflow processes and their enactment in workflow systems have proved to be valuable in increasing the efficiency of work in organizations on the basis of distributed information for different parties. The Semantic Web is the provision to provide distributed information with well-defined meaning and understandability for different parties such as machine as well as human. An Agent-based Semantic Web for Paperless Office Content Management System (aspocms) intends to provide paperless environment for administrative offices of universities and institutes. In this paper, we discuss the ontologies framework with their suitable exemplification for aspocms in paperless environment with the emergence of the Semantic Web perspective and show that how the Semantic Web resource description formats and language can be utilized for paperless office content management system of hypertext structures from distributed metadata. The resources of aspocms are domain, user and observation, which are reconnoitered from ontologies and metadata. We consider a logic-based approach for administrative workflow services using TRIPLE, which facilitate the rule and query language for Semantic Web. Keywords- Workflow of Administration, Semantic Web, Web Technology, Rules, Description Logic, TRIPLE, Ontology. I. INTRODUCTION Paperless Office Content Management System has a long tradition of controlled terminologies in respect to workflow of administrative office with Semantic Web perspectives. The vision of the Semantic Web [1, 2] is capable the machines to interpret and process information in order to better support for humans in carrying out their various tasks with web based application. There are several technologies, which have been developed for shaping, constructing and developing the Semantic Web. The developed Semantic Web Technologies [3] provide us with supported tools for describing and annotating resources on the web in standardized ways, e.g. with Resource Description Framework (RDF) [4, 5], RDF Schema (RDFS) [6, 7] and Ontology Web Language (OWL) [8, 9] and its binding to XML (extensible Markup Language) [10]. The RDF provides a language to encode semantically annotated information and RDF Schema (RDF vocabulary) is a language for capturing schema information in terms of a typing system with inheritance and typed relations. Finally, OWL is a logical language that can be used to describe the constrains and possible interpretation of terms used to annotate the information. The information can be found in various resources (like RDF annotations on the documents themselves) i.e. documents, in annotation of these resources in metadata files (like RDF description) or in ontologies. We can think of functionality allowing us to derive new relation between information. In this connection, imagine a situation that a person is writing an electronic complain file (e.g. document related to financial support to a department and section of any higher educational institute and university) for the particular department in paperless environment. The claim file is complained to particular section with authorized user. Especially in the paperless environment, it is very important to overcome the one-size-fits-some approach and provide to competent authority with their individual experience. In one-size-fits-some approach the electronic complain file must be reliable for all users, which involve in the workflow of the files and documents. Now one question that emerges here is how workflow in paperless environment can be described. In order to our solution with respect to workflow in paperless environment, we envision workflow services capable of interpreting metadata-annotated claim files and documents resources understanding their annotations with respect to ontology of workflow and also with respect to top-level ontology, specific domain ontology, task-level ontology and application-level ontology. To deliver the claim files and documents resources, ontologies will be describing the metadata of files and documents and observations about the performance of staff with the user s current profile. Each aspocms [11] services possess reasoning rules for some specific adaptation purposes. These rules the query for resources and metadata, and reason over distributed data and metadata descriptions. A major step for reasoning after having queried user profile, domain ontologies and claim files or documents object is to construct a temporally valid task knowledge base as a base for applying adaptation rules. II. REPRESENTATION OF RESOURCES OF ASPOCMS Semantic Web technologies e.g. Uniform Resource Identifier (URI), Resource Description Framework (RDF), RDF Schema (RDFS) and Ontology Web Language (OWL) make available us with attractive potential. URI is a global naming scheme to identify the resources as Web identifier

by describing its primary access mechanism or by name in a particular namespace. RDF describes the concept of resources and their properties (metadata). The XML is the standard interchange format for RDF on the Semantic Web, although it is not the only format and RDF Schemas serve to define the relations between resources of the RDF documents. OWL represents to define the concepts of resources and relations of RDF and RDFS documents. There is no restriction on the use of different schemas together in one RDF file. The schema identification comes with attributes being used from that schema so backward dereferencing is again easily possible. We can rationalize the expectations of Semantic Web [12] over paperless office content management system in higher educational institutes and universities using Semantic Web technologies. Now, we are trying to represent the resources of Department of Computer Science of any university and institute for aspocms. These resources can be used to achieve the shared and reusability of knowledge within aspocms. The shared and reusability of knowledge provide the global linked knowledgebase to the agent-based applications as well as aspocms. As an example, we are depicted the resources of Department of Computer Science and their metadata in figure 1. We are represented office of Department of Computer Science with resource #DCS_Office_File. triples of subject-predicate-object. There is another language RDFS (RDF Schema) which uses vocabulary to define resources of RDF statements. The RDF statement is hence generated as following, which is depending on RDF graph of related file: Figure 1: Representation of Department related Files as RDF Statements. The above figure shows list of files of #DCS_Office_File such as #DCS_Dispatch_Fil e,#dcs_purchase_file,#dcs_admission_f ile,#dcs_examination_file,#dcs_lab_ma intenance_file,#dcs_imperst_money_fil e,#dcs_bill_guest_faculty_file,#dcs_u GC_Fellowship_File and #DCS_Scholarsh ip_file etc. with dcterms:haspart from Dublin Core metadata terms etc. We examine the above figure in The RDF statement of a file and document can use an attribute dc:title, dc:description, from Doblin Core Metadata Initiative [13] standard together with haspart from Dublin Core metadata terms etc. We can annotate the electronic version of the files and documents with the help of agent-based proposed system. The above RDF Schema provides a simple ontology language. The more powerful ontology language is also available, which reside on the top of RDF and RDF Schema. In order to combine reasoning mechanisms on distributed metadata and data resources, with the intention of generating link structures and to bring the interoperability ideas with an agent-based application. III. BRINGING TOGETHER RESOURCES AND REASONING In Semantic Web tower, we find the layer of rules and logic framework [14] on the top of RDF and ontology layer. In our approach, the communication between reasoning rules and the paperless office content management environment will take place by exchanging RDF annotations. The functions of reasoning is to discover potential relationship with the known relationship and acquire connotative knowledge with given knowledge by

certain logic and rule. The key players of university ontology reasoning is to insure that computer can interpret the information described by university ontology according to formal description of ontology and to discover unknown potential relationship and connotative information with known relationship according to the relation property in ontology of university. We carried out our reasoning by description logics in this paper. By exchanging RDF annotations, the communication between reasoning rules and the open information environment will take place. These reasoning rules are encoded in the TRIPLE rule language. Rule language especially designed for querying and transforming RDF models in TRIPLE [15, 16, 17]. TRIPLE supports namespaces, set of RDF statements reification and rules with syntax close to that of first-order logic. A namespace is a collection of names, which is identifies by a URIref and URIref denotes the common usage of a URI. A namespace declaration is an expression of the form namespaceabbreviation:=namespace. The resources can use these namespaces abbreviation. For example, DCS_Office := #CS_Office_Files. Statements are similar to F-Logic object syntax: An RDF statement (which is a TRIPLE) is written as Subject[Pr edicate Object]. Several statements with the same subject can be abbreviated in the following way: DCS_Office: index.html [rdf:type->doc:document; doc:hasdocumenttype->doc:complainfiles]; IV. DESIGN OF UNIVERSITY ONTOLOGY University ontology is the formalization of concepts sharing among workflow process field. Sharing concepts refers to the concept models of university information related to offices and workflow. We can design the workflow based University ontology to build up a paperless environment for enhanced office content management system [18]. The university ontology repository will be divided into four modules: top-level ontology, domain-level ontology, tasklevel ontology, application ontology. These levels of ontology and relationship between them are depicted in figure 2. Figure 2: Different Levels of Ontology and their Relationship A. Top-level Ontology It is generic ontology, which describe very general concepts independent of domain such that general concepts like Department, School and University etc. This ontology expresses universal concepts and the relationship among concepts. The general concepts of Departments and various Sections can be used by other University and Institute. For example, the school, department and section are the resources of a particular university. B. Domain Ontology Domain Ontology describes the vocabulary related to a generic domain e.g. the vocabulary of generic ontology is courses, faculty and student s profile of department with their courses etc. This ontology provides concepts and relationship among concepts of special domain. C. Task Ontology Task ontology describes the concepts and the relationships among concepts for special task or action (workflow). Task ontologies enable the reuse of services. If we have knowledge about processes and tasks within a specific domain then there is a higher potential for reuse of the knowledge and of the processes. In the task ontology, we can describe the various workflows of aspocms and their relationship among other workflow of files and documents. It provides the services to the users of aspocms with the authorization. D. Application Ontology The application ontology describes the concepts and relationships among concepts, which depends on special domain and task. In this level of ontology, we will describe the relationship between users and their association with various activities of aspocms with authorization. V. DOMAIN ONTOLOGIES DECLARATION The domain ontology is playing the vital important role in the proposed agent-based system, which enable with Semantic Web technologies. The domain ontologies are data schemas, which are providing a controlled vocabulary of concepts, each with an explicitly defined and machine process-able semantics. For the domain ontology declaration, first of all we need to determine domain resources. Domain ontologies comprise usually classes (which classifies objects of a domain) and relationship between them. One possible domain in paperless office content management system can be a domain of users and concepts described in and application domain. Domain ontology of users and their relationships to other components is represented in Figure 3. The class Users is used to annotate a resource. The users will be engaged on some concept roles e.g. some users are sending the electronic documents to other users for particular task as well as getting the electronic documents for further processing. These concept role is played by some special concept (actions of workflow) i.e. payment of guest faculty, new admission of student and payment of emprest bill etc. We use class Concept to annotate concepts.

Figure 3: Ontology of Users and their Relationship Concepts and Users are related through dc:right object property. The users can be ordered by dcterms:requires relationship. Users and concepts have a certain role in their collaboration in certain concepts. We represent these facts by instances of ConceptRole class and its two properties such that isplayedin and isplayedby. Users, concepts and concepts role can form hierarchical. We define subconceptsof and subconceptroleof properties for these properties. Figure 4: Ontology of User Types with their Classes Now, we are describing different types of users in aspocms according to services, which is classified into classes. Figure 4 depicts the ontology with several user types for paperless office content management system domain. The most top user class is Vice Chancellor. Vice Chancellor has two sub classes of users: Registrar and Finance Officer. Registrar class can be further specialized to Store & Maintenance, Estate, Administrative, Examination, Academic and Student Welfare classes. Administrative class can be further specialized to Establishment and Employee. Student Welfare class can be further specialized into Scholarship, Sport and NSS classes. Finance Officer class can be specialized as DR(Finance) sub-class and DR(Finance) can be further specialized as AR(Finance). VI. OBSERVATIONS OF USER S PERFORMANCE AND DEDICATION The users interact with a hypertext structure of aspocms during runtime. The user s interactions can be used to draw conclusions about possible user performance, about user s dedication with their responsibility etc. Ontology of observations should provide a structure of information about possible user observations. A simple ontology for observing the performance of user is depicted in figure 5. The ontology allows us to instantiate facts that a Users of the system has interacted with hasinetraction (Object Property) with a particular Document with isabout (Object Property) via an interaction of a specific InteractionType. The Interaction has taken place in a time interval between begintime and endtime and has a certain level with ObservationLevel. The users can contribute to an interaction with several workflows of files and documents. There are different kinds of InteractionType such as access, bookmark, annotate etc. and there are different OveservationLevels that a user has visited a page, worked on a project and solved some exercise etc.

The main element of the ontology is the Association. The Association is built from two components: Bindings and UserType. These two components are related to association through hasbindings and hasusertype properties. Bindings reference a particular Document as resource, and their Feature. A Feature can be a Direction. The UserType has a name that is a string and the UserType also point to the UserDesignation. In the rest of these, Association can have associated with events through hasevent property, and an annotation through hasannotation property. The hasevent property defines an event, which is provided within the documents. Whenever the event is generated from observation with reasoning rules to which type of event are triggered. Figure 5: Ontology for User s Performance and their Dedication VII. PRESENTATION OF ONTOLOGY In this section we show that how we will describe the ontology structure which is relevant to paperless environment for administration of a universities or institutes. We can categories the resources of aspocms in various classes. These classes may be linked with each other with their own properties. The User and their binding with document, their annotation and event are depicted in figure 6. VIII. CONCLUSION We have demonstrated an approach to develop the various levels of ontologies (e.g. Top-level Ontology, Domain Ontology, Task Ontology and Application Ontology) for aspocms (An Agent-based Semantic Web for Paperless Office Content Management System). These ontologies have been used which correspond to the components of aspocms. The top level ontology describes very general concepts independent of domain such that general concepts like Department, School and University etc. The domain ontology is representing the activities of departments and sections, the relations between them and concepts covered in the domain of the departments and sections of higher educational institutes and universities. Task ontology describes the concepts and the relationships among concepts for special task or actions of various departments and users which enable the reuse of services and the application ontology generates the concepts and relationships among concepts, which depends on special domain and task. The user s performance and their dedication have been measured according to their response time on action of workflows. ACKNOWLEDGMENT Authors are grateful to Prof. B. Hanumaiah, Vice- Chancellor, Babasaheb Bhimrao Ambedkar University (A Central University) Lucknow, India for facilitating the research environment. We are also thankful to University Grant Commission, India for providing the financial support to the research students. REFERENCES Figure 6: A part of Presentation of ontology [1] Tim Berners-Lee, James Hendler and Ora Lassila. The Semantic Web. Scientific American, May 2001. [2] Tim Berners-Lee, Semantic Web-XML2000. http://www.w3.org/2000/talks/1206 -xml2ktbl/slide10-0.html. 2000. [3] Fensel, D., Bussler, C., Ding, Y., Kartseva, A, Klein, V., Korotkiy, M., Omelayenko, M., and Siebes R, Semantic Web Application Areas, In Proceedings of the 7th International Workshop on Applications of Natural Language to Information Systems, Stockholm, Sweden, June 2002, pp27-28.

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