Preliminary Architecture of the OASIS Content Connector Module

Transcription

1 Preliminary Architecture of the OASIS Content Connector Module Dionysios D. Kehagias 1, Dionysia Kontotasiou 1, Dimitrios Tzovaras 1, Evangelos Bekiaris 2 1 Centre for Research and Technology Hellas, Informatics and Telematics Institute, 1st Km Thermi-Panorama Rd., 57001, Thermi, Thessaloniki, Greece 2 Centre for Research and Technology Hellas, Hellenic Institute of Transport, 6th Km Charilaou-Thermi Rd., 57001, Thermi, Thessaloniki, Greece Abstract This paper describes the preliminary abstract architecture of the Content Connector Module (CCM) of the OASIS framework. Content Connector will be constructed, based on the Data Management Module, which was implemented in the ASK-IT project. The purpose of the CCM is to allow service providers to map the functionality of their services to concepts provided by the OASIS ontologies. Services of the same or different application areas, after being mapped to ontological concepts, will be able to be integrated in the main ontological framework, thus being ready to be used seamlessly through the CCM. The tool also enables modifications to the mapped concepts, using easy-to-use drag-and-drop functionality. In addition, CCM will offer ready made taxonomies for elderly people needs, thus making simpler for the developers to embed the extra functionality into their services. This innovative feature, compared to the ASK-IT Data Management Module, will realize the automatic integration of new services in the context of the OASIS ontological framework, by the development of mechanisms that support automatic code generation and on-the-fly reconstruction of the back-end functionality. The purpose of the CCM back-end is to orchestrate connections between the user interface through the ambient intelligence environment and agent technology, as well as the core functionality of the OASIS System. This module coordinates the communication of every OASIS module with the ontological framework and is responsible to redirect user queries through the appropriate path within the supported ontologies. Upon user request, the CCM performs invocation of real Web services, establishing direct content to the service providers hosts and returns the requested content to the appropriate user. Keywords Web services, ontologies, mapping, service alignment. Page 1 of 12

2 1. Introduction The OASIS project aims at developing an Ontology-driven, Open Reference Architecture and System, which will enable and facilitate interoperability, seamless connectivity and sharing of content between different services and ontologies in all application domains relevant to applications for the elderly and beyond. The OASIS System includes a set of novel tools for content/services connection and management, for user interfaces creation and adaptation and for service personalization and integration. One of the supported tools is the Content Connector Module (CCM), whose goal is to facilitate the automatic or semi-automatic connection of existing and emerging ontologies and services to the OASIS Architectural Framework. This paper describes the preliminary abstract architecture of the CCM, whose development will be based on the Data Management Module (DMM). The latter is a similar to the CCM component which was implemented in the ASK-IT project. The purpose of the CCM is to allow service providers to align the functionality of their services, following its conceptual definition, provided by the OASIS ontologies. Every connection made with the tool will be stored, so as to be used by its software core component, in order to respond to the interconnected services in a unified manner. The user interface, as well as the main functionality of the tool will be based on the one of the Service Alignment Tool developed in the ASK-IT project. The Service Alignment Tool has been developed as a sub-component of the DMM. Thus, existing functionality will be exploited and also expanded in the context of OASIS. For instance, existing user friendliness will be preserved, such as drag and drop operations that hide the complexity of the conceptualized connections from the user. The concepts of the same or different application areas, after being mapped to other ontological concepts, will be able to be integrated in the main ontological framework, thus being ready to be used seamlessly through the CCM. Modifications to the aligned concepts will be feasible using easy to use drag and drop functionality. In addition, the tool will offer readymade taxonomies for elderly people needs, thus making simpler for the developers to embed the extra functionality into their services. This feature, which can be seen innovative, compared to the ASK-IT Data Management Module, will realize the automatic integration of new services in the context of the OASIS ontological framework, by the development of mechanisms that support automatic code generation and on-the-fly re-construction of the back end functionality. In addition to the user interfaces, the CCM will provide a backend functionality similar to the one developed in ASK-IT, based on mechanisms implemented on the OSGi platform. Thus, openness to future additions will make sure the easy enrichment of the tool with new functionalities. The purpose of the CCM back-end is to orchestrate connections between the user interface through the ambient intelligence environment and agent technology, as well as the core functionality of the OASIS System. This module coordinates the communication of every OASIS module with the ontological framework and is responsible to redirect user queries through the appropriate path within the supported ontologies. Upon user request, the CCM performs invocation of real Web services, establishing direct content to the service providers hosts and returns the requested content to the appropriate user. This paper is structured as follows. Section 2 reviews the most representative cases of ontology mapping tools. In section 3 we provide an outline of the ASK-IT Data Management module, which is the main source of inspiration for the Content Connector Module. In fact, the CCM advances the capabilities offered by the DMM by adding more automated Page 2 of 12

3 procedures. In Section 4 we outline the major issues involved in the architecture of the Content Connector Module, based on work done in the ASK-IT project. Final section concludes the paper and refers to future work. 2. Ontology Mapping Tools This section presents some representative efforts towards the provision of tools for automatic ontolology mapping. Paolucci et al addressed the problem of creating semantic metadata (in the form of OWL-S) from WSDL [1], [2]. However, because WSDL contains no semantic information, this tool provides just a syntactic transformation. The key challenge is to map the XML data used by traditional Web services to classes in an ontology. Currently, Patil et al [3] taking inspiration from the classic schema matching problem [4], have constructed a framework called METEOR-S for automatically matching WSDL elements to ontology concepts based on their linguistic and structural similarity (Figure 1). They are working on matching XML schemas to ontologies in the Web services domain. They use a combination of lexical and structural similarity measures. They assume that the user s intention is not to annotate similar services with one common ontology, rather they also address the problem of choosing the right domain ontology among a set of ontologies. Figure 1. The Meteor-S user interface Heß et al. have designed a tool called ASSAM [5] (Figure 2), which uses text classification techniques to learn new semantic annotations for individual Web services from existing annotations [6]. The tool extracts a set of candidate concepts, from which the user selects the correct annotation. ASSAM is a tool for semi-automatically annotating Web services. The tool provides the user with assistance and suggestions for matches based on the results of machine learning techniques. ASSAM implements an ensemble learning approach to improve the results [7]. They also researched and tested the approach of using previously annotated WSDL files as training data. Not only did this dramatically improve the results for classification, but it also enabled them to annotate operations, inputs and outputs [7]. Page 3 of 12

4 Sabou [8] addresses the problem of creating suitable domain ontologies in the first place. She uses shallow natural language processing techniques to assist the user in creating an ontology based on natural language documentation of software APIs. She aims to develop (semi-) automatic ontology learning tools in the context of Web services that can support domain experts in the ontology building task. The goal of this first stage was to get a better understanding of the problem at hand and to determine which techniques might be feasible to use. To this end, she developed a framework for (semi-)automatic ontology learning from textual sources attached to Web services. The framework exploits the fact that these sources are expressed in a specific sublanguage, making them amenable to automatic analysis. Figure 2: The ASSAM tool user interface Most recently, Bowers et al. have proposed a technique by which the semantics of the output of a service operation can be computed from information describing the semantics of the operation s inputs and a query expression specifying the transformation it performs [9]. Sudhir Agarwal et al. [10] created the OntoMat-Service tool that assists the user in annotating semantic Web services by using plain text descriptions found on web sites describing the service. This tool provides an interface, OntoMat- Service-Surfer (Figure 3), that supports the intelligence of the user and guides him to add semantic information (mapping to a client ontology) such that only few logically valid paths remain to be chosen by the user. 3. The ASK-IT Data Management Module 3.1 The Core Component DMM is the ASK-IT component on whose functionality the CCM relies. It comprises the main module of the ASK-IT back-end system whose goal is to semantically integrate a set of registered Web services and to provide the means for searching, retrieval and invocation of the appropriate service upon request. Figure 4 depicts the interoperations occurring between the basic modules of the ASK-IT back-end subsystem, as well as any external actors or any other subsystem components. ASK-IT DMM aims at developing an automatic mechanism for aggregating information originated from multiple service content providers, as shown in Figure 4. The end-user requests through a user interface docked on the Client Side subsystem, Page 4 of 12

5 (desktop application, mobile phone or a PDA), a specific service. The user personal agent sends a request-for-service message to the MAS server agents, which is translated to an ontological query. The actual role of the DMM is to: a) listen to the request, b) search for the appropriate services and c) dynamically compose and orchestrate services, d) call the corresponding services and e) return the retrieved content back to the user. The DMM supports the following operations: Figure 3: The Ontomat-service documentation panel 1. Allows new services to be included in the Service Repository, as they are defined through the Service Alignment Tool. It operates as a middleware between the Service Repository on the one hand and the existing Web services on the other. It manages service advertisement to the MAS, as well as storage of new service definitions in the Repository. 2. Receives a user request for a particular type of services. User request is passed indirectly to the DMM through the Multi-Agent System server, which hosts a set of software agents that interoperate between the DMM and the Client Side subsystem. Thus, MAS agents are aware of the user request for content. These agents notify the DMM about the details of the user request received by the client user interface subsystem. 3. Performs a refinement process, according to which it identifies the service provider that best suits the needs of the requesting party. Upon completion of the refinement process, DMM is able to invoke the appropriate service and return the corresponding content received from them. 4. DMM is also responsible for indexing all available (registered) services, and supports categorization of real services according to the conceptual elements defined in the ontology. In this way, mappings between the ontological concepts of services and the service provider-specific attributes are established within the DMM. The DMM is Page 5 of 12

6 equipped with the necessary mechanisms that provide physical access of available services and retrieval of associated content. 5. When requested by the MAS, the DMM performs invocation of real Web services, establishing direct content to the service providers hosts and return the requested content to be delivered to users through the Client Server subsystem. 6HUYLFH3URYLGHUV 3URYLGHU$ 3URYLGHU% 3URYLGHU [ (QWHUV1HZ (QWHUV1HZ 6HUYLFH$OLJQPHQW 7RRO8VHU,QWHUIDFH (QWHUV1HZ 1HZ 'DWD 0DQDJHPHQW 0RGXOH 6HUYLFH $GYHUWLVHPHQW 5HTXHVW IRU 6HUYLFH 0$6 6HUYHU 8VHU5HTXHVWV 3URILOH /RFDWLRQ HWF &OLHQW 8VHU,QWHUIDFH0RGXOHV 6HUYLFH 5HJLVWUDWLRQ 5HWULHYDO RI 6HUYLFH 5HSRVLWRU\ Figure 4. Abstract architecture of the ASK-IT back-end subsystem. 3.2 Service Alignment Tool The Service Alignment Tool is a supporting tool intended to be used by service providers who want to align their services within the ones described in the ontology. This tool enables quick and easy alignment of heterogeneous and distributed services, based on the ontology-specific service definitions. The ASK-IT alignment tool1 operates on top of a Web-based user-friendly interface, through which service providers manage to align their services according to the context of the ontology. Figure 5 illustrates a snapshot of the user interface, where the process of alignment is activated. By performing a drag and drop operation, the service providers semantically characterise the attributes of their own services with respect to the ASK-IT ontology. The main pane of the tool contains a clickable tree, which represents concept categorization of the ontology. The user can browse services defined in the ontology and the supported operations. By clicking on any branch of the ontology tree a user can get: 1 The tool is publicly available at Page 6 of 12

7 The name of the selected service: Usually the real name of the service is different than the one that appears on the tree. A description that contains guidelines about the service usage and scope in textual form. This description is derived from the ontology. The details of the supported operation(s): The user gets information about the technical details of each operation that corresponds to the selected service. Details for each service are divided in input and output section and corresponds to the input and output parameters of each operation. Figure 5. The Service Alignment Tool user interface. By browsing into the ASK-IT ontology, service providers identify services in the ontology that adhere to their existing services, described in WSDL. The service providers align the parameters of their services with respect to the service parameters specified in the ontology. After completion of the alignment process, the particular service is semantically indexed in the Service Repository and it becomes candidate for retrieval and invocation by the DMM. 4. The Content Connector Module Preliminary Architecture The CCM is a module built within a generic, open-ended framework for organising, maintaining and applying heterogenous ontologies. This architecture framework (called COF-Common Ontological Framework or OASIS hyper-ontology ), is used as an open, modular, holistic, easy-to-use and standards-abiding way to achieve: Interoperability between different Web services from the same of different application domains. Sharing of contextual information between different objects and services. Seamless connectivity between hardware, from hardware to service and from service to service. Page 7 of 12

8 Thus, this hyper-ontological framework will be able to automatically, where possible, and semi-automatically where not: Connect single services to ontologies in their area, via aligning them to a higher level model. Interconnect heterogeneous ontologies that abide to the hyperontological framework, in a common domain. Interconnect ontologies of different domains that abide to the hyper-ontological framework. Develop ontological frameworks, that are compatible to this hyper-ontological framework, in areas where these do not exist. In the context of the above architecture, the role of CCM will be to enable mappings between existing Web services and a higher level knowledge representation entity. This will be structured in the form of ontologies in various application domains, all relevant to the specific information needs of the elderly and disabled users. The CCM will serve an ambient intelligence (AMI) framework to be developed in OASIS, as key enabler of the project development platform, based upon a family of intelligent agents, to orchestrate, monitor, personalise and deliver the integrated services. Its architecture is shown in Figure 6. The used agents are: User Agents. These agents belong to the user personal AMI space. This means that their execution environment is the one which is in direct interaction with the user, including the local environment that surrounds the user. User Agents are responsible to carry and handle detailed information related to the user profile and preferences. This information may include, apart from user-specific attributes, their needs and wants, the type of the end-user device, as well as the attributes of user s physical environment which they conceive through a suitable sensoring mechanism. By collecting all user-related info, these agents become capable of synthesising suitable user-profile data, which they store in a local repository. In addition, these agents are responsible to act on the user personal AMI space by announcing specific notifications according to the type of information received by other agents, in correspondence to a specific request for service or content previously posted by the user. Page 8 of 12

9 Figure 6: OASIS AMI Framework Service Prioritisation Agents. The CCM performs semantic search among suitable available Web services, in order to satisfy the user request. The results produced as outcome of the search mechanism are then fed to the Service Prioritisation Agents, whose role is to provide a ranking of the returned services according to the specific needs, preferences and habits of the user. They actually implement a low-level information filtering process, thus providing the most valuable services to the end user. Service Provider Agents. The real invocation of a requested service is performed by the service provider agents that also take into account user profile-specific information in order to guarantee that the user receives the appropriate content to be rendered on the appropriate device. Content Connector Agents. These agents are responsible to interact with the CCM and initiate the semantic search procedure based on the Hyper-ontology. They exploit user-related information and execute rational logic in order to discover the services that best match the user needs. They do this by receiving combined information from User agents and Service prioritisation agents. Finally, they perform all required actions in order to forward the user request to the CCM and the Hyper-Ontology and receive the appropriate results in an agent understandable format. The Content Connector Agents provide the link between the Hyper-ontology and the AMI. The overall layout of the OASIS System is shown in Figure 7. Page 9 of 12

10 OASIS AmI Framework Service Provider Service Provider Service Provider Service Provider Service Provider WEB Web Services HYPERONTOLOGY Semantic Discovery of Web Services CONTENT CONNECTOR MODULE Personal User Preferences/ Discovered Content and Services AGENT COMMUNITY User Requests/Filtered and Prioritised Content and Services PERSONAL USER SPACE Figure 7: OASIS System and its components In the context of the OASIS project, the CCM will be constructed upon the functional architecture of the ASK-IT DMM but it will go one step further. Altough CMM and DMM will share similar functionality, the former will enable a more automated process of service alignment and integration. The new element in CCM is that it will generate automatically the required source code for the integration of services into a common infrastructure. In this way, service registration process on behalf of service providers will be dramatically decreased in terms of times and development efforts. Figure 8 depicts this idea. Service providers will exploit the user interface of the CCM in order to register their services in the context of semantically described services by the Hyper-ontology. This process will be more automated compared to the ASK-IT DMM. As the service providers enter their descriptions in WSDL, the CCM will parse these descriptions and will automatically decide where to classify them, according to the main service description ontology. This process can be also supervised by the users who will be the last to confirm the correctness of the recommended mappings. In this way, we automate the process of concept anchoring and alignment that allows connection between ontological concepts. The purpose of this process is to allow service providers to align the functionality of their services, following its conceptual definition, with the aid of ontologies. Every connection made with the tool will be stored, so as to be used by the CCM, in order to respond to the interconnected services in a unified manner. The functionality of the CCM user interface is based strictly on drag and drop actions that hide the Page 10 of 12

11 complexity of the conceptualized connections from the user. The concepts of the same or different application areas, after being aligned with other ontological concepts, will be able to anchor in the hyper ontology framework, thus being ready to be used seamlessly through the CCM. Modifications to the aligned concepts will be feasible using easy to use drag and drop functionality. In addition, the tool will offer ready made taxonomies for elderly people needs, thus making simpler for the developers to embed the extra functionality into their services. In the ASK-IT DMM, the process of service mapping against the overall ontology was mainly performed in a manual manner. Moreover, as soon as a new service was being mapped, the integration of the real services became feasible only as soon as the development team performed the appropriate modifications in the DMM source code in order to create the necessary wrappers of the new integrated services. The purpose of these wrappers was to seamlessly invoke the new entered services. This is, of course, a manual process, which will be also fully automated in the OASIS project. Thus, the CCM will actually perform the process of creating the appropriate wrappers and compiling them at real time in an automatic fashion, as soon as a new service will be mapped in the ontology. This feature will enable the seamless invocation of Web services upon user request and during the operation of the AMI framework. Figure 8: The OASIS abstract design philosophy Page 11 of 12

12 6. Summary and Conclusions This paper presented the abstract architecture of the Content Connector Module of the OASIS project. This module has the purpose of enabling automatic mappings between existing Web services and the OASIS hyper-ontology. In this way, seamless service invocation upon user request is implemented in the context of the OASIS AMI framework. The CCM is based on the functionality of the ASK-IT Data Management Module. However, CCM goes one step further by adding more automated processes about service mappings and creation of wrappers, appropriate for invocation of real Web services. By providing automated solutions for the aforementioned processes, we expect the CCM tool effectively decrease the times of ontology mappings, as well as the development efforts required for the construction and re-compiling of a new wrapper. Based on empirical evidence, it is estimated that the average time that a developer needs to create and compile a wrapper is about 4 hours. Through the CCM tool the same process is estimated to be completed in less than a minute, at most. Thus, the automation of this process will significantly reduce the required times for service integration. References [1] Paolucci, M., Srinivasan, N., Sycara, K., Nishimura, T., Towards a semantic choreography of Web services. From WSDL to DAML-S. In: Int. Conf. for Web services, [2] Martin D., Paolucci M., McIlraith S., Burstein M., McDermott D., McGuinness D., Parsia B., Payne T.R., Sabou M., Solanki M., Srinivasan N., Sycara K. (SRI, CMU, Univ. Toronto), Bringing Semantics to Web services: The OWL-S Approach. First International Workshop on Semantic Web services and Web Process Composition (SWSWPC 2004) 6-9, San Diego, California, USA, [3] Patil, A., Oundhakar, S., Sheth, A., Verma, K.: Meteor-s web service annotation framework. In: 13th Int. WWW Conf., New York, USA, [4] Mitra P., Wiederhold G., and Kersten M. L., A graph-oriented model for articulation of ontology interdependencies, In EDBT, [5] Heß A., Johnston E., and Kushmerick N., Assam: A tool for semi-automatically annotating semantic Web services. In ISWC, [6] Heß A. and Kushmerick N., Learning to attach semantic metadata to Web services. In ISWC, pages , [7] Heß A., Kushmerick N., Machine Learning for Annotating Semantic Web services. In: AAAI Spring Symposium on Semantic Web Services, [8] Sabou, M.: From software APIs to web service ontologies: a semi-automatic extraction method. In: 3rd International Semantic Web Conference, Hiroshima, Japan, [9] Bowers S. and Ludascher B., Towards automatic generation of semantic types in scientific workflows. In: WISE Workshops, [10] Agarwal, S., Handschuh, S., Staab, S., Surfing the service web. In: 2nd International Semantic Web Conference, Sanibel Island, FL, USA, Page 12 of 12