Supporting Ontology-Based Dynamic Property and Classification in WebSphere Metadata Server [chapter]

Shengping Liu, Yang Yang, Guotong Xie, Chen Wang, Feng Cao, Cassio Dos Santos, Bob Schloss, Yue Pan, Kevin Shank, John Colgrave
2008 Lecture Notes in Computer Science  
Metadata management is an important aspect of today's enterprise information systems. Metadata management systems are growing from toolspecific repositories to enterprise-wide metadata repositories. In this context, one challenge is the management of the evolving metadata whose schema or meta-model itself may evolve, e.g., dynamically-added properties, which are often hard to predict upfront at the initial meta-model design time; another challenge is to organize the metadata by
more » ... classification schemes. In this paper, we present a practical system which provides support for users to dynamically manage semantically-rich properties and classifications in the IBM WebSphere Metadata Server (MDS) by integrating an OWL ontology repository. To enable the smooth acceptance of Semantic Web technologies for developers of commercial software which must run 24 hours/day, 7 days/week, the system is designed to consist of integrated modeling paradigms, with an integrated query language and runtime repository. Specifically, we propose the modeling of dynamic properties on structured metadata as OWL properties and the modeling of classification schemes as OWL ontologies for metadata classification. We present a natural extension to OQL (Object Query Language)-like query language to embrace dynamic properties and metadata classification. We also observe that hybrid storage, i.e., horizontal tables for structured metadata and vertical triple tables for dynamic properties and classification, is suitable for the storage and query processing of co-existing structured metadata and semantic metadata. We believe that our study and experience are not specific to MDS, but are valuable for the community trying to apply Semantic Web technologies to the structured data management area. S. Liu et al. data, but prescriptive information that constrains the structure and content of data. The metadata can be technical metadata, such as relational schemas, XML schemas, schema mappings, UML models and application interface specifications, and can be business metadata, such as business concepts, business rules and business process definitions in an enterprise. The metadata management tool (also known as repository) [15] is crucial for enterprise information management and has become the foundation of Data Warehousing [9], Enterprise Information Integration [8] and Service-Oriented Architecture (SOA). Recent standards work on MOF/XMI [11] within OMG for metadata representation and interchange has been followed by many vendors, then MOF-based metadata repositories have become the mainstream in industry offerings 5]. Amongst these MOF-based metadata repositories, a common feature is the object-oriented storage strategy where Object-Relational Mapping functionality is used to generate physical schemas for the corresponding MOF meta-models and provide an object-oriented programming interface to the underlying database. One typical example is the IBM WebSphere MetaData Server (MDS), which is a unified metadata services infrastructure within a service-oriented architecture. Within the enterprise-wide IT environment, metadata management has become more and more challenging because of rapidly-changing business requirements. Metadata repositories are growing from tool-specific, application-specific systems to enterprise-wide, asset-management and architecture decision support systems, in which metadata are shared and integrated across multiple applications or even third party tools [6] . While the metadata and their relationships dramatically grow, it is impossible to design a unified meta-model for all kinds of metadata with all possible attributes and relationships at design stage as the business requirements evolve. Therefore there is a requirement to dynamically add properties for classes in the registered metamodel. For example, after a WSDL meta-model which describes WSDL documents has been registered, a service administrator might add QoS (Quality of Service) metadata to the "WSDLService", such as the "responseTime". Another example is to dynamically build particular relationships across registered meta-models. After the metadata repository has run and collected entries for a period of time, a user needs to create a dynamic relationship "dependsOn" from the class "Activity" in the business process meta-model to the class "WSDLService" in the WSDL meta-model, which later can be used to enable traceability and impact analysis across those models. Moreover, semantic annotations are required to enrich the semantics of dynamic relationships, e.g. annotating "dependsOn" as "transitive". Based on these semantic annotations, ontology reasoning will be made to infer additional information which is not explicitly defined. In metadata management, a classification scheme is used to classify the metadata objects, such as relational schemas and WSDL definitions in a metadata repository. Examples of classification schemes range from simple tags (keywords), thesauri, taxonomies to formal ontologies. With the growing volumes of metadata in different applications and users of metadata from various business units of enterprises, a flexible and semantic-rich classification scheme is needed to help different users to organize metadata from different viewpoints. This is because: (1)the classification scheme itself
doi:10.1007/978-3-540-88564-1_56 fatcat:v4nsvi7pqfeyref24tk7wckaha