Knowledge Management and Representation

The company started its research on knowledge management and semantic network standards during lab phase three. The two drivers in this effort were representing the lab’s extensive technology knowledgebase and modeling service-oriented solutions to reduce the complexity of integrating enterprise heterogeneous sources of information. The use of semantic technologies increased significantly throughout lab phase four, as part of the company’s interest to create a semantic development paradigm, applying these technologies to the representation of its SOA reference framework, enabling components and SaaS applications. QoS Labs defined key functionalities of its SaaS platform by studying emerging Semantic Web standards, listening to its allies and customers, and testing a first semantic engine implementation through lab use cases in Florida, Brazil and Mexico (e.g., e-Government, banking, education, service providers). Special efforts were devoted to understanding and testing various knowledge representation standards and technologies and learning about metadata standards.

The service-oriented vision that always guided the company’s research in the past expanded in lab phase five under a wider scope, working on enterprise ontology. QoS Labs decided to replace the first semantic engine developed jointly with R&D allies and create its own technology.

Parallel lab projects throughout this phase focused on application modeling and how to apply it to enabling components such as Web Services engine, Enterprise Service Bus (ESB), Business Process Management (BPM) and IT management tools. Many limitations were found in the enabling components available at the time when applied to real customer problems. Using its proprietary semantic engine and SaaS reference framework, QoS Labs developed Corporate Governance modeling and best practices, utilizing 28 third-party enabling components that were applied to Employee Life Cycle Management and Sarbanes Oxley regulatory compliance – two critical enterprise problems. These solutions required domain ontology work under the company’s semantic development paradigm. IT Life Cycle Management work was performed at an experimental level based on emerging standards and international best practices to extend the Corporate Governance framework to IT Governance.