Sharing summarised semantic data rather than just data

Summary form only given. To enable a group of multiple disciplinary computer software systems to effectively and efficiently collaborate is an important task for applications such as cooperative designs, energy efficiency monitoring system, real-time collaborative mechatronic control systems, e-learning, and enterprise computing etc. With the cost reduction of the hardware for storing data and the need of maintaining the vast amount of data generated from simulation tools, social media and sensors for decision making, to retrieve the right information and to share appropriate knowledge at right time among the participants is a challenging task. On-line Analytical Processing, OLAP, is an effective tool to summarize vast structured data into concise data cubes with multiple dimensions for business intelligence and decision making. Semantic OLAP was developed in the research communities is to process the linked data which is a form of web data representation with semantics increasingly gaining its popularity over the Internet. The introduction of OLAP has increased the efficiency of data retrieval and data management, but it does not address the issues of information and knowledge sharing. In this talk, these issues will be reviewed with examples and a new OLAP framework which could bridge the gaps and increase the sharing among different OLAPs will be presented with a case study. This talk will also share delegates with recent research findings from some ongoing EU-funded projects.