Data Governance and Semantic Recommendation Algorithms for Cloud Platform Selection

Platform as a Service is the major productivity enabler in the cloud computing stack. By providing managed and highly automated application environments, it enhances developer productivity and reduces developer operations and maintenance efforts. The market, however, is fast-changing and offerings are differing conceptually as well as in their supported technological ecosystem. Therefore, provider selection is an important but currently not well supported step for companies trying to benefit from the technology. Influenced by the diversity of service offerings and the absence of applied standards this is a tedious task, especially for ensuring application portability. In this paper, we present a multi-criteria selection approach for cloud platforms based on a field-tested ontology and a comprehensive data set. The methodology is enhanced by semantic algorithms and mappings to reduce hidden query and data biases. This allows not only the exact matching of requirements but also the evaluation of possible alternatives that can be adapted to fit the defined requirements. We validate our approach by contrasting real user queries against the results of our semantically enhanced algorithms