Data Generation Based on Domain Ontology

The growing importance of IT systems implies an increased demand for reliable data. Such data can be used for different purposes, including application testing, AI training, or domain query- ing. Existing tools struggle to generate realistic data consistent with the business rules of the domain under consideration. The paper proposes a data generation method based on ontology, which is treated as a source of domain knowledge description. Wordnet taxonomy supports the generation process by allowing the selection of appropriate external resources to create instance properties. An ontology reasoner is used to enrich generated properties. The proposed method has been implemented as a prototype tool capable of processing ontologies expressed in OWL 2. The tool tests showed that the generated data is complete and corrected within the supported set of constraints. Data realism depends on the domain definition, the provided sources of data, and the instrumentation of the generation process through configuration

Rapid Development of Data Generators Using Meta Generators in PDGF

ABSTRACT Generating data sets for the performance testing of database systems on a particular hardware configuration and application domain is a very time consuming and tedious process. It is time consuming, because of the large amount of data that needs to be generated and tedious, because new data generators might need to be developed or existing once adjusted. The difficulty in generating this data is amplified by constant advances in hardware and software that allow the testing of ever larger and more complicated systems. In this paper, we present an approach for rapidly developing customized data generators. Our approach, which is based on the Parallel Data Generator Framework (PDGF), deploys a new concept of so called meta generators. Meta generators extend the concept of column-based generators in PDGF. Deploying meta generators in PDGF significantly reduces the development effort of customized data generators, it facilitates their debugging and eases their maintenance