Data Evolution and Its Modeling

Incomplete information about how data has evolved over time has caused many puzzles in applications such as audit trail, data quality. Such challenges mandate the need for rich and descriptive derivation information about data to accompany the data in order to understand and reuse it. This paper puts forward the concept of data evolution to describe the process of semantics change for data product in its lifecycle, in which data product is an entity with interactive computation capability. In practice, data has intrinsic semantics as well as extension semantics, but current data models only describe the intrinsic semantics for data. Therefore, this paper presents a new explanation of dasiadatapsila, i.e. dasiadatapsila is a combination of data object, genetic information and computing component. Data object expresses the intrinsic semantics for dasiadatapsila. The genetic information represents the extension semantics for dasiadatapsila. The computing component interacts with user behaviors, evolves data object and genetic information and memorizes the process of semantics change. We present the framework of data evolution, analyze its characteristics and present its research challenges.