Self-Evolution of Data

In traditional data application scenarios, data is often left idle after a single use, lacking sustained value. However, this pattern of one-time data usage is effectively changed with the application of Schema tools. Schema tools not only prevent the one-time use of data but also introduce a mechanism for continuous data evolution. For example, consider the use of image data; in Schema tools, an image's initial annotation does not signify the end of its value. Over time, the same image may be re-annotated by different annotators according to new needs or perspectives. Such continuous annotation activities allow the originally single image data to accumulate new information, enhancing its content and value with each annotation. This accumulation and optimization of data significantly improve the quality and flexibility of its application, better meeting various complex and personalized application needs. Therefore, Schema tools ensure that data is not only preserved but also evolved and reused, providing broader possibilities for data analysis and application.