Semi-structured data

Semi-structured data is a form of structured data that is not rigidly structured. The data model associated with semi-structured data is interpreted when the data is read from a data storage medium or accessed in memory. The data model need not conform to a predefined database schema and is not optimized for succinct, low-overhead streaming or persistent storage as is normal with a relational database, graph database, data table, or graph. Instead, semi-structured data includes delimiter characters or tags to separate semantic elements or to describe relationships among records and fields within the data. The data is said to have a self-describing structure. Semi-structured data may be human-generated or machine-generated. It may be part of an unstructured document such as narrative text or may encompass unstructured data such as free-form comments. It may be intended to be read by humans, to be shared between software services or applications whose data models are not fully consistent, or to be transmitted from sensors or other devices to computers. Optical character recognition in combination with intelligent document processing can convert semi-structured data appearing on printed pages into machine-ready formats such as JSON. Electronic data interchange uses standard segments, elements, and delimiters to transfer business transaction data between computers owned by different organizations. Metrics from an array of various sensors can be combined, as heterogeneous data without predefined schemas, in JSON format.