Structured Data refers to any form of data that resides in established fields within a record. This is distinguished from unstructured data, which does not have a pre-defined data model. Examples of structured data include spreadsheets, SQL databases, knowledge bases, and knowledge graphs. Examples of unstructured data include many portions of web pages, visual input, paper documents without a filing system, and text of ambiguous purpose.
Diffbot’s web extraction products pull unstructured data from across the public web into billions of structured entities and trillions of structured facts. Utilization of cutting-edge natural language processing, machine vision, and machine learning to optimize knowledge graph ontologies allow Diffbot to truly turn the unstructured web into a structured semantic data source.
See also unstructured data, relation extraction, DIKW Pyramid.