Information extraction is the process of extracting specific information from textual sources. It enables the automation of tasks such as smart content classification, integrated search, management and delivery. It also facilitates data-driven activities such as mining for patterns and trends, uncovering hidden relationships, etc.
Semantic repository, in general, is a database management system. It allows storing, querying, and managing structured data. Its major benefit is the use of semantic data schema paradigm, called ontology, which is stored and managed independently from the data.
An ontology is a formal description of knowledge as a set of concepts within a domain and the relationships that hold between them. Read about how ontologies not only introduce a sharable and reusable knowledge representation, but can also add new knowledge about the domain.
DIKW Pyramid represents the relationships between data, information, knowledge and wisdom. Each step up the pyramid answers questions about and adds value to the initial data. The more questions we answer, the higher we move up the pyramid.
Linked Data is one of the core pillars of the Semantic Web, also known as the Web of Data. The Semantic Web is all about making links between datasets understandable not only to humans, but also to machines, and Linked Data provides the best practices for making these links possible.
Semantic Technology uses formal semantics to give meaning to the disparate and raw data that surrounds us. In other words, the core difference between Semantic Technology and other data technologies, the relational database for instance, is that it deals with the meaning rather than the structure of the data.
The Semantic Web is a layer of the existing Web that is meant to provide software agents with machine-readable definitions of all kind of things and the relationships between them. Its ultimate goal is to enable machines to better manipulate information on our behalf.