Structures

Semantic Tags

Every piece of information in ASIP is stored with metadata. Semantic Tags are like words, which are used for describing metadata. There are 4 different types of Semantic Tags in the implementation:

• Normal Semantic Tags are used for describing the Topic and the Type of information
• Peer Semantic Tags are used for describing the Peer dimension of information. They can represent either real persons, devices or machines.
• Time Semantic Tags are used for describing the period of time in which a piece of information is relevant.
• Spatial Semantic Tags are used for describing the location in which a piece of information is relevant.
• Predicate Semantic Tags are used for describing the relation between two Semantic Tags wihtin a Semantic Net. This relation is directive from a source Semantic Tag to a target Semantic Tag and has also a name.

Each Semantic Tag has one or multiple Subject Identifiers, a name and a unique ID. Sepcial Semantic Tags like the Peer Semantic Tag possess additional attributes like an address.

All known Semantic Tags of a peer are forming the Vocabulary of the Peer.

Semantic Nets

Semantic Tags are nearly always stored wihtin a SemanticNet. A Semantic Net is a container for Semantic Tags. This container can additionally include multiple Predicate Semantic Tags for describing the relation between the Semantic Tags. Each type of Semantic Tag has its own special type of Semantic Net. For example in a Peer Semantic Net, only Peer Semantic Tags can be stored in it.

Knowledge and Knowledge Base

The Knowledge Base is the most important class of SharkPython. It contains all known Tags, Semantic Nets and Predicates of the Peer and offers methods for inserting new Knowledge into the Knowledge Base and exposing an interest. The Knowledge Base has only one attribute, the Knowledge.

Knowledge contains Vocabulary, InfoData and InfoContent. Currently Info Data and Info Content are simple data holders.