Complexity Dimension

The kernel is designed to provide support to persistently store very simple atoms of knowledge representation like terms, predicates and very complex propositional systems like arguments, rules, axiomatic systems, loosely held paragraphs, and more complex structured and consistent compositions. All the component classes in GNOWSYS are classified according to complexity into three groups, where the first two groups are used to express all possible well formed formulae permissible in a first order logic.

Figure 1: A diagram representing the architecture of GNOWSYS kernel showing the component classes, and complexity, and generality dimensions.

Terms:

`Object', `Object Type' for declarative knowledge, `Event', `Event Type', for temporal objects, and `Meta Types' for expressing upper ontology. The objects in this group are essentially any thing about which the knowledge engineer intends to express and store in the knowledge base, i.e., they are the objects of discourse. The instances of these component classes can be stored with or without expressing `instance of' or `sub-class of' relations among them. They are also designed to borrow monadic relations (attributes) from the predicate group to characterize them.

Predicates:

This group consists of `Relation', and `Relation Type' for expressing declarative knowledge, and `Function' and `Function Type' for expressing procedural (behavioral) knowledge. This group is to express qualitative and quantitative relations among the various instances stored in the knowledge base. While instantiating the predicates can be characterized by their logical properties of relations, quantifiers and cardinality as monadic predicates of these predicate objects. An additional comment of how functions can be represented in GNOWSYS is warranted. Though it is possible to explicitly define functions from very primitive `atoms' (as done in ACT-R) GNOWSYS provides an implicit way of instantiating surrogates of functions available in the operating system or from the grid of GNOWSYS servers any where on the Internet. More on this unique feature later. Another notable point regarding predicates is that the relations are not only expressed by specifying foreign keys on the argument objects, but also as independently reified objects.

The object and predicate group together provide the basic vocabulary and ground assertions. They constitute the set of well formed formulae in the knowledge base, with quantifiers, and other possible kinds of formal annotations.

Structures:

`System', `Encapsulated Class', `Program', and `Process', are base classes for complex structures, which can be combined iteratively to produce more complex systems. The component class `System' is to store in the knowledge base a set of propositions composed into ontologies, axiomatic systems, complex systems like say a human body, an artifact like a vehicle etc., with or without consistency check. An `Encapsulated Class' is to compose declarative and behavioral objects in a flexible way to build classes. A `Program' is not only to store the logic of any complete program or a component class, composed from the already available behavioral instances in the knowledge base with built-in connectives (conditions, and loops), but also execute them as web services. A `Process' is to structure temporal objects with sequence, concurrency, synchronous or asynchronous specifications. Using these classes a wide variety of domain specific systems are specifiable either formally or informally. These classes can be used to flexibly design in more than one design architecture, like functional, structural, object or agent oriented ways. As mentioned earlier these structures are part of the higher layers, which can reuse the ground assertions as well as other simpler structures instantiated earlier, but they do not interact with each other unless explicitly specified. This is to ensure that inconsistencies in one structure do not propagate to other structures stored in the knowledge base. This is how GNOWSYS is intended to store multiple ontologies, epistemologies and logics.

Every object in the database keeps the neighborhood information, such as its super-class, sub-class, instance-of, and other relations, in which the object has a role, in the form of predicates. This feature makes computation of drawing graphs and inferences, on the one hand, and dependency and navigation paths on the other hand very easy. Since references about an object are present on other objects in the network, an accidentally lost object could be reconstructed. These points justify an element of redundancy in the database. All the data and metadata is indexed in a central catalogue making query and locating resources efficient.