| Term | Meaning |
|---|
| Class | |
| Constraint | |
| Dataset | |
| Domain Expert | A Domain Expert is an End User. In addition, he/she can generate new models based on existing knowledge bases. A Domain Expert cannot modify the knowledge in a knowledge base. |
| End User | An End User is a user that uses existing solutions with new data. An End User cannot generate new models based on an existing knowledge base. Also, this user cannot modify the knowledge base. This type of user is comparable to someone that uses an existing spreadsheet for computations with new data. |
| Entity | An Entity is a generic description of an Object (e.g. a ship structure) or a Process (e.g. the design of a propeller or a seakeeping analysis). |
| Frame | |
| KCMA | Knowledge-based Computational Model Assembling: the creation of a model based on a network of knowledge components. From relations, applications, data etc. a model is created in collaboration by system and user, to compute the requested Top Goal. |
| Knowledge | Technical knowledge is all information that can be captured in data, parameters and relations (formulas, equations, procedures, applications), their properties and networks built from these concepts. |
| Anchor |
|---|
| KnowledgeBase |
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| KnowledgeBase |
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|
Knowledge Base | |
| Anchor |
|---|
| KnowledgeEngineer |
|---|
| KnowledgeEngineer |
|---|
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Knowledge Engineer | A Knowledge Engineer is a Domain Expert. In addition, he/she can create, expand and modify knowledge bases. |
| Object | An object in Quaestor consists of a collection of parameters Parameters or 'value containers'. |
| Parameter | Value container. Knowledge is created by creating relations between parameters. |
| Process | |
| Project | |
| Quaestor | [Q]uaestor is a computer program that allows a user in a simple way, to enter relations and to couple existing data, applications and databases. The inference engine then combines, in an intelligent way, the collections of relations, applications, data and databases to solutions for a given problem.This is an interactive process, where Quaestor searches suitable alternatives and proposes these to the user. Depending on the choices a user makes, the result is a model to solve the problem at hand. The finally generated model can be used over and over again with new data, but fixed knowledge. |
| Relation | parameter = function(par1, par2, ..., parn) |
| Solution | A solution is the model that is generated as a result of the dialog between system and user. In the Knwledge Knowledge Base, one or more Top Goals Goals can be selected. After that, the user starts the computation. By entering values on Quaestor's request and by accpeting accepting or rejecting relations, a model is generated that can compute the Top Goal(s).This model can then be used over and over again with new input data. A solution can be regarded as programmed knowledge. |
| Taxonomy | A Taxonomy consists of a hierarchy of Entities, each representing an object Object that contains its private data, goals and model fragments and its sequence represents a work flow. |
| Telitab | Text-List-Table. A data structure type used inside Quaestor. |
| Top Goal | A Top Goal is a parameter for which a (range of) value(s) must be computed. |
| Value | A value can be (a vector of) numerical, nominal (string/document), binary or object Object. |
