
## 1 Previous Works

In [All03] was done an analysis of the visualization tools for knowledge engineering, from that the lack of an established theory about user tasks and the cognitive support they require was revealed. Also were identified many difficulties encountered when performing user testing in the knowledge engineering domain, including gaining access to expert users, generalizing results over different domains and quantifying the knowledge acquired and used by such tools. 

These issues recommend focusing on more qualitative approaches which included a user survey, two contextual inquiries, and investigation of related work; using these different techniques provided a series of useful perspectives on the problem. There exists a wide variety of users and domains to which ontology engineering is being applied, and further, that visualization is a desired feature. 

Based on an analysis of the Knowledge Acquisition system [TKG01]
the experimenters observed users performing the following high-level tasks:
- **understanding the given knowledge acquisition task;** 
- **deciding how to proceed with the knowledge acquisition task;** 
- **browsing the knowledge base to understand it;** 
- **browsing the knowledge base to find something;** - **editing (create or modify) a knowledge base element;** 
- **checking that a modification had the expected effects on the** 
knowledge base; 
- **looking around for possible errors;** 
- **understanding and deciding how to fix an error;** 
- **recovering from an error by undoing previous steps (to delete or** 
restore a knowledge base element); 
- **reasoning about the system.** 
In [BKR01] were identified some typical concerns that users may have when adding new knowledge to an intelligent system. Some of these concerns were that the users do not know where to start and where to go next, the users do not know if they are adding the right things and the users often get lost as it takes several steps to add new knowledge. Here is clearly shoed that the standard knowledge engineering methodology, consisting of the steps of modelling, acquiring and verifying knowledge, fails to accommodate the specific needs of users, even modellers in the domain. It is no use to have a crisp and detailed methodology if users cannot easily make use of it in any one of its stages. 