# Ontology-Based Methodology for Knowledge Acquisition from Groupware
## 3 Design
### Acquisition Hub  
The Acquisition Hub is the key and the most complex component within the framework as it is where knowledge is harvested. This stage is also referred to as the validation stage. Two fundamental activities take place at this hub:  
1. New knowledge is recognised. 2. New knowledge is inserted/hooked into the existing knowledge base. To recognise a new knowledge is to identify one of the following:  
* an entirely new concept, or
* an existing concept with a new relation, or
* an existing concept with a new attribute. This step may seem quite trivial, especially if done manually, but automating it would require a major formalisation of EQUALITY of two concepts to be able to say that a given concept already exists in the knowledge base. In general, the notion of ontology equality of concepts is still not well-defined and there is no clear consensus on this [42; 43; 44; 45; 46; 47; 48; 49; 50; 51], especially when the new knowledge is from a sentence, which would obviously contain much less content compared to a concept already defined in an existing knowledge base. Therefore, this paper, in its specificity, proposes a technique known as Facts Enrichment Approach (FEA) for the identification and insertion/hooking of a new concept (C) from a sentence into an existing ontology (BO) by considering the notions of equality, similarity, and equivalence of concepts to develop a Target Ontology (TO). TO includes the structural representations in BO, and all its concepts and the newly added C. It is pertinent to note that new knowledge is to be recognised from a sentence and, as such, it is quite rare to be able to recognise new attributes, but perhaps new relations. For the moment, the focus will be mainly on recognising new concepts only. Figure 3: The Harvesting Hub internal structure. To better understand the technicalities underlying our proposition, the general structure of a concept is presented in Figure 5:  
Where: C is the concept in question, S is a super-concept of C, IS_A, RI, and Rm are relations; atrI atrI are attributes with values, vi vk, respectively; and AI Bm are concepts related, respectively, in and out of C.  
Figure 5 says that in general, for a concept in question C, we have:  
Label = C  
Figure 4: The logico-semantic structure that is generated from the Harvesting Hub. Figure 5: Structural view of a concept. If C has a set of attributes and values \(\rm{Catr_{i}}=v_{i}\) for certain indices i, we write:  
\[[\ C\ \ \{\ \rm{Catr_{i}},v_{i}\ \}\ ] \tag{1}\]  
Should C have one or more super-concepts S\({}_{j}\), i.e., there are relations IS_A (C, S) for certain indices j, and with their respective attributes and values S\({}_{j}\)atr\({}_{k}\) = v\({}_{k}\) for certain indices k, we thus have:  
\[[\ S_{j}\ ]\ \{\ \rm{S_{j}}atr_{k},\ v_{k}\}\ ] \tag{2}\]  
As such, given inheritance, the set of attributes for the concept C is actually:  
\[[\ C\ \ \{\ \rm{Catr_{i}},v_{i}\ \}\ \cup_{j}\ \ \{\ \rm{S_{j}}atr_{k},\ v_{k}\ \}\ ] \tag{3}\]  
There may be one or more relations R\({}_{l}\) into C from concepts A\({}_{l}\), for certain indices l, say:  
\[R_{l}\ (A_{l},\ C) \tag{4}\]  
There may be one or more relations R\({}_{m}\) out of C into concepts B\({}_{m}\), for certain indices m, say:  
\[R_{m}\ (C,\ B_{m}) \tag{5}\]  
Our proposed FEA uses relative meanings, a five-dimensional (5D) approach and certain fundamental principles (FP) to determine the newness of a concept, hence this is quite different from the approaches that are in [41, 43, 44, 49], which rely on similarity measures that may vary sometimes. Our approach checks all the labels, attributes and values, relations (in/out), and associated super-concepts and sub-concepts. The FP that guides the identification of a new concept using FEA are:  
* Labels need not be the same at the outset but should be made the same once recognised as equal, similar and/or of equivalence. * The set of attributes and values cannot be expected to be the same, but they must not contradict.