L scorpioides Erben in Mitt Bot Staatssamml [scorpioídes] München 28: 387 (1989)

Ontology mapping is the process, which needs to be done after successfully constructing new Ontology (semi-)automatically from the uploaded LO. The aim of this Ontology mapping is to conform, establish correspondences and determines the set of overlapping concepts, concepts that are similar in meaning but have different names or structure, and concepts that are unique to each source, between the new Ontology with the existing Ontology in knowledge base. This work is either done to create a single coherent Ontology that includes the information from all the sources (merging) or if the sources must be made consistent and coherent with one another but kept separately (alignment). Figure 4-6 illustrates the difference between Ontology Mapping, Ontology Merging and Ontology Alignment; the yellow and purple box represents two different Ontologies.

Ontology Mapping Ontology Merging Ontology Alignment

Figure 4- 6Ontology Mapping, Merging, and Alignment

Because there are two kinds of Ontology in this SAOKBCS, the Ontology Mapping in our process consists of two folds. The first fold is Context Ontology Mapping and the second fold is content Ontology Mapping. The context Ontology refers to Ontology that model anything describing the LO in e-Learning environment. The content Ontology

SP ppt Learning

Object Learning Object SP ppt

Learning Object

refers to Ontology that model anything describing what is the content of the LO tell us about. The case scenario of context Ontology mapping is illustrated by Figure 4-7 which is done automatically in our framework. For Content Ontology Mapping PROMPT (Natalya et al. 2000) algorithm is adopted. PROMPT algorithm is illustrated in Figure 4- 8.

A: New Ontology

C:Merged Ontology

Figure 4- 7 Context Ontology Merging Case Scenario

The part A of Figure 4-7 is a new Ontology which is constructed automatically from the uploaded LO i.e. text Learning Materials, part B is the existing Ontology in knowledge base before a new Ontology (part A) is added, and part C is the Ontology in knowledge base after a new Ontology (part B) is added. Part C is showing how the new Ontology (part A) is to be mapped to the existing Ontology. As depicted in Figure 4-7 Part C, it is found that Semantic Web is mapped as subclass of Learning Object, NIA is mapped as instance of Contributor, and KMD is mapped as instance of Subject.

The second part of Ontology mapping, merging, and alignment is under taken for content Ontology. To doing so, PROMPT framework is adopted to our SAOKBCS. The PROMPT algorithm is depicted by Figure 4-8.

Figure 4- 8 PROMPT Algorithm (Natalya et al. 2000)

Figure 4-8 illustrates the PROMPT Ontology-merging and Ontology-alignment algorithm. PROMPT takes two Ontologies (the new Ontology and the existing Ontology in knowledge base) as input and guides the user in the creation of one merged Ontology as output. First PROMPT creates an initial list of matches based on class names. Then the following cycle happens:

(1) The user triggers an operation by either selecting one of PROMPT’s suggestions from the list or by using an Ontology-editing environment to specify the desired operation directly; and

(2) PROMPT performs the operation, automatically executes additional changes based on the type of the operation, generates a list of suggestions for the user based on the structure of the Ontology around the arguments to the last operation, and determines conflicts that the last operation introduced in the Ontology and finds possible solutions for those conflicts.

The set of Ontology-merging operations that Ontology mapping module done consists operations such as: merge classes, merge slots, merge bindings between a slot and a class; perform a deep copy of a class from one Ontology to another (includes copying all the parents of a class up to the root of the hierarchy and all the classes and slots it refers to);

Make Initial Suggestion Select Next Selection

Perform Automatic Update Find Conflicts Make Suggestion

perform a shallow copy of a class (just the class itself, and not its parents or the classes and slots it refers to).

For example, suppose in the case of merging two Ontologies and it performs a merge- classes operation for two classes A and B to create a new class M. PROMPT then performs the following actions:

(i) For each slot S that was attached to A and B in the original Ontologies, attach the slot to M with the same value type and other facets. If S did not exist in the merged Ontology, create S.

(ii) For each superclass of A and B that has been previously copied into the merged Ontology, make that copy a superclass of M (thus restoring the original relation). Do the same for subclasses.

(iii) For each class C in the original Ontologies to which A and B referred (that is, for each superclass, subclass, slot value, and class restricting a slot value of A and B), if C has not been copied to the merged Ontology, suggest that it is copied to the merged Ontology.

(iv) For each class C that was a facet value for A or B and that has not been copied to the merged Ontology, declare a dangling-reference conflict.

(v) For each pair of slots for M that have linguistically similar names, suggest that the slots are merged. Later, if the user chooses to merge the slots, suggest that the classes restricting the values of these slots are merged as well.

(vi) For each pair of superclasses and subclasses of M that have linguistically similar names, suggest that they are merged: these classes have similar names and, in addition, they were both superclasses (or subclasses) for A and B, which the user declared to be similar.

(vii) Check for redundancy in the parent hierarchy for M: If there is more than one path to any parent of M (other than the root of the hierarchy), suggest that one of M‘s parents is removed.