Incompleteness Errors in Ontology 1 Muhammad Abdul Qadir, 2 Muhammad Fahad, 3 Syed Adnan Hussain Mohammad Ali Jinnah University, Islamabad, Pakistan 1 aqadir@jinnah.edu.pk, 2 mhd.fahad@gmail.com, 3 syedadnan@gmail.com Abstract Ontology evaluation is one of the most important phases of Ontology Engineering. Researchers have identified different types of errors that should be catered in ontology evaluation process and classified them in error’s taxonomy. We have found that some important errors are missing in the error’s taxonomy. We have identified and defined two new incompleteness errors i.e. Functional Property Omission (FPO) for single valued property and Inverse-Functional Property Omission (IFPO) for a unique valued property. We have demonstrated the importance of such errors by giving different scenarios where appropriate. We have evaluated different ontologies and presented empirical results.. 1. Introduction Ontology is regarded as the formal specification of the knowledge of concepts and the relationships among them [3]. They require formal syntax and semantics to represent domain concepts. They have not only played a key role for describing semantics of data in semantic web application but revolutionized the traditional knowledge engineering and explored the ontology driven architecture based systems. Ontology has to go through a repetitive process of refinement during its development lifecycle. Ontology engineers have to pay much attention to produce high quality bug free ontology. But there is a possibility that the ontologists unintentionally make some errors in ontology [5]. Ontology evaluation is one of the most important phases of Ontology Engineering because if ontology itself is error prone then the applications dependent on the ontology have to face some critical and catastrophic problems [6]. Domain researchers have identified some errors and defined them in error’s taxonomy for assistance in the ontology evaluation [1,15]. This error’s taxonomy becomes a guideline for ontology engineer to evaluate the ontology in perspective of such errors. If some errors are not defined in error’s taxonomy then we can say that the ontology engineer based on the error’s taxonomy will not detect such errors. Gomez et al. identified and categorized three types of errors that are usually encountered by ontologist i.e. inconsistency, incompleteness and redundancy of information [1]. Inconsistency originates when there exists some contradictory information about concepts. Redundancy means that same information is inferred from ontology more than once. Incompleteness means the concepts are not completely defined and some important information is overlooked. Qadir et al [4] identified the scenarios where disjoint knowledge omission leads toward catastrophic situations and proposed a system that detects disjoint knowledge omission and generates warnings for ontologists. Besides ontological errors, Baumeister and Seipel [9] identified some design anomalies in ontologies that create maintainability issues and represent badly designed areas within the ontology. They defined the detection method by using prolog and FN-query language. These anomalies help the ontologist to develop consistent ontology that can be better maintained and easily extensible. Brank et. al. [14] discussed the overall approaches for ontology evaluation and concluded that different approaches are useful in different application. The selection of evaluation approach depends on the application. This survey helps the ontologist to select appropriate evaluation method for its domain. Previously we have extended Gomez’s error taxonomy by identifying two new errors [15]. One is Sufficient Knowledge Omission Error that arises when ontologists does not elaborate the characteristics of the concept like its self description by using intersection, union, complement or restriction axioms in OWL. Second is Redundancy of Disjoint Relation Error that arises when ontologists made concept disjoint with other concept but in actual they are already disjoint as their parents are disjoint. In this paper we have shown our current findings about the evaluation of error taxonomy. We identified that some important incompleteness errors are missing