Bio-medical Ontologies Maintenance and Change Management

178 D. Apiletti et al.
Rules shown in Table 2 allow us to infer two quasi tuple constraints, which
have a high confidence (e.g., greater than 70%):
1. (Class = Mammalia) → (Reproduction = vivipary) [with confidence of 75.2%]
2. (Class = Aves) → (Reproduction = ovipary) [with confidence of 99.7%]
The first rule means that the majority of mammalians (75.2%) stored in the database
are vivipary, the second one that almost all the birds (99.7%) are ovipary.
To compute the dependency degree between Class and Reproduction we consider
all the extracted rules that involve the two attributes (not only those that are
reported in Table 2) and we obtain a value of 0.95. Supposing to set a threshold of
0.05, this value is high enough to state that there is a quasi functional dependency
between the two attributes, as reported in Table 3.
Table 3. Dependency degree between Class and Reproduction
Quasi-functional dependency Dependency degree
Class → Reproduction 0.95
4.2 Violations of Constraints and Dependencies
Constraint extraction has the double aim of discovering hidden relationships
among data, which may improve domain knowledge and data quality, and investigating
anomalies with respect to these relationships. If a quasi tuple constraint or a
quasi functional dependency has been detected, it means that there are few cases
in which the relationship is not valid. Such cases are anomalies with respect to the
frequent ones. These anomalies can be errors or exceptions in the data. Analyzing
such anomalies can be useful in different application domains to perform data
cleaning or improve the context knowledge.
To better investigate the nature of the detected anomalies, we can analyze the
confidence of the rules that involve the attribute values of the quasi tuple constraint
or the quasi functional dependency. If this value is very low (compared to
the confidence value of the other rules), we can strongly suggest that this is an error,
otherwise it is more likely to be a correct exception.
With respect to the Animal relation introduced in the previous section, we investigate
the rules that involve Class and Reproduction with a low confidence
(i.e., lower than 30%). We find the following rules:
1. (Class = Mammalia) → (Reproduction = ovipary) [with confidence of 24.8%]
2. (Class = Aves) → (Reproduction = vivipary) [with confidence of 0.3%]
Both of them represent interesting cases. The first one is a correct, albeit infrequent,
relationship, since there are some mammalians which lay eggs (such as the
Ornithorhynchus). The second one is an error, since there is no bird that is not
ovipary. There is a mistake in the 100th row because the Passer Domesticus has an
ovipary reproduction.