Bio-medical Ontologies Maintenance and Change Management

Extraction of Constraints from Biological Data
Daniele Apiletti, Giulia Bruno, Elisa Ficarra, and Elena Baralis
Department of Control and Computer Engineering (DAUIN),
Politecnico di Torino
C.so Duca degli Abruzzi 24, 10129 Torino, Italy
1 Introduction
Data constraints are used in structured and unstructured databases to capture realworld
semantics observed in the modeled application domain. In our context, a
constraint can be defined as a set of predicates P 1 ∧ P 2 ∧ ... P k . Each predicate is in
the form C 1θ C 2 , where C 1 is an attribute, θ is a comparison operator and C 2 is either
an attribute or a constant [15]. Constraints are assertions on permissible or
consistent database states, and specify certain properties of data that need to be
satisfied by valid instances of the database.
Constraints show dependencies among data and add semantics to a database
schema. Thus, they are useful for studying various problems such as database
design, query optimization and dimensional reduction. Constraints are usually
introduced at design time to describe a priori knowledge. Consequently, the valid
instances of the database are those satisfying simultaneously all constraints. However,
collected data can hide interesting and previously unknown information because
of unstated constraints. For example, this happens when data is the result of
an integration process of several sources or when it represents dynamic aspects.
Furthermore, the design process is not always complete and the constraint definition
may be omitted from the design. The analysis of heterogeneous data with the
aim of detecting implicit information is in important and useful task, which may
become complex due to the size of datasets.
Among the numerous constraint types, we focus on table constraints, which refer
to a single relation of the database. Examples of such constraints are domain
constraints and tuple constraints. A domain constraint restricts allowed values of a
single attribute, i.e. it describes its domain. A tuple constraint limits the allowed
values for several (related) attributes of the same tuple. Constraints are properties
of the database schema, thus they can not be directly inferred from data. We will
denote this type of constraints as schema constraints. However, if the constraints
are not a priori known, they can be hypothesized by analyzing database instances.
We can not directly infer schema constraints from data, but we can infer instance
constraints, i.e., constraints which represent the current relationships holding
among data. Instance constraints represent a snapshot on the current database state
A.S. Sidhu et al. (Eds.): Biomedical Data and Applications, SCI 224, pp. 169–186.
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