Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: Data quality assessment and data cleaning are context-dependent activities. Motivated by this observation, we propose the Ontological Multidimensional Data Model (OMD model), which can be used to model and represent contexts as logic-based ontologies. e data under assessment is mapped into the context, for additional analysis, processing, and quality data extraction. e resulting contexts allow for the representation of dimensions, and multidimensional data quality assessment becomes possible. At the core of a multidimensional context we include a generalized multidimensional data model and a Datalog± ontology with provably good properties in terms of query answering. ese main components are used to represent dimension hierarchies, dimensional constraints, dimensional rules, and dene predicates for quality data specication. ery answering relies upon and triggers navigation through dimension hierarchies, and becomes the basic tool for the extraction of quality data. e OMD model is interesting per se, beyond applications to data quality. It allows for a logic-based, and computationally tractable representation of multidimensional data, extending previous multidimensional data models with additional expressive power and functionalities.

Ontological Multidimensional Data Models and Contextual Data Quality