Authors:
Fatma Abdelhedi
1
;
Amal Ait Brahim
2
;
Faten Atigui
3
and
Gilles Zurfluh
2
Affiliations:
1
CBI2 – TRIMANE, France
;
2
Toulouse Institute of Computer Science Research (IRIT) and Toulouse Capitole University, France
;
3
CEDRIC-CNAM, France
Keyword(s):
Big Data, NoSQL, Knowledge, MDA, QVT Transformation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Enterprise Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Symbolic Systems
;
Tools and Technology for Knowledge Management
Abstract:
In 2014, Big Data has passed the top of the Gartner Hype Cycle, proving that Big Data technologies and
application start to be mature, becoming more realistic about how Big Data can be useful for organizations.
NoSQL data stores are becoming widely used to handle Big Data; these databases operate on schema-less
data model enabling users to incorporate new data into their applications without using a predefined
schema. But, there is still a need for a conceptual model to define how data will be structured in the
database. In this paper, we show how to store Big Data within NoSQL systems. For this, we use the Model
Driven Architecture (MDA) that provides a framework for models automatic transformation. Starting from
a conceptual model that describes a set of complex objects, we propose transformation rules formalized with
QVT to generate a column-oriented NoSQL model. To ensure efficient automatic transformation, we use a
logical model that limits the impacts related to techni
cal aspects of column-oriented platforms. We provide
experiments of our approach using a case study example taken from the health care domain. The results of
our experiments show that the proposed logical model can be effectively implemented in different columnoriented
systems independently of their specific technical details.
(More)