In the recent year, social networks have revolutionized the ways of interacting and
exchanging information on the Internet. Millions of users interact frequently and share variety …

In secondary data use context, traditional data warehouse design methods don't address
many of today's challenges; particularly in the healthcare domain were semantics plays an …

With the tremendous growth of social networks, there has been a growth in the amount of
new data created every minute on these networking sites. Twitter acts as a great source of …

Data warehousing projects still face challenges in the various phases of the development
life cycle. In particular, the success of the design phase, the focus of this paper, is hindered …

The design process of a data warehouse (DW) raises many problems and then is
considered as a complex and tedious task. DW designers follow different levels concerning …

Multidimensional schemas are used to model data warehouse systems, a special type of
large databases dedicated for decision support. Several approaches have been proposed in …

Designing a multidimensional model is a non-trivial task: the requirements collected from
senior managers can be inaccurate and difficult to use, especially when they are not …

The design phase of a data warehousing project remains difficult for both decision makers
and requirements analysts. In this paper, we tackle this difficulty through two contributions …

As the amount of textual information grows explosively in various kinds of business systems,
it becomes more and more essential to analyze both structured data and unstructured …

Aiming at the unstructured brain data and data-driven research process, provenances have
become an important component of brain and health big data rather than the accessory of …