In the big data era, personal data is, recently, perceived as a new oil or currency in the digital world. Both public and private sectors wish to use such data for studies and businesses. However, access to such data is restricted due to privacy issues. Seeing the commercial opportunities in gaps between demand and supply, the notion of personal data market is introduced. While there are severa...

Although many data warehouse systems have been developed in recent years, the practice of data warehouse is still immature. Most of current systems have some limitations in terms of flexibility, efficiency and scalability. Furthermore, the contents of a data warehouse are becoming a large and messy jungle. It is difficult to maintain and analyze the data. Much research has been done in data mar...

Association rules mining is one of the most successfully applied data mining methods in today’s business settings (e.g. Amazon or Netflix recommendations to customers). Qualified association rules mining is an extension of the association rules data mining method, that uncovers previously unknown correlations that only manifest themselves under certain circumstances (e.g. on a particular day of...

OBJECTIVE Electronically linked datasets have become an important part of clinical research. Information from multiple sources can be used to identify comorbid conditions and patient outcomes, measure use of healthcare services, and enrich demographic and clinical variables of interest. Innovative approaches for creating research infrastructure beyond a traditional data system are necessary. ...

In one of our previous papers, the idea of deductive data warehouses has been introduced. It was shown how to use Datalog rules to perform Online Analytical Processing (OLAP) analysis on data. In this paper, we show how to use Datalog rules to specify the data warehouse model (data mart) as well as how to add rules that produce aggregate and derived tables that are normally used to speed up the...

In this paper we examine the possibilities offered by the EU legal framework to set and regulate a data and meta-data market. It is our contention that a policy and legally-driven market could benefit from analytical concepts —meta-rule of law, semantic web regulatory models, legal ontologies— to reduce privacy and data protection risks. We introduce a general and integrated framework, and prov...

In equal employment cases it is important to compare the salary, hiring or promotion status of minority employees or applicants to that of similarly qualified majority members. Standard regression methods include a binary variable indicating minority status along with major job-related variables to assess whether belonging to a minority has a negative effect. Implicitly, this method assumes tha...