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Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the same time, data variety increases continuously across multiple axes. First, data comes in mu ...
Medical data are often scattered among multiple clinics, hospitals, insurance companies, pharmacies, and research institutions that store and process personal healthcare information. The use of information and communication technologies for health (eHealth ...
As data collections become larger and larger, users are faced with increasing bottlenecks in their data analysis. More data means more time to prepare and to load the data into the database before executing the desired queries. Many applications already av ...
This article investigates the evolution of data quality issues from traditional structured data managed in relational databases to Big Data. In particular, the paper examines the nature of the relationship between Data Quality and several research coordina ...
Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...
Aspect Term Extraction (ATE) detects opinionated aspect terms in sentences or text spans, with the end goal of performing aspect-based sentiment analysis. The small amount of available datasets for supervised ATE and the fact that they cover only a few dom ...
Sensor datasets on the Web are becoming increasingly available, and there is a need for making them discoverable and accessible, so that they can be reused despite their heterogeneity. While RDF and Linked Data provide fundamental principles for sharing da ...
The article investigates the potential role of conceptual modeling for policymaking. It argues that the use of conceptual schemas may provide an effective understanding of public sector information assets, and how they might be used to satisfy the needs of ...
The joint consideration of big data and analytics is a relatively recent development, particularly, within the domain of Management of Information Systems (MIS). In recent years there is a dramatic increment of the data produced by digital devices and syst ...
Nowadays, business and scientific applications accumulate data at an increasing pace. This growth of information has already started to outgrow the capabilities of database management systems (DBMS). In a typical DBMS usage scenario, the user should define ...
