Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data
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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 ...
With the emergence of brain research initiatives around the world, the need for standards to facilitate neuroscience data sharing is growing. A crucial first step will be to establish a minimal metadata standard that allows the discovery of and access to s ...
In the context of next generation radio telescopes, like the Square Kilometre Array, the efficient processing of large-scale datasets is extremely important. Convex optimisation tasks under the compressive sensing framework have recently emerged and provid ...
Wrong manipulation, storage or disposal of chemicals can cause great damage whether it occurs on industrial plants, in academia or at home. Amongst the numerous reasons, lack of knowledge and haste are the most common ones. Except for a few substances subj ...
Many software systems consist of data processing components that analyse large datasets to gather information and learn from these. Often, only part of the data is relevant for analysis. Data processing systems contain an initial preprocessing step that fi ...
Many analytics applications generate mixed workloads, i.e., workloads comprised of analytical tasks with different processing characteristics including data pre-processing, SQL, and iterative machine learning algorithms. Examples of such mixed workloads ca ...
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 ...
In recent years, ontology for the Product Lifecycle Management domain has raised a lot of interest in research communities, both academic and industrial. It has emerged as a convenient method for supporting the concept of closed lifecycle information loop, ...
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 ...
Big-Data streaming applications are used in several domains such as social media analysis, financial analysis, video annotation, surveillance, medical services and traffic prediction. These applications, running on different types of platforms from mobile ...
