Nowadays, data plays a key role in organizations, and management of its quality is becoming an essential activity. As part of such required management, organizations need to draw up processes for measuring the data quality (DQ) levels of their organizational units, taking into account the particularities of different scenarios, available resources, and characteristics of the data used in them. ...

This article presents the top-level of an ontology categorizing and generalizing best practices and quality criteria or measures for Linked Data. It permits to compare these techniques and have a synthetic organized view of what can or should be done for knowledge sharing purposes. This ontology is part of a general knowledge base that can be accessed and complemented by any Web user. Thus, it ...

Many of the real-time tasks within embedded real-time control applications fall into the imprecise category. Such tasks are iterative in nature, with output precision improving as execution time increases (up to a point). These tasks can be terminated early at the cost of poorer quality output. Many imprecise tasks in CPS are dependent, with one task feeding other tasks in a task precedence gra...

Abstract National statistical institutes currently investigate how to improve the output quality of official statistics based on machine learning algorithms. A key issue is concept drift, that is, when joint distribution independent variables and a dependent (categorical) variable changes over time. Under model requires regular updating prevent it from becoming biased. However, asks for additio...

The performance of acoustic multichannel equalization techniques, which are based on estimating and inverting the room impulse responses (RIRs) between the source and the microphone array, is known to be very sensitive to estimation errors of the RIRs. In order to increase the robustness, it has been proposed to use regularization with the aim of decreasing the energy of the inverse filters. Th...

Data sets are generated today at an ever increasing rate in a host of new formats and vocabularies, each with its own data quality issues and limited, if any, semantic annotations. Without semantic annotation and cleanup, integrating across these data sets is difficult. Approaches exist for integration by semantically mapping such data using R2RML and its extension for heterogeneous sources, RM...

Mobile telecoms operators possess an enormous quantity of data, which could be used to reduce the cost of installing new infrastructure, to provide a better QoS or to plan their infrastructure. Thus, they are concerned to model, understand and predict SMS and calls activity levels in their infrastructures. Besides, SMS and call activities analysis can open new business opportunities for geomark...