Data management

Leader: Dessislava Petrova-Antonova

Data management includes principles and techniques for data management such as data acquisition (collection, structuring and storing, generalization), data cleaning (consistency checking for out of range data records or extreme values, logical inconsistences finding, as well as treatment of missing responses), data aggregation and linking (transformation of large quantities of data to linked data through semantic web technologies), as well as privacy and anonymization mechanisms to facilitate data protection.

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Data analytics

Leader: Ivan Koychev

Data analytics includes processing and analysis of data to improve data understanding and the meaningfulness of data. Data processing is related to data modelling, analysis and reasoning including semantic and knowledge-based analysis, scalable and incremental reasoning, linked data mining and cognitive computing.

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Data insight

Data insight provides both accessibility and proper visualization, including advanced visualization techniques that consider a variety of Big Data (i.e. graphs, geospatial, sensor, mobile, etc.) available from diverse domains.

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Big Data engineering

Engineering and development affects all technology directions and considers the integration of science with engineering and design by adopting proper methodologies and toolchains.

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