Data Science and Big Data Area
Data Science is the discipline that gathers all the work of analysis on data sets that requires a considerable amount of skills in programming, engineering and software management, as well as extensive knowledge in Mathematics, Statistics and Computer Science.
Problem solving through Data Science involves a series of stages such as: understanding the data, extracting its properties, modeling and analyzing the problem, presenting results, and developing software to exploit the knowledge extracted. Data Science provides the tools to deal with and benefit from Big Data.
Big Data is creating new opportunities in all the aspects of technology by leveraging its most valuable asset: information. Big Data Technologies help improve efficiency, quality, and the personalized products and services offered by organizations. In scientific terms, Big Data Analysis opens new research horizons with potentially more promising results and deeper revelations than before. In many cases, Big Data analysis integrates structured and unstructured data with real-time responses, opening new paths to innovation and development.
Research Lines
Research lines in the area of Data Science and Big Data.
Information retrieval and recommendation systems
The primary aim of this research line is focused on improving the definition and development of mechanism and models applied…
More infoarrow_forwardNatural Language Processing and Social Network Analysis
The knowledge is one of the outcomes of the humankind, and it is encoded in natural language, which is the…
More infoarrow_forwardData Pre-Processing and Data Quality
In recent years, there has been an immense growth in data, leading to the Big Data. This requires large computing…
More infoarrow_forwardDescriptive Data Mining
Descriptive data mining techniques are aimed at describing the data or the phenomenon underlying the data, and are generally applied…
More infoarrow_forwardImage and video processing
The main goal of this research line is to create new theoretical and practical developments in the field of image…
More infoarrow_forwardAnomaly Detection
As Machine Learning (ML) is applied to increasingly sensitive tasks, and applied to increasingly noisy data, it has become important…
More infoarrow_forwardMachine Learning in non-standard problems
In recent years, new problems and paradigms have appeared in Machine Learning, which, in some way, do not fit into…
More infoarrow_forwardExplainable and responsible AI
Artificial Intelligence (AI) offers increasingly precise algorithms that make it possible to analyse all kinds of data or signals, such…
More infoarrow_forwardBlockchain and Data Protection
Blockchain is the underlying technology of all the crypto currencies that have been emerging in the first decades of the…
More infoarrow_forwardFederated Learning and Privacy
Federated Learning is a distributed learning paradigm which arises from both, the increasing awareness of data privacy and the growing…
More infoarrow_forwardTime series and real-time data analysis
A time series is a set of data relating to the measurement of a magnitude (scalar or vector) ordered in…
More infoarrow_forwardBig Data and Smart Data
At present, there is a growing trend on data generation, collection and processing in many different application areas, namely health,…
More infoarrow_forwardArea Coordinators
María José del Jesus Díaz, Universidad de Jaén
Sebastián Ventura, Universidad de Córdoba
Salvador García, Universidad de Granada