BIGCIDIA: Big Data and Data Science: Challenges in the Application of Artificial Intelligence in Data Analysis
We have recently witnessed a massive growth in the amount of information that computer systems are capable of capturing and storing. At the same time, new computing technologies have been developed to successfully manage such vast data sources. The synergy between the two has allowed the establishment of Big Data, which is associated with the analysis and interpretation of large volumes of data for the extraction of useful and valuable knowledge.
Therefore, fields such as Artificial Intelligence in general, and Automatic Learning in particular, have evolved significantly. Big Data involves the design and development of new tools and scalable algorithms to solve the tasks of managing, analyzing, synthesizing, visualizing and above all discovering the underlying knowledge in massive data. Examples are the new tools based on Spark, or the use of Deep Learning techniques.
Objectives
The purpose of this Network is articulated around several axes of study and debate, to enhance and strengthen the research of participating groups:
- Obtaining quality data in Big Data and data science environments
- Development of new models of Big Data, Deep Learning and Data Science according to the real scope of application.
- Obtaining models that can be interpreted in Big Data and Deep Learning.
- Data fairness, treated in a transversal way in the different axes.
- Application of Big Data technologies in our socio-economic environment and in the challenges of the United Nations (17 objectives for sustainable development).
Project
/research/projects/big-data-e-ciencia-de-datos-retos-na-aplicacion-da-intelixencia-artificial-na-analise-de-datos
<p>We have recently witnessed a massive growth in the amount of information that computer systems are capable of capturing and storing. At the same time, new computing technologies have been developed to successfully manage such vast data sources. The synergy between the two has allowed the establishment of Big Data, which is associated with the analysis and interpretation of large volumes of data for the extraction of useful and valuable knowledge.</p> <p>Therefore, fields such as Artificial Intelligence in general, and Automatic Learning in particular, have evolved significantly. Big Data involves the design and development of new tools and scalable algorithms to solve the tasks of managing, analyzing, synthesizing, visualizing and above all discovering the underlying knowledge in massive data. Examples are the new tools based on Spark, or the use of Deep Learning techniques.</p><p>The purpose of this Network is articulated around several axes of study and debate, to enhance and strengthen the research of participating groups:</p> <ul> <li>Obtaining quality data in Big Data and data science environments</li> <li>Development of new models of Big Data, Deep Learning and Data Science according to the real scope of application.</li> <li>Obtaining models that can be interpreted in Big Data and Deep Learning.</li> <li>Data fairness, treated in a transversal way in the different axes.</li> <li>Application of Big Data technologies in our socio-economic environment and in the challenges of the United Nations (17 objectives for sustainable development).</li> </ul> - José María Alonso Moral
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