Big Data Research

This section showcases the Chair's research projects in the field of Big Data.

Index

Projects

A more detailed description of each project is provided below.

UDIGEN Project

He Taro Research Group The University of La Laguna participates in the project «"Development of a Genomic Diagnostic Unit (UDIGEN)"» from the national call for proposals "Challenges" of the Ministry of Science (RTC-2017-6471-1_UDIGEN) in collaboration with the Institute of Technology and Renewable Energies (ITER) and the Canary Islands Foundation for Health Research (FUNCANIS).

The overall objective of the UDIGEN project is the development of an integrated genomic analysis platform, from sequencing to interpretation, to facilitate genetic counseling and reduce the time between suspected genetic disease and a definitive diagnosis. This objective promotes technological development, innovation, and high-quality research, as specified in the thematic objective of the project's operational program.

As a result of this experience, the routine use of exome sequencing is expected to be introduced as a first-line test to support the diagnosis of genetic disorders, thereby reducing the time and costs required to obtain a definitive diagnosis. Furthermore, bioinformatics tools will be developed for managing, querying, and interpreting genetic variation and its connection to diseases through efficient Big Data analysis procedures.

DATALAI Project

The DATALAI project falls within the field of artificial intelligence and integrated big data analytics aimed at the epidemiological control of COVID-19. It consists of a tool that generates real-time information, capable of eradicating the current situation caused by COVID-19 and preventing such extreme situations in the future, thus avoiding the health, social, and economic collapse of society.

The proposed information system is composed of the following elements, each of which constitutes one of the objectives to be achieved in the development of the project:

  • A data repository, or Data Lake, that draws from different data sources and guarantees data persistence.
  • An ecosystem of AI-based processing tools for processing this data that are capable of:
    • Inferring geographic mobility patterns through mobile phone, public transport, air quality and ambient temperature data.
    • Identify the urban centers at highest risk based on mobility and the emergence of new COVID-19 outbreaks.
  • Dashboards for visualizing and analyzing the results obtained, geared towards decision-making and with real-time information.
  • Automatic generation of alerts that warn via email or Telegram
  • Integration with mobile apps to improve communication with citizens.

By integrating various existing data sources and ensuring compliance with the GDPR, the DATALAI project will allow the detection, in real time, of infection hotspots through algorithms based on Artificial Intelligence and Deep Learning that will be able to access the data automatically.

From the point of view of preventive control 

  • Identify Affected Areas where positive cases have occurred.
  • Identify the Zones and Establishments where residents of the affected areas have left a trace.
  • It proposes areas to be disinfected.
  • It proposes areas where rapid tests can be carried out. 

From the Individual's Point of View

  • Identify whether the different effects that the disease can have on an individual follow certain patterns.
  • Detect if there are common patterns that identify asymptomatic individuals, or Especially Sensitive Personnel (ESP).
  • Carry out special monitoring in affected or high-risk areas.