DSLab Apps
Data Science Applications from Rey Juan Carlos University
Welcome to DSLab Apps
Innovative data science applications developed by the Data Science Lab at Universidad Rey Juan Carlos
The Data Science Lab (DSLAB) coordinates and fosters research, education, innovation and knowledge transfer on data science and big data. Our applications demonstrate cutting-edge research in machine learning, optimization, and statistical modeling applied to real-world challenges.
Featured Applications
PACE - Performance Analytics and Competitions Evaluation
Sports Performance Analysis Platform
Transform large volumes of sports data into actionable insights. PACE provides athletes and coaches with predictive analytics, race simulations, and performance optimization tools to drive competitive success.
- Race outcome predictions
- Performance trend analysis
- Strategic recommendations
- Victory probability calculations
EVASTOUR - Sustainable Tourism
Tourism Indicators Management Platform
Comprehensive platform for analyzing and managing sustainable tourism indicators. EVASTOUR helps tourism professionals make data-driven decisions aligned with Sustainable Development Goals.
- Tourism indicator exploration
- Comparative analysis tools
- Predictive modeling
- SDG alignment assessment
DICYME - Dynamic Industrial Cyber Risk Modelling based on Evidence
Industrial Cyber Risk Modelling Platform
Research project addressing automation of cyber risk assessment and management in OT cybersecurity environments. DICYME examines how threats vary depending on infrastructure vulnerabilities, control strength, and external attacker motivations.
- Cyber risk automation
- OT-focused threat modeling
- Evidence-based decision support
- Visualization dashboard for analysis
OBEPE - EPE Tecendo Conexões ETL
Energy Planning Platform
Prototype and public dashboards for the OBEPE project, developed with EPE to support energy planning through interactive data visualization and reproducible Shiny apps.
- Prototype dashboard access
- Public dashboard integration
- Documentation and technical notes
- R package for deployment and reproducibility
CRAS - Cybersecurity Risk Analysis and Simulation
Shiny App for Cybersecurity Risk Analysis
CRAS is a Shiny application for simulating and analyzing cybersecurity risks. Users can model potential events and assess their impact to support risk management decisions.
- Simulation inputs
- Customizable parameters for magnitude and loss event frequency
- Scenario analysis between proposed and current values
- Report generation
SIAGRO - Farm Production Analysis
Shiny App for Farm Data Analysis
SIAGRO is a Shiny app developed for analyzing farm production data. The application provides a structured dashboard to explore, analyze, and report on agricultural data from multiple files.
- Products tab
- Analysis modules
- Global report tab
AfCIOT - African Continental Input Output Table
Shiny App for African Data Analysis
AfCIOT is a project developed by UNECA to develop data applications.
- Focused on Africa
- Statistical model built on the data and statistics collected and compiled by African countries.
CitizenLab
Shiny App for Predictive Citizen Behavior and Economic Development
CitizenLab is a data-driven platform that analyzes and models citizen behavior to create innovative business systems where citizens themselves are the main beneficiaries.
Use cases developed by DSLAB:
Tourism
Health
Infrastructures
About the Data Science Lab
The Data Science Lab at Universidad Rey Juan Carlos is dedicated to advancing the field of data science through:
- Research & Innovation: Developing novel statistical and computational methods
- Education & Training: Offering courses and workshops in data science
- Knowledge Transfer: Providing strategic consulting and technology integration support
Our multidisciplinary team combines expertise in machine learning, optimization, statistical modeling, and big data to tackle complex real-world problems across various domains.