The National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) is hosting a two-day virtual workshop titled “Big Data Integration: Unlocking the Potential for Enhanced Epidemiological Research” on September 27-28, 2023.
The purpose of the workshop is to improve the use of big-data for population studies by promoting an understanding of current scientific research. The workshop will create a platform for researchers to discuss the importance of data standards and harmonization for reproducibility in research. This will allow for the sharing of ideas and experiences in integrating different data sources and types, as well as leveraging established data tools and techniques. The goal is to encourage collaboration and networking among researchers from various fields in order to share best practices and insights on data integration and analysis. The workshop also aims to inspire innovative approaches to epidemiological research by integrating diverse data sources and utilizing advanced data analysis tools and techniques.
- Evaluate current scientific research and identify gaps in big-data use for population-based research and analysis.
- Review and summarize the current state of population-based research big data generation and analytical tools.
- Review innovative strategies for extracting biological meaning from large volumes of data
- Examine the limitations and challenges of using data from multiple sources in population-based research.
- Promote a dialogue within the research community about the importance of data standards and data harmonization for reproducibility and its applications in research.
- Detect gaps in scientific research or workflows that impede the efficient utilization of multiple data sources, hinder scientific reproducibility, or introduce methodology or algorithm biases.
- Offer insights and research opportunities to address these gaps and enhance the use of population-based data for epidemiological analysis.
- Integrate different data sources and data types, and leverage proven data tools/techniques for improved population-based research.
- Identify different data sources and data types that can be integrated to improve population-based research.
- Explore the advantages and challenges of integrating these data sources, including the application of machine learning and other established data tools/techniques.
- Showcase instances of successful integration of multiple data sources in various fields and assess their potential for adaptation to similar data infrastructures.
- Propose recommendations on how to effectively merge different data sources and harness established data tools/techniques to advance population-based research.
- Offer insights and research opportunities to address these challenges and enhance data integration for epidemiological analysis.
This workshop is open to the public and will be recorded. View the agenda and registration details.
Individuals with disabilities who need Sign Language Interpreters and/or reasonable accommodation to participate in this event should contact the NHLBI Workshop Support Program at NHLBIWorkshopSupport@nih.gov. Requests need to be made five (5) days in advance.
For logistical questions or to request reasonable accommodations to participate in this event, email Workshop Coordinator Alexandra Guillermety at NHLBIWorkshopSupport@nih.gov. For programmatic questions, email Workshop Chair Dr. Gabriel Anaya at Gabriel.email@example.com.