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Data integration working group meeting
June 5 @ 3:00 pm - 4:30 pm
Weiser Hall, MIDAS, Suite 600
Data integration is an essential component of data science research in almost all research areas that use heterogeneous data varying in format, dimensionality, quality and granularity. The examples are endless: multi-omics data integration is increasingly critical in biological research; clinical research benefits greatly from the integration of patient longitudinal data, lab data, sensor data and other types of diagnosis and self-report; environmental monitoring often needs the integration of statistical data, image data and geospatial data; social science research, including education, political science and economics, increasingly integrates social media and other web-based data with traditional survey data… All the applications encounter similar data science challenges, including idiosyncratic integration methods, missing data, bias and coverage, consistency and quality control issues. Our working group welcomes researchers with interest in data integration methodology and its application in any scientific domain. The Michigan Institute for Data Science (MIDAS) continues to convene a research working group on data integration to create a forum that will foster new ideas and collaborations.
- Informal talks.
- Vyas Ramasubramani (Chemical Engineering, student of Sharon Glotzer) will talk about their work in collaboration with Simon Adorf to develop a software package (the signac framework) for data and workflow management.
- Stilian Stoev (Professor, Statistics) will talk about data integration issues when examining the Argo data (a global array of 3,800 free-drifting profiling floats allows the continuous monitoring of the temperature, salinity, and velocity of the upper ocean).
- Open discussion on ideas and collaboration.
Please sign up using the online form. For questions, please email Jing Liu, MIDAS Senior Scientist, email@example.com