Informatics Professor: Biomedical Big Data Science Open Educational Resources (OERs) Released; Feedback Sought

For the last couple years, faculty from the Oregon Health & Science University (OHSU) Department of Medical Informatics & Clinical Epidemiology (DMICE) and Library have been developing open educational resources (OERs) in the area of Biomedical Big Data Science. Funded by a grant from the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) Program, OERs have been produced that can be downloaded, used, and repurposed for a variety of educational audiences by both learners and educators.

Development of the OERs is an ongoing process, but we have reached the point where a critical mass of the content is being made available for use and to obtain feedback. The image below shows the home page for the Web site.

The OERs are intended to be flexible and customizable and we encourage others to use or repurpose these materials for training, workshops and professional development or for dissemination to instructors in various fields. They can be used as "out of the box" courses for students, or as materials for educators to use in courses, training programs, and other learning activities. We ultimately aim to create 32 modules on the following topics:

Biomedical Big Data Science
Introduction to Big Data in Biology and Medicine
Ethical Issues in Use of Big Data
Clinical Standards Related to Big Data
Basic Research Data Standards
Public Health and Big Data
Team Science
Secondary Use (Reuse) of Clinical Data
Publication and Peer Review
Information Retrieval
Version Control and Identifiers
Data Annotation and Curation
Data Tools and Landscape
Ontologies 101
Data Metadata and Provenance
Semantic Data Interoperability
Choice of Algorithms and Algorithm Dynamics
Visualization and Interpretation
Replication, Validation and the Spectrum of Reproducibility
Regulatory Issues in Big Data for Genomics and Health Semantic Web Data
Hosting Data Dissemination and Data Stewardship Workshops
Guidelines for Reporting, Publications, and Data Sharing
Terminology of Biomedical, Clinical, and Translational Research
Computing Concepts for Big Data
Data Modeling
Semantic Web Data
Context-based Selection of Data
Translating the Question
Implications of Provenance and Pre-processing
Data Tells a Story
Statistical Significance, P-hacking and Multiple-testing
Displaying Confidence and Uncertainty

At the present time, 20 of the above modules are available for download and use. We are encouraging their use and seeking feedback from those who make use of them. The feedback will be used to improve the available modules and guide development of those not yet released.

We have also been developing mappings to research competencies in other areas, such as for the NIH Clinical and Translational Science Award (CTSA) consortium research competency requirements and the Medical Library Association professional competencies for health sciences librarians. To this end, we have been able to link these materials to existing efforts, and provide training opportunities for learners and educators working in these areas. We ultimately aim to complete this mapping across all of the BD2K training offerings, to align with other groups, avoid redundancy and to ensure we are meeting the needs of these various groups.

This project is actually one of several projects that have been funded by grants to develop and provide education in biomedical informatics and data science. The other projects include: