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Data science education resources for everyoneNicole Vasilevsky, Jackie Wirz, Bjorn Pederson, Ted Laderas, Shannon McWeeney, William Hersh, David A. Dorr, Melissa Haendel
Oregon Health & Science University
MLA/PNC 2016
The problem
Major challenge: how to manage, analyze and interpret vast amounts of data being generated in biomedical research
One goal of NIH Big Data to Knowledge (BD2K) initiative: provide training for students and researchers to address this
Research team in the Library and Department of Medical Informatics and Clinical Epidemiology (DMICE) is developing skills courses and open educational resources (OERs)
http://whelf.ac.uk/activity-data-delivering-benefits-from-the-data-deluge/
Our Approach
Skills courses and OERs connect the dots that help researchers understand how to apply data science techniques in the context of their whole research life cycle
Skills courses and OER topics are aimed to fill specific gaps
BD2K Skills Courses
Taught by BD2K Faculty, Post-doc and Staff In person format Targeted to a variety of
students
Defining The Problem Wrangling Data
Data Identification And Resources
Problems amenable to analytics Importance of question Team definitions Scope When we do this wrong: methods don't match
Finding the right data Search methods
Use of metadata Data management
Exploratory Data Analysis Data Dictionary As you touch data, what can go wrong?
Methods, Tools And Analysis Scientific Communication
Visualization Matching algorithms to problems
… Reporting Findings and Limitations Giving “Elevator Speech” on ideas of how to
approach problem Critique of related problem
Course OfferingsCourse Length Who WhatWhen
Intro Course Week long course (~40 hrs)
July2015
Interns and undergraduates
Taught basics of data science in the context of the research life cycle
Data After Dark 2 evening course (4 hrs/nt)
January 2016
OHSU students, staff and faculty
Emerging data science activities/research impact
Data and Donuts 2 morning course (3 hrs/day)
June 2016
OHSU Summer interns
Basics of data science
Advanced Course 4 evening course (2 hrs/nt)
May 2016
OHSU students, staff and faculty
Hands on Data viz / Data wrangling
Data and Donuts West
4 hour courseJuly 2016
OHSU summer interns (West Campus)
Basics of data science
Evaluation of Skills Courses
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Evaluation Summary from Beginnner Students
Beginner Percent 6 & 7 Beginner Percent 3, 4 & 5Beginner Percent 1 & 2
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Evaluation Summary from Advanced Students
Advanced Percent 6 & 7 Advanced Percent 3, 4 & 5Advanced Percent 1 & 2
The instructors clearly presented the skills to be learned
The instructors presented content in an organized manner
The instructors effectively presented concepts and techniques
OER Modules01 | Biomedical Big Data Science02 | Introduction to Big Data in Biology and Medicine 03 | Ethical Issues in Use of Big Data 04 | Clinical Standards Related to Big Data05 | Basic Research Data Standards06 | Public Health and Big Data07 | Team Science 08 | Secondary Use (Reuse) of Clinical Data 09 | Publication and Peer Review10 | Information Retrieval 11 | Version Control and Identifiers 12 | Data annotation and curation 13 | Data Tools and Landscape14 | Ontologies 10115 | Data metadata and provenance 16 | Semantic data interoperability 17 | Choice of Algorithms and Algorithm Dynamics 18 | Visualization and Interpretation
19 | Replication, Validation and the spectrum of Reproducibility Semantic data interoperability
20 | Regulatory Issues in Big Data for Genomics and Health Semantic Web data
21 | Hosting data dissemination and data stewardship workshops
22 | Hosting data dissemination and data stewardship workshops
23 | Terminology of Biomedical, Clinical, and Translational Research
24 | Computing Concepts for Big Data25 | Data modeling26 | Semantic Web data27 | Context-based selection of data28 | Translating the Question29 | Implications of Provenance and Pre-processing30 | Data tells a story31 | Statistical Significance, P-hacking and Multiple-testing32 | Displaying Confidence and Uncertainty
https://dmice.ohsu.edu/bd2k/topics.html
What is available in the modules?
Module Overview Online viewing Powerpoint files Audio files
Exercises References Resources
MLA- Professional Competencies For Health Sciences Librarians
https://dmice.ohsu.edu/bd2k/mapping_MLA.html
Competency #1Understand the health sciences and health care environment and the policies, issues, and trends that impact that environment
BDK02 - Introduction To Big Data In Biology And MedicineBDK03 - Ethical Issues In Use Of Big DataBDK07- Team Science
Competency #3Understand the principles and practices related to providing information services to meet users' needs
BDK10 - Information RetrievalBDK22 - Guidelines For Reporting, Publications, And Data Sharing
Competency #4Have the ability to manage health information resources in a broad range of formats
BDK09 - Publication And Peer ReviewBDK12 - Data Annotation And CurationBDK14 - Ontologies 101BDK15 - Data Metadata And Provenance
Competency #5Understand and use technology and systems to manage all forms of information
BDK10 - Information RetrievalBDK12 - Data Annotation And CurationBDK13 - Data and tools landscapeBDK14 - Ontologies 101BDK26 - Introduction to Semantic Web data
Competency #6Understand curricular design and instruction and have the ability to teach ways to access, organize, and use information
BDK21 - Hosting Data Dissemination And Data Stewardship Workshops
Competency #7Understand scientific research methods and have the ability to critically examine and filter research literature from many related disciplines
BDK07- Team ScienceBDK18 - Visualization And InterpretationBDK19 - Replication, Validation And The Spectrum Of Reproducibility
BDK01 - Biomedical Big Data Science
BDK04 - Clinical Data And Standards Related To Big DataBDK05 - Basic Research Data Standards
BDK04 - Clinical Data And Standards Related To Big DataBDK05 - Basic Research Data Standards
Challenges
Scope
Images
Style
Dissemination
How to scope generic curricula for different levels of users
How to translate diverse teaching styles into general materials
How to maximize dissemination while protecting intellectual property
How to incorporate images and other copyrighted materials into open resources
Who are these resources for? EVERYONE!
thenounproject.com
Undergraduate Students
Graduate Students
Clinicians Post-docs
Librarians Staff Faculty
Help review our modules:https://dmice.ohsu.edu/bd2k/topics.html
Acknowledgements
Bill Hersh, PI Melissa Haendel, PI Shannon McWeeney, PI David Dorr, PI
Ted Laderas,Instructor
Jackie Wirz,Instructor
Nicole Vasilevsky,Instructor
Bjorn Pederson, Instructional Designer
This work is supported by NIH Grants 1R25EB020379-01 and 1R25GM114820-01.
You can find me at:@[email protected]
Thanks!