[Skip to Content]
Visit us on YouTube Visit us on Twitter View our RSS Feed
The MidContinental Messenger
IssuesIssuesIssues Contact UsContact Us ArchivesArchives Region/OfficeMCR Website SearchSearch

Learn the Fundamentals of Data Science


Discuss With Your Colleagues – Earn MLA CE

The NN/LM MCR is strongly encouraging health sciences librarians to support biomedical big data research at their institutions. One of the barriers preventing this support is a lack of knowledge on what data science researchers do and what librarians can do to support them. A relatively simple strategy is to increase knowledge in this exciting topic area. To support the education of non-data scientists, the National Institutes of Health’s Big Data to Knowledge (BD2K) Initiative has been delivering free weekly virtual lectures. The series started in September 2016 and will run through May 2017.  The lectures have been excellent and, despite covering a complex field of study, the enthusiastic presenters have been able to deliver them in a way that is understandable. Each lecture has been archived and is available on the BD2K web site.

To further aid in learning, the NN/LM MCR is offering additional support for Network members to become more informed about how to support big data researchers.  The support comes in two ways. The first is for Network members to attend a 30 minute debrief session following the weekly BD2K Fundamental sessions. The second is for members to register for the asynchronous debrief session. In both ways, attendees will have a chance to discuss with peers the roles librarians can play to support researchers at their institution. Discussions will focus on the assets librarians bring to the table, identify skills and resources needed to provide services, and identify the most important stakeholders librarians need to align with to get a seat at the table. Each virtual lecture and debrief session attended will earn participants 2 MLA Continuing Education contact hours.

[To join the live discussions or attend the asynchronous sessions, go to the NN/LM MCR professional development web page for information. If you have any questions, please contact the instructors john.bramble@utah.edu or shirley.zhao@utah.edu]

Take a look at some of the past and future topics. Consider viewing them live or at your own pace. Attend the debrief sessions and earn MLA CE.

– John Bramble, Utah/Research Enterprise Coordinator

The BD2K Guide to the Fundamentals of Data Science Series

9/9/2016 -Introduction to Big Data and the Data Lifecycle
Speaker: Mark Musen
Stanford University
View slides | View lecture abstract & speaker biography
9/16/2016 – Data Indexing and Retrieval
Speaker: William Hersh
Oregon Health & Science University
View slides | View lecture abstract & speaker biography
9/23/2016 – Finding & Accessing Datasets, Indexing & Identifiers
Speaker: Lucila Ohno-Machado
University of California San Diego
View slides | View lecture abstract & speaker biography
9/30/2016 – Data Curation and Version Control
Speaker: Pascale Gaudet
Swiss Institute of Bioinformatics
View slides | View lecture abstract & speaker biography
10/7/2016 – Ontologies
Speaker: Michel Dumontier
Stanford University
View slides | View lecture abstract & speaker biography
10/14/2016 – Provenance
Speaker: Zachary Ives
University of Pennsylvania
View slides | View lecture abstract & speaker biography
10/21/2016 – Metadata Standards
Speaker: Susanna-Assunta Sansone
University of Oxford
View slides | View lecture abstract & speaker biography
10/28/2016 – Data Representation Overview
Speaker: Anita Bandrowski
University of California San Diego
View slides | View lecture abstract & speaker biography
11/4/2016 – Databases & Data Warehouses, Data: Structures, Types, Integrations
Speakers: Chaitan Baru & Elena Zheleva
National Science Foundation
View slides | View lecture abstract & speaker biography
11/18/2016 – Data Wrangling, Normalization & Preprocessing: Part I Signals
Speaker: Joseph Picone
Temple University
View slides | View lecture abstract & speaker biography
12/02/2016 – Data Wrangling Normalization & Preprocessing: Part II Text
Speaker: Sanda Harabagiu
University of Texas at Dallas
View slides | View lecture abstract & speaker biography
12/09/2016 – Exploratory Data Analysis
Speaker: Brian Caffo
Johns Hopkins University
View slides | View lecture abstract & speaker biography
12/16/2016 – Natural Language Processing-NLP
Speaker: Noemie Elhadad
Columbia University
View slides | View lecture abstract & speaker biography
1/6/2017 – Computing Overview
Speaker: Patricia Kovatch
Icahn School of Medicine at Mount Sinai
View slides | View lecture abstract & speaker biography
1/13/2017- Workflows & Pipelines
Speaker: Rommie Amaro
University of California, San Diego
1/20/2017 – Running a Data Sciences Laboratory: Infrastructure and Applications
Speaker: Trey Ideker
University of California, San Diego
1/27/2017 – Modern Computing: Cloud, Distributed, & High Performance
Speaker: Umit Catalyurek
The Ohio State University, Columbus
2/3/2017 – Commons: Lessons Learned, Current State
Speaker: Vivien Bonazzi
National Institutes of Health, Bethesda
2/10/2017 – Data Modeling & Inference Overview
Speaker: Rafa Irizarry
Harvard University
2/17/2017 – Supervised Learning, prediction, Machine Learning & Dimensionality Reduction
Speaker: Daniela Witten
University of Washington
2/24/2017 – Smoothing, Unsupervised Learning, Clustering & Density Estimation
Speaker: Ali Shojaie
University of Washington
3/3/2017 – Algorithms & Optimization
Speaker: Pavel Pevzner
University of California, San Diego
3/10/2017 – Bayesian Inference
Speaker: Mike Newton
California State University, Sacramento
3/17/2017 – Data Issues: Multiple testing, Bias, Confounding & Missing Data
Speaker: Lance Waller
Emory University
3/24/2017 – Causal Inference
Speaker: Joe Hogan
Brown University
3/31/2017 – Data Visualization Tools & Communication
Speaker: Nils Gehlenborg
Harvard University
4/7/2017 – Modeling Synthesis
Speaker: John Harer
Duke University
4/14/2017 – Open Science
Speaker: Brian Nosek
University of Virginia
4/21/2017 – Data Sharing & Social Obstacles
Speakers: Christine Borgman & Irene Pasquetto
UCLA
4/28/2017 – Ethical Issues
Speaker: Bartha Knoppers
McGill University
5/5/17 – Reproducibility
Speaker: John Ionnaidis
Stanford University
5/12/2017 – Considerations & Limitations for Clinical Data
Speaker: Zak Kohane
Harvard University

The MidContinental Messenger is published quarterly by the National Network of Libraries of Medicine MidContinental Region

Spencer S. Eccles Health Sciences Library
University of Utah
10 North 1900 East, Building 589
Salt Lake City, Utah 84112-5890

Editor: Suzanne Sawyer, Project Coordinator
(801) 587-3487
suzanne.sawyer@utah.edu

This project has been funded in whole or in part with Federal funds from the Department of Health and Human Services, National Institutes of Health, National Library of Medicine, under cooperative agreement number UG4LM012344 with the University of Utah Spencer S. Eccles Health Sciences Library.

NNLM and NATIONAL NETWORK OF LIBRARIES OF MEDICINE are service marks of the US Department of Health and Human Services | Copyright | Download PDF Reader