This one hour online training will cover how to import publication data from Web of Science into biblioshiny to quickly create dynamic visualizations related to author, country, and topic/keyword trends for a collection of publications. This training will introduce biblioshiny, a web interface for the R programming language package bibliometrix that can be used by non-coders to create analytics and plots for a collection of publications.
Data Services
The NIH Library's Data Services program provides classes on a variety of topics related to managing, analyzing, and visualizing data. The list below includes Data Services classes in our course catalog. Click the title of the class to view any upcoming sessions.
A Review of Epidemiology Concepts and Statistics
In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering several trainings that cover general concepts behind statistics and epidemiology. These trainings will help participants better understand and prepare data, interpret results and findings, design and prepare studies, and understand the results in published literature.
Advanced Demonstration of Web of Science APIs
This one-hour online training will include live demonstrations of various Application Programming Interfaces (APIs) available for the Web of Science (WoS) platform and specific use cases, including research assessment, policy formation and tracking, and funding evaluation. Technical demonstrations will be performed using Python clients and a WoS API data parser/converter toolkit.
By the end of this training, attendees will be able to:
Applying Findable, Accessible, Interoperable, Reproducible (FAIR) Principles for Reproducible Research
This one-hour online training covers various aspects of sharing code using MATLAB community tools like File Exchange and GitHub. Well-documented methods and workflows enable reproducible research by helping scientists follow each other’s experimental logic and interpret results.
By the end of this training, attendees will be able to:
Coding Macros in SAS
This one-hour online training, provided by a presenter from SAS, will demonstrate how using macros makes a code in SAS easier to read, easier to edit, less prone to errors, and often allows it to run more efficiently. Macros are ways to use code to substitute in a value. Examples of macro code will be made available to attendees for modification and later use.
By the end of this training, attendees will be able to:
Creating Charts in Excel
This one-hour online training will instruct participants on chart creation in Excel.
By the end of this training, attendees will be able to:
Review and select chart types, layout, and style
Change colors and format options
Add titles and labels
Creating Pivot Tables in Excel
This one-hour online training will provide detailed information on how to create and manipulate pivot tables in Excel. Pivot table is an interactive way to quickly summarize large amounts of data.
By the end of this training, attendees will be able to:
Data Management and Sharing: Part 1 of 2
This one-hour and thirty minute online training is part one of an introductory two-part series for those who want to learn about research data management and sharing, or for those who are interested in a refresher. The series provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation.
Data Management and Sharing: Part 2 of 2
This hour and half online training is part two of an introductory two-part series for those who want to learn about research data management and sharing, or for those who are interested in a refresher. The series provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation.
Data Science and Artificial Intelligence: Signals and Time Series Datasets Using MATLAB
This one-hour online training introduces applying data science and artificial intelligence (AI) techniques to signals and time-series datasets using MATLAB. The training will cover the entire AI pipeline, from signal exploration to deployment.
Data Sharing and Discovery in Generalist Repositories: Resources and Real-World Examples
This one-hour online training offers an overview of the NIH-sponsored Generalist Repository Ecosystem Initiative (GREI) (Dataverse, Dryad, Figshare, Mendeley Data, Open Science Framework, Vivli, and Zenodo), and the role of participating in these repositories in the NIH data repository landscape for intramural researchers. The session will highlight how these repositories support compliance with the NIH Data Management and Sharing Policy.
By the end of this training, attendees will be able to:
Data Wrangling in Excel
This one-hour training will equip participants with data wrangling techniques using Excel and will tackle the challenges of messy datasets. Participants will learn how to clean, format, transform, standardize, and organize data in Excel. This class is for beginners: no advanced Excel experience is required but basic familiarity with Excel is expected.
By the end of this training, attendees will be able to:
From Excel to MATLAB: Boost Your Data Analysis
This one hour and half online training discusses how MATLAB enhances data analysis and visualization for technical professionals who typically use Excel. It highlights MATLAB's advantages, such as access to pre-built mathematical and analysis functions, powerful visualization tools, and the capability to automate analysis workflows, addressing the functional limitations often encountered with Excel.
By the end of this training, attendees will be able to:
Getting Started with SAS
This one-hour online training, provided by a presenter from SAS, introduces the basics of accessing SAS 9.4 tools and setting up your environment.
By the end of this training, attendees will be able to:
Load data using SAS Studio or Enterprise Guide
Introduction to Data Wrangling Using Python: Part 1 of 2
This one-hour online training, is the first of a two-part series, which introduces participants to cleaning and exploring a patient health dataset using Python and pandas. Attendees will load tabular data, inspect structure and data types, summarize columns, and identify common data quality problems such as missing values, inconsistent formats, and duplicate records. They will then apply practical fixes, including standardizing height and weight units, parsing and normalizing dates of birth, splitting combined fields, and using Boolean masks to flag or correct implausible values.
Introduction to Data Wrangling Using Python: Part 2 of 2
This one-hour online training, the second session of the two-part series, focuses on reshaping and enriching the cleaned patient dataset to prepare it for analysis and reporting. Attendees will practice splitting and recombining columns (for example, separating full names into first and last names), converting columns to appropriate data types, and engineering new fields such as outlier indicators and blood pressure status labels.
Less Code More Science: Low Code Data Analysis
This hour and a half online training covers how to analyze and model data using interactive tools in MATLAB. Through live demonstrations and examples, attendees will learn to solve many steps in a data analysis workflow without writing any code. The interactive tools can generate the MATLAB code needed to reproduce the work programmatically.
By the end of this training, attendees will be able to:
Managing Data in Excel
This one-hour online training will provide detailed information and demonstrations on how to manage data in Excel.
By the end of this training, attendees will be able to:
Filter data by text, numbers, and date
Sort data alphabetically and by color
Remove duplicates
Modeling of Biological Systems with MATLAB: Introduction to Simbiology and Biopipeline Designer
This one-hour online training introduces attendees to modeling and simulation of biological systems using MATLAB’s SimBiology and BioPipeline Designer toolboxes. SimBiology is a versatile toolbox for modeling, simulating, and analyzing dynamic biological systems such as metabolic pathways, signaling cascades, and pharmacokinetics/pharmacodynamics (PK/PD) models. BioPipeline Designer complements this by streamlining workflows for integrating biological data and automating computational analyses.
NVivo: Making Your Data Come to Life: Part 2 of 2
This one and a half hour online training focuses on the practical use of NVivo by importing data, coding data, and then analyzing and visualizing textual data using NVivo, an analysis and visualization software for qualitative and mixed-methods research, evaluation, and literature reviews.
By the end of this training, attendees will be able to:
Overview of Statistical Concepts
In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering several trainings that cover general concepts behind statistics and epidemiology. These trainings will help participants better understand and prepare data, interpret results and findings, design and prepare studies, and understand the results in published literature.
Overview of Study Design
In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering several trainings that cover general concepts behind statistics and epidemiology. These trainings will help participants better understand and prepare data, interpret results and findings, design and prepare studies, and understand the results in published literature.
Resources for Finding and Sharing Research Data
This one-hour online training provides researchers with an overview of online resources for locating research datasets, data repositories, and data publications for data sharing and re-use. Participants will learn search strategies for locating datasets through federated data search portals and generalist data repositories, including directories for locating discipline-specific and institutional data repositories.
Statistical Considerations in Preparing Your Paper
In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering this two-hour online training to assist researchers in writing a manuscript. Participants will become familiar with statistical issues that can arise as well as recommendations to prevent them. Most of the examples will be related to clinical research; however, anyone can benefit from the tips shared.