ScHARe Think-a-Thons

2:00 – 4:30 p.m. ET

A Conceptual Model for using AI to Advance Ethical Health Research
Toward Goal 1:

This webinar provides a framework for fair and ethical AI by covering:

• AI development pipeline and bias mitigation strategies
• How to assess data quality and consistency
• Tips and tools for developing fair and ethical AI

2:00 – 4:30 p.m. ET

Health Outcome Research Paradigm Shift: Understanding How Big Data Expands Knowledge

2:00 – 4:30 p.m. ET

Data Preparation for Creating an AI-ready Quality Data

2:00 – 4:30 p.m. ET

Data Exploration to Initiate a Model Development

2:00 – 4:30 p.m. ET

An Introduction to Python for Data Science

2.5 hours

Video coming: ScHARe Data Repository
Toward Goal 1:

We'll continue to review how to use the ScHARe Data Repository to host, manage, and share data with different privacy settings. Topics include:

• How to upload data
• How to create data tables and collections
• How to map data to ScHARe/PhenX Core Common Data Elements (CCDEs)

2.5 hours

View video: ScHARe Generalized Data Ecosystem Repository
Toward Goal 1:

This session introduces basic principles of data cleaning and data management in the Python programming language. Designed for beginners, the session covers essential but simple skills that are essential for data science, such as how to:

• Upload data
• Create data tables and collections
• Map data to ScHARe/PhenX Core Common Data Elements (CCDEs)

2.5 hours

View video: Data Management and Analysis in Python
Toward Goal 1:

This session introduces basic principles of data cleaning and data management in the Python programming language. Designed for beginners, the session covers essential but simple skills that are essential for data science, such as how to:

• Clean data (detect and handle missing values)
• Combine and view two datasets
• Develop and test an algorithm

2.5 hours

View video: An Introduction to Python for Data Science
Toward Goal 1:

This session introduces the Python programming language, its application in Data Science on ScHARe, and free Python resources. Designed for beginners, this session addresses jargon, general concepts and high-level functions, serving as a preparatory step before diving into a full Python course.

2.5 hours

View video: Be a Part of the Future of Knowledge Generation: AI-Ready Datasets and Computational Strategies
Toward Goal 1:

Second in a series that equips data scientists, health researchers, and students to participate in future ScHARe research:

• How to prepare an AI-ready dataset using gold standard data management principles
• Choosing computational strategies (AI, Machine Learning, statistics)

2.5 hours

View video: Be a Part of the Future of Knowledge Generation: AI/Cloud Computing Basics and Common Data Elements
Toward Goal 1:

First in a series that equips data scientists, health researchers, and students to participate in future ScHARe research:

• ScHARe mission and vision
• Fundamentals of artificial intelligence and cloud computing concepts behind ScHARe
• How to prepare for a ScHARe research endeavor
• The role of Common Data Elements in preparing and combining datasets

2.5 hours

Data Science Projects 1: Accelerating Health Disparities and Health Outcomes Research
Toward Goal 2:

Hands-on research collaboration session:

• Form multidisciplinary, multi-career-stage research teams
• Design a study that uses ScHARe’s big data and cloud computing resources
• Commit to learning and practicing transparent approaches for ethical AI

2.5 hours

View video: Preparing for AI-driven Research on ScHARe: A Comprehensive Review and Brainstorming Session – Part 2
Toward Goal 2:

Prepares participants for ScHARe research collaborations by covering:

• Choosing computational strategies (AI, ML, statistics)
• An overview of Python data science libraries
• The significance of testing and monitoring in algorithm development
• The role of open science in ensuring reproducible and transparent AI-based research

For researchers and students at all levels who want to collaborate on ScHARe to develop innovative and publishable research projects

2.5 hours

View video: Preparing for AI-driven Research on ScHARe: A Comprehensive Review and Brainstorming Session – Part 1
Toward Goal 2:

Prepares participants for ScHARe research collaborations by covering:

• Understanding the pivotal role of CDE for mapping and combining datasets
• Preparing an AI-ready dataset using gold standard data management principles
• Choosing data science computational strategies
• Identifying topics for AI-driven research and relevant datasets available on ScHARe

For researchers and students at all levels who want to collaborate on ScHARe to develop innovative and publishable research projects

2.5 hours

View video: Preparing for AI-Driven Research 3: Computational Data Science Strategies – Getting Ready for a Data Science 101 Course
Toward Goal 1:

How to choose computational tools and techniques in data science, including:

• Demystifying the process of aligning computational strategies with specific data analysis goals
• Fundamental differences between artificial intelligence (AI), machine learning (ML), and traditional statistics, and use cases where each method is most helpful
• Free infographics, templates, and decision trees

• Part 1
• Part 2
• Part 3
• Part 4
• Part 5
• Part 6
• Part 7

2.5 hours

View video: Preparing for AI 2: An Introduction to FAIR Data and AI-ready Datasets
Toward Goal 1:

How to prepare an AI-ready dataset using gold standard data management principles, including:

• Making datasets findable, accessible, interoperable, and reusable (FAIR)
• Using transparent data documentation to foster data re-use
• Ensuring that selected data addresses expected outcomes and drives meaningful AI insights
• Handling missing data through strategies, proxies, and synthetic data

2.5 hours

View video: Preparing for AI 1: Common Data Elements and Data Aggregation
Toward Goal 1:

How to use common data elements (CDEs) to enable big data-enriched research:

• Pivotal role of CDEs in the context of mapping and combining datasets (data aggregation)
• How CDEs standardize and harmonize data across diverse datasets and studies, enabling research breakthroughs and innovations

2 hours

View video: ScHARe 5: A Review of the ScHARe Platform and Data Ecosystem
Toward Goal 1:

• Create and configure an account and workspace and set the appropriate permissions
• Create and run a notebook
• Set up billing
• Add data to a workspace
• Access, visualize, and analyze data from Google-hosted federated/national datasets (e.g., the American Community Survey) and ScHARe-hosted public datasets (e.g., the Behavioral Risk Factor Surveillance System)

2 hours

View video: An Introduction to Python for Data Science – Part 2
Toward Goal 2:

• Continue hands-on introduction to the Python programming language and its use in data science applications on ScHARe
• Review free Python related tutorials and resources available online
• How to create and configure a Terra billing account and add ScHARe hosted data to a Terra workspace

2 hours

View video: An Introduction to Python for Data Science – Part 1
Toward Goal 1:

• Hands-on introduction to the Python programming language and its use in data science applications on ScHARe
• Review the free Python related tutorials and resources available online

2 hours

View video: ScHARe 4 – Terra ScHARe-hosted Datasets
Toward Goal 1:

• Conclude exploration of the ScHARe Data Ecosystem, focusing on ScHARe-hosted federated/national datasets (e.g.: BRFSS - Behavioral Risk Factor Surveillance System)
• How to access, import, visualize, and analyze data and save results
• How to use workflows to simplify your work

2 hours

View video: ScHARe 3 – Terra Google-hosted Datasets
Toward Goal 1:

• Continued exploration of the ScHARe Data Ecosystem, focusing on Google-hosted federated/national datasets (e.g.: ACS – American Community Survey)
• How to access, import, visualize, analyze data and save results
• How to create and configure a Terra billing account

2 hours

View video: ScHARe 2 – Terra Datasets
Toward Goal 1:

• Introduction to the ScHARe Data Ecosystem
• How to add data to a Terra workspace and how to access, visualize, and analyze the data and save results

2 hours

View video: ScHARe 1 – Accounts and Workspaces
Toward Goal 1:

• An inside look at ScHARe’s Terra instance: general introduction and features
• How to create and configure an account
• How to create a workspace and set the appropriate permissions
• How to clone or create and run a notebook

2 hours

View video: Artificial Intelligence and Cloud Computing 101
Toward Goal 1:

• Introduction to the artificial intelligence and cloud computing concepts behind the ScHARe platform
• Fundamental terminology
• Cloud architecture, services and providers
• Data structures and management
• Technology benefits and concerns in the research collaboration world
• NIH initiatives and strategies for low-cost cloud development
• Inclusion of cloud computing costs into grant applications
• ScHARe mission and vision