ScHARe Think-a-Thons

ScHARe Think-a-Thon graphic: hands of different skin colors form the shape of a light bulb as a metaphor for collaboration

The monthly ScHARe Think-a-Thons scheduled or archived below are designed so participants reach one of these goals (as noted with each session):

Goal 1: Achieve a better understanding of both the fields and the terminology used to describe the AI/cloud computing infrastructure, components and processes.
Goal 2: Develop research questions and projects relevant to AI and cloud computing that leverage the cutting-edge technology and data/computing resources now available to health disparities researchers (including the ones at their disposal on the ScHARe platform).

Upcoming Think-a-Thons

Past Think-a-Thons

See FAQs

Think-a-Thon Schedule

Think-a-Thons are held on the third Wednesday of each month. Accommodations information | Think-a-Thon recordings

Date	Time	Topic	Register
Nov. 20, 2024	2:00 - 4:30 p.m. ET	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)	Register

Date

Time

Topic

Nov. 20, 2024

2:00 - 4:30 p.m. ET

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)

Individuals who need reasonable accommodation to participate should contact the ScHARe team at least five business days before the event.

Past Think-a-Thons

Date	Duration	Topic (linked if video available)	Materials
October 16, 2024	2.5 hours	Video coming: ScHARe Data Repository Toward Goal 1: 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)	Coming
September 18, 2024	2.5 hours	Video coming: 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	Coming
August 21, 2024	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.	Coming
July 17, 2024	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)	View slides -or- Part 1 Part 2 Part 3
May 15, 2024	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	View slides -or- Part 1 Part 2
April 17, 2024	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	View slides
March 20, 2024	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	View slides -or- Part 1 Part 2 Part 3 Part 4 Part 5 Part 6
February 21, 2024	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	View slides
January 17, 2024	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	View slides -or- Part 1 Part 2 Part 3 Part 4 Part 5 Part 6 Part 7
November 15, 2023	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	View slides
October 18, 2023	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	View slides
September 20, 2023	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)	View slides
August 16, 2023	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	View slides
July 19, 2023	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	View slides
June 21, 2023	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	View slides
May 17, 2023	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	View slides
April 19, 2023	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	View slides
March 15, 2023	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	View slides
February 15, 2023	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	View slides

FAQs

Who can participate in a Think-a-Thon?

Think-a-Thons are open to researchers and students from high school through graduate studies. We encourage experts in health disparities, health outcomes, data science, bias mitigation, and AI ethics to participate and share their knowledge through these sessions.

Why Think-a-Thons?

Collaborative data analysis can provide health disparities and health outcomes researchers access to powerful research tools. It can also help AI bias researchers ensure that these tools are used responsibly.

Think-a-Thons are designed to create opportunities for these forms of collaboration. They help researchers collaboratively improve their understanding of AI and cloud computing, develop team-based publishable research projects, address bias mitigation strategies, and learn to take advantage of the ScHARe platform. The ScHARe platform houses numerous datasets for social science, social determinants of health, health outcomes, and health disparities, as well as secure workspaces and computational tools. A key goal of the ScHARe platform is to reduce cost and knowledge barriers related to the use of AI and cloud computing for underrepresented groups and populations that have been economically or socially marginalized, and to advance research on health disparities, health outcomes, and AI bias mitigation.

Can I choose which Think-a-Thons to attend or are some prerequisites for others?

Participants can choose which Think-a-Thons to attend based on their knowledge and interests. There are no attendance prerequisites. Some Think-a-Thons will teach participants to use the ScHARe platform and others will help participants launch collaborative research teams.

Where will the Think-a-Thons be held?

Think-a-Thons are held virtually on Zoom.

See the ScHARe Think-a-Thon schedule for details and to register.

How do Think-a-Thons work?

Think-a-Thons are two-to-three-hour virtual meetings that enable participants to achieve two key goals:

Learn to use the ScHARe Cloud, including its computational tools, datasets, and the Terra platform
Form cross-disciplinary, multi-level research collaborations that will lead to publications on health disparities, health outcomes, and/or AI bias mitigation

The teams formed during research collaboration Think-a-Thons will continue their collaborative efforts beyond their initial meeting, as they complete their research project and develop and submit a publication.

What materials will I need to participate in a Think-a-Thon?

Think-a-Thon organizers will provide participants with the following material before each session, if applicable:

An agenda
Useful background material, reports, and a relevant glossary of key terms or information

What are AI tools?

Artificial intelligence (AI) uses machines intentionally designed by humans to perceive, synthesize, infer, and identify patterns in big data to help make rapid decisions or anticipate problems. AI combines information from a variety of different sources, including sensors, digital data, or remote inputs, and acts on the insights derived from those data, often in real time. Some commonly used AI tools include R packages and Python libraries for structured and unstructured data.

What is cloud computing?

Cloud computing involves using a secure network of remote servers hosted on the internet to store, manage, and process amounts of data too large for personal computers while still enabling these data to be utilized in confidential personal workspaces.

What are the advantages of cloud computing?

Cloud computing can provide:

Cost savings by eliminating the need to pay for data storage space or features that researchers do not need.
Real-time data management and collaboration on a centralized platform.
Enhanced data security and data loss prevention through secure cloud-based storage and data encryption.

Why do minority health and health disparities researchers face barriers to using AI and cloud computing tools?

Common barriers to the use of AI and cloud computing tools include a lack of opportunities for training and collaboration with relevant experts, as well as potentially prohibitive costs.

Think-a-Thons lower these barriers by facilitating the use of AI and cloud computing tools on the ScHARe platform. The ScHARe platform contains easily accessible, open-source tools for data analysis. The Think-a-Thon collaborative framework promotes learning and the formation of multi-disciplinary research teams which combine data science experts with health experts.

What specific topics will the Think-a-Thons cover?

Please see the ScHARe Think-a-Thon schedule to view upcoming topics.

Page updated Nov. 7, 2024 | created Jan. 18, 2023

Get Involved

Access Platform

Learn More

Stay Updated

ScHARe Think-a-Thons

Think-a-Thon Schedule

Past Think-a-Thons

FAQs

Who can participate in a Think-a-Thon?

Why Think-a-Thons?

Can I choose which Think-a-Thons to attend or are some prerequisites for others?

Where will the Think-a-Thons be held?

How do Think-a-Thons work?

What materials will I need to participate in a Think-a-Thon?

What are AI tools?

What is cloud computing?

What are the advantages of cloud computing?

Why do minority health and health disparities researchers face barriers to using AI and cloud computing tools?

What specific topics will the Think-a-Thons cover?

ScHARe Think-a-Thons

Think-a-Thon Schedule

Past Think-a-Thons

FAQs

Staying Connected