• Best Use of Data: The Non-Wheel Inventors team developed an application to ingest and analyze NASA's lessons learned databases using NLP. Team members: Haroon Khan, Marc Shaw-Lecerf, Sumedha Garud, Cristal Gomez, Nirali, Patel, and Gerardo Cruz-Ortiz.
• Best Use of Technology: The Community Backlog of Inner-Source Code team created a platform for NAS staff to share and vote on ideas for reusable, inner-source code (a.k.a., software developed by and shared within NASA). Team members: Taylor Yates and Justin Gosses.
• Most Creative/Innovative: The Intra-Agency and Public Work Sharing System team produced a design and mock-up for a "LinkedIn"-style website to host employee professional pages that are semi-automatically populated with data from Agency systems. Team members: Leor Bleier, Felecia Berry, Balir Allen, and Brodan Richter.
• Most Potential NASA Impact: The Generating a Change Current team developed a vision, graphic, and 5 key efforts (playgrounds, journalists, champions, embedded experts, leaders and teams) to accelerate NASA’s DT culture shift. Team members: Rebecca Levy, Yonghong Shen, Jason Kinney, Erin Misegades, Channon Wong, and Victoria Danna.

The DT hackathon will empower diverse DT champions across NASA and create an inviting forum to experience, learn, and grow the culture that supports digital effectiveness. The hackathon builds NASA’s culture of innovation and diligence by creating short-term experiences of interdisciplinary teams that merge diverse skills and perspectives, produce innovative tools, invent new collaborative practices, spark ingenuity, solve tough challenges, and accelerate innovation.

Teams will be invited to work on diverse challenges in these focus areas:

• Data - facilitate data-enabled insights and decisions through efficient, real-time, and appropriate data sharing, integration, and secure access.
• Collaboration - pursue frictionless, agile, fully-integrated, secure internal and external collaboration, including partnerships, to enable our missions and workforce.
• Model-based work - model any system or process, from engineering to safety to finance, by creating a structured, executable digital description of the system.
• Process transformation - improve mission support efficiency and effectiveness through end-user focused process re-engineering, duplicate steps removal, process automation.
• Artificial intelligence/machine learning (AI/ML) - accelerate all NASA missions and business functions through infusion of powerful AI/ML techniques.
• Culture and workforce - promote a workforce and workforce culture with the essential traits of a digital workforce: adaptable, driven, innovative, connected, and open.

Challenges for the 2020 DT Hackathon

Science Discovery Engine

• Develop an intelligent literature search and analysis application that reads NASA-relevant scientific articles using natural language processing and text mining, returns knowledge analysis and relevant scientific findings, and reveals knowledge gaps and multi-disciplinary research opportunities.

Natural Language Processing for Requirements Checking

• Create a Natural Language Processing System to parse documents looking for conflicts, duplicates, gaps and other errors in NASA project requirements.

Designing the Culture Shift of Digital Transformation

• Design a road map and plan for how to accomplish NASA’s Digital Transformation culture shift, by involving our workforce to understand, describe, and shape the culture we have, the culture we aim to continue building, and our planned path.

Programmer Collaboration Portal

• Improve the ability of NASA staff to collaborate around software development, enabling developers to: find NASA platforms, tools, policies, and services related to writing code; suggest and vote on inner-source code projects; discover parties writing or interested in writing similar code; and share/discover reusable code.

Data Literacy Training for All

• This challenge will design a set of data science curriculums and associated learning tools for scientists, engineers, and managers.

Model NASA’s Governance

• Model elements of NASA's governance: Understand how to organize and supply governance data (e.g., board charters, policies) and to model NASA governance processes (e.g., reviews, decision making), interface/integrate those models, maximize model commonality, and surface governance issues and best practices.

Model-Based Organization Structure

• Design a conceptual model that shows how organizational structures in NASA currently operate and change.

Semi-Automated Technical Work Sharing

• NASA needs the ability to share the technical contributions and technical work information of staff, to promote internal collaboration, build on each other’s work, incentivize publication, and give due credit for original technical work.

Modeling NASA’s Mission Support

• How can a virtual model of a mission support function be effectively used to improve NASA’s enterprise business operations?

Mining NASA’s Lessons Learned

• Design an application utilizing advanced digital technologies and analytical methods to gain new insight from old data, specifically from NASA lessons learned databases that contains a wealth of information on past projects and missions.

Find a challenge that interests you, start or join a team, and spend a day discovering what’s possible when NASA advances digital transformation.