Do you want to learn more about scientific database management? Have ideas about how to store and analyze both computational and experimental results? Now is the time to set up your teams and get ready to crunch!
The Acceleration Consortium (AC) and the Society for Laboratory Automation and Screening (SLAS) are excited to co-host a FREE, virtual hackathon on October 22 – October 24, 2021.
The integration of machine learning and artificial intelligence (AI) into scientific research is transforming scientific inquiry. Such advances require well-designed databases suitable for scientists to store and analyze computational and experimental results from multiple experiments and users.
Teams (3-4 people) will work with a database management framework and choose their own datasets to prototype, build, and/or enhance tools to address the challenges that researchers face today. We welcome datasets and applications in all fields.
After registration, you will gain access to the AC Discord server with further information, including a forum for questions and discussions. All hackathon activities will take place virtually.
You are responsible for assembling a team of up to four (4) people, who you want to spend the weekend with (virtually or physically—your choice—but please respect COVID protocols wherever you are). Teams must have 3 or 4 people. If you want to join but don’t have a full team, you can sign up with 1-2 people and we’ll match you with others looking to complete their team!
We are limiting this first event to a maximum of 10 teams.
Registration closes Thursday, October 7, 2021. If registration is full or you’ve missed the deadline, please feel free to sign up for the waitlist.
You can also participate as a mentor or judge (scroll down to learn more)!
What do I need?
A computer with a solid internet connection
Familiarity with SQL
Comfort with learning new python APIs
You can participate from anywhere in the world, but please note that the event (and all event deadlines) will be based in the EST time zone:
Thursday, October 7: Registration closes.
Monday, October 11: Database tutorials released. You are not expected to begin your project right away, these recorded tutorials will provide a preview of what to anticipate.
Friday, October 22 – Sunday, October 24: Start hacking!
Sunday, October 24: Winners announced.
What's in it for the winners?
Cash prizes (split evenly among team members)!
1st place: $2,000
2nd place: $1,250
3rd place: $750
Plus, a podcast interview, bragging rights, and more…
What about everyone else?
All participants will receive Hackathon swag compliments of SLAS and the Acceleration Consortium. (If we told you everything, it wouldn't be as fun, now would it?) We will ask for your shipping address to mail it to you. If you're not interested, feel free to omit that information when you register.
Email us at firstname.lastname@example.org
Hackathon mentors and judges
Mentors are welcome from any and all time zones. There will be opportunities to participate both synchronously and asynchronously.
We are looking for mentors with:
Programming experience who can help with questions about python and the API
A scientific background who can provide insight into using a database for scientific data
Data science expertise who can advise on data analytics
… and more! If you have any kind of interest in the event, write to us and we will find a spot for you!
You are expected to:
Give advice on how to approach certain problems and search for solution
Point teams towards helpful resources
Provide feedback on teams’ brainstorming sessions and problem statement submission
You are not expected to:
Be an expert with the database
Be available 24/7
Do the project for the teams
Solely focus on one team
We also welcome mentors and/or volunteers to speak about the broad hackathon topic in a live Twitch broadcast. The broadcast will be saved and published later online.
Your thoughts and experiences using a scientific database for computational and/or experimental data
Alternative database frameworks that you have used
What the ideal database might look like
How you might approach the problem statement from your perspective
For the daring—live coding using the database framework
Teams may be highly independent, so these are just estimates. You are, of course, welcome to participate and spend as much time as you like beyond the minimum estimate.
Total time: 12 hours
~2 hours before the event, to familiarize yourself with the database framework and API that will be provided to teams.
2 hours during the evening of Friday, October 22 (advising on project descriptions).
8 hours of being “on call” answering questions and talking to teams in the Discord channel, Saturday, October 23–Sunday, October 24.
If the description above sounds interesting, please write to email@example.com with “Hackathon Mentor” in the subject line, and include a brief description of your background.
Judges will evaluate:
Each team’s problem statements, submitted Saturday at 11:00 am EST.
Each team’s final projects, submitted to Github.
With a maximum of 10 projects, we hope to keep time commitment low:
Total time: 5 hours
0.5 hours before Saturday, October 23 to familiarize yourself with the problem statement and judging guidelines
2 hours on Saturday, October 23 to discuss team project descriptions
2.5 hours for the evaluation of projects and deliberation of project submissions
We strongly welcome judges who would like to provide public remarks on the projects and subject at large.
Judges may also serve as mentors but may only answer questions asked in a public channel.
If you’d like to volunteer as a judge, please write to firstname.lastname@example.org with “Hackathon Judge” in the subject line, and a brief description of your background (links to websites / group pages are acceptable).
About the hackathon co-hosts
Based at the University of Toronto, the Acceleration Consortium is a global community of academia, government, industry and entrepreneurs dedicated to accelerating the discovery of new materials and molecules.
SLAS is an international professional society of academic, industry and government life sciences researchers coupled with the developers and providers of laboratory automation technology. SLAS advances scientific innovation by providing education, collaboration and professional development that unites scientists across disciplines and transforms research.