"Machine learning people use hugely complex algorithms on trivially simple datasets. Biology does trivially simple algorithms on hugely complex datasets."
Concepts of reproducible science
Note: it may hinder science if it does not come with reusability because it pushes people to do all the same things
Reusability: allows you to do things that the original creator did not have in mind
Education: replication by running code but unreadable code (probably going in the
The 2 last are more valuable for science, but require more work
We cannot achieve reusability and high quality for everything
=> solution creating a curated, tractable experiment: data + pb
What do we want from the way science moves forward (many incremental ideas in a conference)?
- Curated (maintained libraries)
- Versioning of code and tags
- Docker... but that's replication, not reuse
- Changing incentives