data refuge paths
These are the paths we used at Data Rescue Philly. There are many paths to data refuge
Guides will take you on these Paths: choose one according to your interests and skills. A fuller description of the workflow is available at https://datarefuge.github.io/workflow/
Seeding & Sorting Path (to feed the End of Term Archive): This is the widest path and requires a variety of skill levels. Consider this path if you are a coder, hacker, have front end web experience, or just have a great attention to details.
- DataRefuge Path:the various interwoven paths to get "uncrawlable" data into DataRefuge
Researchers (to review URLs the Seeders & Sorters mark as Uncrawlable): Consider this path if you have a strong front end web experience and like to find out more information about thing.
Harvesters (to figure out how to capture the uncrawlable data): Consider this path if you're a hacker
Checkers (to inspect a harvested dataset and make sure that it is complete): The main question the checkers need to answer is "will the bag make sense to a scientist"? Checkers need to have an in-depth understanding of harvesting goals and potential content variations for datasets.
Baggers (to do a quality assurance check and package the data): Consider this path if you have data or web archiving experience, or have strong tech skills AND attention to detail.
Describers (includes a few people from the Baggers path): Consider this path if you have experience working with scientificdata (particularly climate or environmental data) or with creating metadata. Trained librarians and scientists will be very helpful on this path.
Documentation & Storytelling: Consider this path if you’re on social media (Facebook, Instagram, Twitter, whatever), if you can use Storify, if you have good listening and writing skills, and/or if you can make creative and engaging materials.
The Long Trail: Consider this path if you’d like to build DataRefuge into the future. Future projects will also call attention to all the data that exists but can't be captured in a single weekend as well as data that doesn't exist, but should. Many kinds of skills needs. Experience in public engagement projects and informal STEAM education settings will be especially helpful.