diff --git a/episodes/02-data_management.md b/episodes/02-data_management.md index d9e85000..0302067b 100644 --- a/episodes/02-data_management.md +++ b/episodes/02-data_management.md @@ -143,7 +143,7 @@ Which file formats do you store your data in? Enter your answers in the collabor filename itself, while keeping the filename regular enough for easy pattern matching. For example, a filename like `2016-05-alaska-b.csv` makes it easy for both people and programs to -select by year or by location. Common file naming conventions are discussed in the [Turing Way](https://the-turing-way.netlify.app/reproducible-research/rdm/rdm-storage.html) and in the [Project Organization](https://carpentries-incubator.github.io/good-enough-practices/05-project_organization) episode of this lesson. +select by year or by location. Common file naming conventions are discussed in the [Turing Way](https://the-turing-way.netlify.app/reproducible-research/rdm/rdm-storage.html) and in the [Project Organization](05-project_organization.md) episode of this lesson. *Variable names*: Replace inscrutable variable names and artificial data codes with self-explaining alternatives, e.g., rename variables @@ -276,7 +276,7 @@ Which of the following places would be good places to share your data? :::::::::::::::::::::::::::::::::::::::::::::::::: Your data is as much a product of your research as the papers you write, and just as likely to be useful to others (if not more so). -Sites such as [Dryad](https://datadryad.org) and [Zenodo](https://zenodo.org) allow others to find your work, use it, and cite it; we discuss licensing in the episode on collaboration [04-collaboration]. +Sites such as [Dryad](https://datadryad.org) and [Zenodo](https://zenodo.org) allow others to find your work, use it, and cite it; we discuss licensing in the episode on [collaboration](04-collaboration.md). Follow your research community's standards for how to provide metadata. Note that there are two types of metadata: metadata about the dataset as a whole and metadata about the content within the dataset. If the audience is humans, write the metadata (the README file) for humans.