Reproducible Quantitative Methods

Lesson 3

Introduction to Metadata / Data and scientific authorship

yeah bar

Topics and Resources

  1. Introduction to metadata

    So what exactly is metadata? What does metadata need to include? Review the following resources:

      • Metadata Guide from Australian National Data Service (a simple working-level view of the needs, issues, processes around metadata collection and creation; not discipline specific)

      • Best Practices for Data Management from DataONE: Section 5.4 (p.5)

      • See also: Metadata Directory from Research Data Alliance - which provides a list of metadata standards used in various disciplines.

    The goals for this lesson are to help you understand the benefits of open data, how to encourage others to make their data open, and to identify what you can do with your own data to make it possible for someone to build on your work.

    This is a good time to read Nine simple ways to make it easier to (re)use your data

  2. Data creation and authorship

    What defines scientific authorship, and how do data creators fit in? Conventions vary between fields, but in general, authorship may be defined by contribution to following areas:

      • Concept framework and question

      • Funding

      • Research design

      • Data collection

      • Analysis

      • Writing and manuscript preparation

      • Editing

      • Manuscript submission and revision handling

    A great overview of authorship (with a focus on ecology) in plain language: Determining authorship for a peer-reviewed scientific publication by Chris Buddle. And there's lots of outher resources- Here's a 2010 Science Magazine article on authorship conventions across disciplines, and a blog post from Hutton Institute on authorship conventions in an inderdiciplinary organization. There's also some social issues around scientific authorship, for example, see this article on gender disparities in authorship across diciplines.

Exercises

  1. DATA-README
  2. Write a DATA-README for project data set.

  3. Authorship exercise
  4. It's always a good idea to set authorship expectations early in the game- it helps contributors understand their respective roles. Discuss with your group- who needs to be on the author list beyond the group members? If people outside the group are to be included, how will they know what their respective roles are? Author order can be determined at a later date, but begin thinking about this as well!

  5. Reading
  6. To prep for next week’s activities, please skim through The Quartz guide to bad data.

Discussion

Authorship in Science

Please read Chris Buddle's article from above, for class on Thursday- this article is highly relevant to ecology authorhip conventions. You can also skim Defining the Role of Authors and Contributors from the International Committee of Medical Journal Editors gives a more technical, medically-relevant guide to authorship, but conventions vary between fields.


ProTip


A helpful hint from those that came before

Consult the experts If you consider your home field somewhere outside of ecology, consult with your librarian to find information on authorship conventions relevant to your field. How do practices differ? What do they have in common?

Video

Data Management SNAFU in 3 Short Acts (4:40)

Questions

What are the authorship conventions in your field? Since our class is multi-disciplinary, discuss differences in conventions among varied fields.

What makes someone an author on a paper? What kinds of contributions might a researcher make?

What if the research product is something else: code, data set, how is authorship different?

How does first use of a data set, and then use of data after previous publication differ for your field’s authorship rules? (This can vary, and isn't easy to answer.)

When does a data and/or code creator qualify to be an author?

What challenges are often present when working with data created by others?

Previous Lesson | Home | Next Lesson