What's in it for me? What's in it for me? Transparently organizing - - PowerPoint PPT Presentation

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What's in it for me? What's in it for me? Transparently organizing - - PowerPoint PPT Presentation

What's in it for me? What's in it for me? Transparently organizing your research from start to fi nish Candice C. Morey MRC-CBU Open Science Day Adopting open research practices Scientists endorse openness, but most don't prioritize it


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What's in it for me? What's in it for me?

Transparently organizing your research from start to finish

Candice C. Morey MRC-CBU Open Science Day

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Adopting open research practices

Scientists endorse openness, but most don't prioritize it Perceived to be a lot of work Rewards fuzzy: · · · Idealistic only? Maybe important later, but not vital now?

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Strategic concerns

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Strategic concerns

Won't it slow me down? ·

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Strategic concerns

Why should someone else benefit from my work? ·

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Strategic concerns

What if I fail? ·

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Science is a collaborative effort

You are working together to achieve something bigger.

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Why PIs need in-lab transparency

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Why PIs need in-lab transparency

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Why PIs need in-lab transparency

Each student thinks their project is theirs, but it is always part of something bigger.

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Why PIs need in-lab transparency

To ensure consistency in training researchers To know the provenance and protect the security of data To stem information loss that comes with turn-over To make it easy to share publicly when its time · · · ·

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Components of my open-lab workflow

Lab handbook Open Science Framework Scripted analysis Pre-registration · · · ·

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  • 1. My lab handbook

https://ccmorey.github.io/labHandbook/

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Why have a lab handbook?

End theory-of-mind games when training new students Articulate a standard to aspire to · · So students know what I would consider "professional" (i.e., worthy of high marks)

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Why make it public?

To get feedback To be helpful So you might influence standards Enrich descriptions of your published method · · · ·

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  • 2. The Open Science Framework

OSF: A tool you can use to organize, back-up, and eventually share finished components Sharing your finished products != working totally in public · · Custom software, stimuli, protocols: they're finished when study is ready to be run Pre-registrations: Before analyzing new data Anonymized data: when the data set is closed to new members, entries Analysis code and papers that are ready for scrutiny from someone

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Nice features of OSF

It's free Control project members, visibility Can get DOI assigned to project Good tool for supervision - can see quickly where project stands · · · ·

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How I use it

Students are introduced to OSF at start They are added to an existing project or create their own Finished products (materials, data, writing) are uploaded They "register" project at important milestones The OSF page supplements whatever we publish · · · · Creates a back-up Provides a timestamp in case we need it

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  • 3. Scripted Analyses

Not part of my training! Workflow I learned in my training was not easy to reproduce · ·

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Principles of scripting

Processing data shouldn't lead to information loss Script starts from anonymized raw data Everything done to the data is recorded in the script · · Every time

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Is documented, can be changed efficiently

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Advantages of scripting

Once you have a routine, it is much faster Changes can be made quickly and easily You have a record of every step performed The analysis is reproducible Your colleagues (inside and outside the lab) can see exactly what was done · · · · ·

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  • 4. Pre-registration

Documenting detail of method and analysis plan before analyzing (or collecting) data ·

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Why it is helpful

Prevents rushing into data collection Better ensures that students collecting data understand what they are doing (and can provide useful criticism ahead of time) Makes it clear to students how to proceed with data analysis Prevents p-hacking · · · ·

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Does pre-registration slow projects down?

Probably. But also Inculcates a lab culture where it is clear that speaking up about design is welcome · · prevents wasting time running sub-optimal designs helps catch confounds improves pedagogy

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Why these things specfically?

Adopted them because I saw they would solve specific problems I experience directing a lab run largely on short-term student labor Didn't adopt them wholesale, immediately · Uncertainty about what students had done in the lab Or with the data Wanting to make better use of their efforts

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Was always gradual, picked something I could manage, built on it later

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Openness in the lab makes openness outside it easier

When you are confident about Less anxiety about sharing outwards Sharing publicly has been beneficial · the provenance of the data the reproducibility of the analyses the quality of the design

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· Increases citations Reputation benefits Goodwill from others who appreciate your resources

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Transparency is for your team

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Transparency is also for Science

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Transparency is also for Science

But it's mostly for you.

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Thanks for your attention!

My data and materials are publicly available on Open Science Framework (https://osf.io/4xwa8) Blogging at The Mnemonic Lode, candicemorey.org Twitter: @CandiceMorey Editor-in-chief, www.journalofcognition.org

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