Data Carpentry Instructor Onboarding

@datacarpentry http://www.datacarpentry.org

Overview• Overview of Data Carpentry • How it started• Focus of workshops• Target audience• Goals for workshops

• Workshop overview• Workshop structure• Curriculum

• Workshop logistics• Scheduling workshops• Setting up workshops• How to get help with lessons or workshops

Overview of Data Carpentry

With the emergence of new technologies generating large datasets in all domains of research, data management and analysis is no longer the domain of specialists and is instead widely done by all researchers.

Training is the missing piece between data and data-driven discovery

Biggest Bioinformatics Difficulty Most useful thing BRAEMBL could do

Survey by Bioinformatics Resource Australia – EMBL

Researchers view the major limiting factor in research progress as a lack of expertise in how

to handle and analyze data

How it started• Idea to focus on materials for these researchers who had little

computational experience, but now needed to manage and analyze data, came from an NSF BIO Center meeting in 2013 where we identified this shared need for training

• Wanted to use the same hands-on collaborative approach that Software Carpentry was using

• After developing and teaching a few of these workshops in 2014, we saw there was broader interest and after talking with Greg Wilson, Data Carpentry began as a sibling organization to Software Carpentry

Workshop focusWorkshops are focused on data – teaching researchers the foundational skills that will let them effectively manage, organize, analyze and visualize data.

Workshops follow the data lifecycle, starting with ‘so, you just got your data’

Foundational skills:- Project organization- Data organization in spreadsheets- Data cleaning and wrangling- Data analysis in a scripting language- Data visualization in a scripting language

Target audience• Current audience is domain researchers with little to no

computational experience. This is advertised on every workshop website, to manage expectations of the participants.

• This doesn’t mean there won’t be some people there with more experience, but we restate this at the beginning of the workshop to help manage expectations, and encourage those with some experience to help their neighbors

Workshop goals• Primary goal is increased confidence in a learners ability to do

computational work and continue to learn more.• Lower the activation barrier for people to get started working

with data. Often people don’t know where to start.• The skills we teach should be ones they can immediately apply

to their research.• People should learn the things we’re teaching.• We should see a shift in perspective in the value of skills like

scripting for better research and reproducible research.• People should have a positive workshop experience that

empowers them to do better work with data.

Deliver domain-specific hands-on intensive workshops covering the full lifecycle of data-

driven research. Current workshops are designed for people with little to no prior

computational experience.

Workshop Overview

Workshop structure• Workshops are domain-specific, so participants are working

with the type of data they use in their research

• Workshops use one dataset from start to finish to go through the whole process of the data management and analysis

• Workshops follow a narrative structure, again going through the process in the workshop that is what a researcher will go through in their data processing.

• Data sets are teaching datasets of real data and are publicly available for reuse

Workshop Introduction• Because this audience is people newer to computation, setting up a

friendly environment for learning from the start is very important!

• For an overview on introductions, see An Introduction to Introductions

https://github.com/tracykteal/instructors-introduction/tree/gh-pages• Introduce yourself highlighting your experience, but also your

interest and enthusiasm for teaching this group. You want to show that you know what you’re talking about, but also that you’re accessible and approachable.

• Highlight the Code of Conduct http://www.datacarpentry.org/code-of-conduct/ pointing out that it mainly is ‘Be respectful of each other’.

Workshop curriculum• Current domains are ecology, and genomics, and spatial data

under development with NEON

• Lesson templates are slightly different than SWC (we just use Markdown and Rmarkdown and no pandoc), but module and lesson structure is essentially the same

• Because the workshops are a narrative approach, it’s important to use the specified lessons

LessonsEcology:https://github.com/datacarpentry/ecology-workshop

Genomics:(stilll in beta; will be 1.0 in early 2016)

https://github.com/datacarpentry/genomics-workshop

Spatio-temporal lessons (Developed in collaboration with NEON, alpha phase)http://github.com/data-lessons/NEON-R-Spatial-Rasterhttps://github.com/data-lessons/NEON-R-Tabular-Time-Serieshttps://github.com/data-lessons/NEON-R-Spatial-Vector

Lessons• Bringing in Reproducible Research curriculumhttps://github.com/Reproducible-Science-Curriculum/workshop-planning/blob/master/workshopOverview.md

Contributing to lessons is still being done through github, but if you are not familiar with github and want to contribute to lesson development, get it touch and we’ll help. Don’t let the technology be a barrier to participation if you’re interested.

Ecology lessons

Points of interest

• Spreadsheet lessonhttp://www.datacarpentry.org/spreadsheet-ecology-lesson/

• OpenRefine lessonhttp://www.datacarpentry.org/OpenRefine-ecology/

Even if ecology is not your field of study, these are lessons you can teach. They are focusing on using tabular data.

Genomics lessons

Points of interest

• Amazon EC2 or a local HPC is used for these lessons. I need to spin up instances for a workshop, if you’re using EC2

• These lessons go through getting data back from a sequencing center, understanding the FASTQ file type, connecting to remote resources, using the command line and running a bioinformatics pipeline on remote computers, data transfer and data analysis and visualization in R.

Some genomics or bioinformatics background is needed to teach this workshop.

Workshop logistics

Scheduling workshopsHosts request workshops through a request formhttp://www.datacarpentry.org/workshops-host/

Maneesha Sane is our Program Coordinator as well as Software Carpentry’s and she will put out calls for instructors for requested workshops. If you are interested and available to teach, please sign up! We are making efforts to match experienced instructors with newer instructors for each workshop.

As a newer and smaller organization, Data Carpentry does not have the same process for self-organized workshops as Software Carpentry. We’re updating our workshop request form and documentation to reflect this, so better details soon, but if you want to run a self-organized workshop, you need to put in a workshop request form and request a fee waiver. We will grant waivers if self-organized criteria are met.

Setting up a workshop• Workshop templates are like Software Carpentryhttps://github.com/datacarpentry/workshop-templateIf the workshop is not self-organized, you can also ask us to set up the workshop web site.

• Like for Software Carpentry, there will be a lead instructor. That instructor will communicate with the host and other instructors and helpers in preparation for the workshop with the instructor checklists as a guide.

• http://software-carpentry.org/workshops/checklists/lead_instructor.html

• http://software-carpentry.org/workshops/checklists/instructors.html

• For all workshops, we will set up pre and post workshop surveys and send them to you to distribute

• If you need help going through lessons or with workshop questions or logistics, you can contact admin@datacarpentry.org and we’ll make sure the right person gets it.

• For lessons, each module has (or will soon have) topic maintainers. They are people you can ask questions about individual modules.

• The SWC discuss list is a place to ask questions• We also just set up a Slack channel! Request to join.

https://carpentries.slack.com• There are regular debriefing meetings being run by the

Mentoring Subcommittee. Come there before a workshop to ask questions about lessons.

How to Get Help

After a workshop• After a workshop we will:• Ask for the number of participants you had in your workshop• Share the post-workshop survey results with you

• After a workshop you can:• Attend a Mentoring Subcommittee debriefing meeting• Let us know if you had any suggestions for the workshop,

whether that’s materials, organization or structure or anything else

• Contribute back changes you made to the lessons. If you made changes that you thought improved the lessons, please put in a Pull Request or talk to us about those changes. It’s the only way the lessons get better!

Guiding Data Carpentry

Data Carpentry Steering Committee:Karen Cranston (NESCent / OpenTree of Life)Hilmar Lapp (NESCent / Duke)Aleksandra Pawlik (Software Sustainability Institute)Karthik Ram (rOpenSci / Berkeley Institute of Data Science Fellow)Ethan White (University of Florida / Moore DDD Investigator)Greg Wilson (Software Carpentry)

Hiring an Associate Directorhttp://www.datacarpentry.org/blog/associate-director-posting/

Data Carpentry support

Questions?