Introduction to Library Carpentry

Overview

Teaching: 30 min
Exercises: 0 min
Questions
  • How can The Carpentries & Library Carpentry help libraries meet the data and software needs of their communities and staff?

Objectives
  • Learn about campus trends in data science.

  • Understand data science challenges and opportunties for libraries.

  • Learn how The Carpentries & Library Carpentry works.

  • See what libraries are doing with The Carpentries & Library Carpentry.

  • Understand how you can get involved and about training at your institution.

Introduction to Library Carpentry – Teaching Data Science Skills

Who you are?

Start with your background, role at your institution, and what role (or desired role) you have in the Library Carpentry/Carpentries community.

Our aim is to help libraries become data and software savvy.

Outline

With the emergence of our ability to generate increasing amounts of data, research and work in almost every domain has a data and computational component, including the whole new field of data science.

Libraries are guided by the needs of their communities…

Unmet needs

According to Barone L, Williams J and Micklos D. Unmet Needs for Analyzing Biological Big Data: A Survey of 704 NSF Principal Investigators (2017):

Fig 3. Unmet data analysis needs of National Science Foundation (NSF) Biological Sciences Directorate (BIO) principal investigators (PIs) (percent responding negatively, 318 ≤ n ≤ 510).

In a survey of biology NSF PIs, the top 3 unmet needs are around training

Importance of research software & training

S.J. Hettrick et al, UK Research Software Survey 2014 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.14809

Educational Pathways

Academic institutions should provide and evolve a range of educational pathways to prepare students for an array of data science roles in the workplace.

National Academies of Sciences, Engineering, and Medicine. 2018. Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press. https://doi.org/10.17226/25104.

Moore-Sloan Data Science Environments

On our campuses, library spaces have been transformed—among other things—into campus centers for data science research, training, and services, with open floor plans and furnishings that are adaptable to a range of activities that promote and support data science research and learning.

Creating Institutional Change in Data Science” Chronicles of Higher Ed, Mar 2018

Rise of data science initiatives in academia

From the Data Science Community Newsletter by Noren & Stenger:
Brigham Young University, Caltech, Carnegie Mellon, College of Charleston, Columbia, Cornell, Dartmouth UMass, George Mason University, Georgetown University, Georgia Tech, Harvard, Illinois Wesleyan University, Johns Hopkins, Mid America Nazarene University, MIT, Northeastern University, Northern Kentucky University, Northwestern, Northwestern College in Iowa, Ohio State University, Penn State University, Princeton, Purdue, Stanford, Tufts University, UC Berkeley, UC Davis, UC Irvine, UC Merced, UC Riverside, UC San Diego, UCLA, UIUC, University of Iowa, University of Michigan, University of Oregon, University of Pennsylvania, University of Rochester, University of San Francisco, University of Warwick, University of Washington, UT Austin, UW Madison, Vanderbilt University, Virginia Tech, Washington University in St. Louis, Middle Tennessee State University, NYU, Amherst College, Brown, CU Boulder, Duke, Illinois Institute of Technology, Lehigh University, Loyola University - Maryland, Rice University, SUNY at Stony Brook, UC Santa Barbara, UC Santa Cruz, UCSF, UMass Amherst, UNC - Wilmington, University of Vermont, University of Arizona, University of British Columbia, University of Chicago, University of Virginia, USC, Worchester Polytechnic, Yale
70 and counting…

Investing in America’s data science and analytics talent

April 2017 Business-Higher Education Forum (BHEF) report titled “Investing in America’s Data Science and Analytics Talent: The Case for Action.

66% of the Data Carpentry workshop attendees are early career.

Analysis of Software and Data Carpentry’s Pre- and Post-Workshop Surveys https://doi.org/10.5281/zenodo.1325463

Data Carpentry Respondents by Career Stage

The Carpentries workshops and lesson materials address data and software needs.

Training in data science tools and approaches provides a path to better science in less time.

Our path to better science in less time using open science tools

Reproducibility has long been a tenet of science but has been challenging to achieve—we learned this the hard way when our old approaches proved inadequate to efficiently reproduce our own work. Here we describe how several free software tools have fundamentally upgraded our approach to collaborative research, making our entire workflow more transparent and streamlined. By describing specific tools and how we incrementally began using them for the Ocean Health Index project, we hope to encourage others in the scientific community to do the same—so we can all produce better science in less time.

Lowndes, Julia S. Stewart, et al. “Our path to better science in less time using open data science tools.” Nature ecology & evolution 1.6 (2017): 160.

Challenges & opportunities for libraries

The Strategic Value of Library Carpentry & The Carpentries to Research Libraries

For libraries, organizing Data, Software, and Library workshops and meet-ups have provided an excellent opportunity to connect with their community, understand their data and software needs, and grow their library services.

See:
https://librarycarpentry.org/blog/2018/08/library-carpentry-strategic-value/

UNC Chapel Hill Libraries

Reasons why people come to Library Carpentry…

38 mentions of The Carpentries in The Shifting to Data Savvy Report.

Demonstrated need from libraries

Expanding Library Carpentry

The California Digital Library will advance the scope, adoption, and impact of the emergent “Library Carpentry” continuing education program… The training opportunities enabled by the project will provide librarians with the critical data and computational skills and tools they need to be effective digital stewards for their stakeholders and user communities.

See Institute of Museum and Library Services Grant RE-85-17-0121-17

On April 17, 2018, the California Digital Library welcomed Chris Erdmann, Library Carpentry Community and Development Director to help grow the Library Carpentry effort.

Growing Library Carpentry involves:

Involving community members has been key

Software, Data, and Library Carpentry at a glance

Workshops

For images, see https://twitter.com/search?f=images&vertical=default&q=library%20carpentry%20workshop&src=typd

Workshops are 2-day, hands-on, interactive, friendly learning environment (Code of Conduct), teaching the foundational skills and perspectives for working with software and data

Focus of Data, Software, and Library Carpentry

The Carpentries workshop goals

Goals of the workshop, aren’t just to teach the skills, but to build self-efficacy and increase confidence and create a positive learning experience. We know we can’t teach everything in two days, but we want to teach the foundational skills and get people started and give them the confidence to continue learning. Many people have had demotivating experience when learning things like coding or computational skills, and we want to change that perspective.

Instructor training

Educational pedagogy is the focus of Instructor training program. The following steps are required to become a certified Instructor who can teach all Carpentries lessons!

More information: http://carpentries.github.io/instructor-training/

Lesson maintenance

Community opportunities

Outcomes

Short and long term surveys show that people are learning the skills, putting them into practice and have more confidence in their ability to do computational work. See The Carpentries January 2018 long-term survey report

Outcomes

We also see researchers writing about the impact Carpentries training and approaches have had in their workflows:

Yenni, G. M., Christensen, E. M., Bledsoe, E. K., Supp, S. R., Diaz, R. M., White, E. P., & Ernest, S. M. (2019). Developing a modern data workflow for regularly updated data. PLoS biology, 17(1), e3000125. Chicago https://doi.org/10.1371/journal.pbio.3000125

Library Carpentry core objectives

Library Carpentry workshops teach people working in library- and information-related roles how to:

How to get involved

How can I get started? Contribute to a lesson.

All of our lessons are CC-BY and hosted on GitHub at https://github.com/LibraryCarpentry. Anyone can contribute!

How can I get started? Host, help, teach.

Become a member

The Carpentries & Library Carpentry websites

Connect with The Carpentries

Share information with your colleagues

What is your library/network doing to meet the data science needs of your community?

Thank you

Key Points

  • Library Carpentry helps libraries…

  • Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks.

  • Identify and use best practices in data structures.

  • Learn how to programmatically transform and map data from one form to another.

  • Work effectively with researchers, IT, and systems colleagues.

  • Automate repetitive, error prone tasks.