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Library Carpentry Case Studies rscd2018
- 1. + case studies $ Sharron Stapleton QUT $ Matthias Liffers University of Western Australia
- 2. $ why library carpentry? Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh
- 3. $ what is with the sticky notes? Image Source: Nick Hamilton https://www.flickr.com/photos/100739735@N06/32413492400/in/album-72157678322534801/
- 4. $ who provides library carpentry? Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image source: http://www.nsla.org.au/sites/www.nsla.org.au/files/styles/large/public/BW-vols-600.jpg?itok=bXz1ygaC Belinda Weaver with volunteer helpers Richard Vankoningsveld (left) and Sam Hames (right) at the Library Carpentry workshop at State Library of Queensland.
- 5. $ so I go to training…now what? Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop
- 6. Learners @ LATN Library Carpentry UTS July 2016 $ our experience Image source: Nick Hamilton https://www.flickr.com/photos/100739735@N06/35356351354/ Image source: Belinda Weaver @cloudaus 30 Oct 2017 Image source: Barbara Parnaby @BJPiano 11 July 2016 Instructors Dec 2017 Learners @ Carpentry instructor training UQ July 2017 Helpers @ Software Carpentry QUT Oct 2017
- 7. $ The 21st Century Academic: Smart, Savvy and Social program $ Prof Ginny Barbour, Natasha Simons, QUT Library & CC Australia How does a cross-institutional group collaborate to create a new workshop with reproducible website and version control? https://github.com/
- 8. $ ERA Impact and Engagement Pilot Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop How many of these 7782 papers were co-authored with someone outside academia? Without doing it manually.
- 9. $ ERA Impact and Engagement Pilot Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 1: What are the rules? One author’s affiliation NOT (univ* OR inst*)
- 10. $ ERA Impact and Engagement Pilot Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 2: What does our data look like? All authors and their affiliations in one field, delimited with ;
- 11. $ ERA Impact and Engagement Pilot Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 3: Which tool(s) can we use? OpenRefine can split the field and preserve record structure /^((?!univ|inst).)*$/ (not exact)
- 12. $ ERA Impact and Engagement Pilot Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 4: How much time and sanity did we save? 15 hours
- 13. $ Bolstering Open Access articles Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop How many UWA-authored papers are Open Access without us knowing about it? Without doing it manually.
- 14. $ Bolstering Open Access articles Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 1: What are the parameters? Identify unknown OA papers in our own repository
- 15. $ Bolstering Open Access articles Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 2: What does our data look like? 30,518 publications with DOIs, but those DOIs may be incorrectly formatted
- 16. $ Bolstering Open Access articles Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 3: Which tools can we use? OpenRefine to clean data and query API for each DOI oaDOI API (now known as Unpaywall API)
- 17. $ Bolstering Open Access articles Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop Step 4: How much time and sanity did we save? 2435 previously unknown OA papers discovered 7 working weeks @ 30 seconds per paper
- 18. $ back to those sticky notes… Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop one data example one barrier
- 19. $ Thank you Image Source: Mario Antonioletti https://www.epcc.ed.ac.uk/blog/2016/08/29/data-and-software-carpentry-combo-edinburgh Image Source: Belinda Weaver @cloudaus 30 Jul 2017. Underway with #jargonbusting @LibCarpentry @nsla Adelaide workshop
Editor's Notes
- Developer of Library Carpentry James Baker Librarians play a crucial role in cultivating world-class research. In most disciplinary areas today world-class research relies on the use of software. Comparable introductory software training programmes with a focus on the needs and requirements of the library professionals do not exist (Data Science for Librarians being a notable exception). This I find curious because research librarians already have substantial expertise working with data and adding software skills to their armoury would seem to be an effective and useful use of professional development resource. And so Library Carpentry aimed to both fill and better understand a skills gap, confident that a proliferation of librarians with software skills can only make world-class research even better. Principles around Library carpentry: Professional development – capacity building Helping Librarian to help clients Connect people with information and services Increasingly in the research sector, academics no longer need librarians to help them find information, they want data or information in the data they already have. Your organisation my provide financial data via subscription databases, that don’t pull the data out in the layout the researcher needs. They want help to clean, mine, sift and manage and visualise that data. http://musingsaboutlibrarianship.blogspot.com.au/2017/12/data-carpentry-long-data-from-library.html Aaron Tay is currently Library Analytics Manager Every organisation generates data that needs to be used for planning and service delivery University and research libraries are open access publishers, developing repositories and curating digital objects, including peer reviewed publications, theses, data, presentations, performances and more. How do we extract value from or understand the value of these? Defined metrics are great, but what about the semi regular queries to examine a sub-set of the database, or identify errors to fix, extract particular data from many different formats of output. How can we mine these datasets? What questions might we answer for our Research Office for the ERA process, faster and reproducible? Digital stewards (Uni of California) University of California / California Digital Library was recently awarded a grant from Institute of Museum and Library Services that funds a two year, full-time North American Coordinator for Library Carpentry and discussions are starting about integrating with Software Carpentry and Data Carpentry. In their statement of need As institutions have begun to view the data output of researchers as an asset, and as requirements for data sharing have become the norm for funding, issues around research data best practices have emerged. This has resulted in the formation of Research Data Management and Research Data Curation programs, often located in the library. The services offered include access to repositories, information on Data Management Plans (DMPs), and consultations about requirements. While studies show this kind of training is a critical need for researchers, training in data skills and tools are lacking, and librarians with the ability to teach or help researchers with their hands-on data needs are rare. In addition, librarians cannot be effective in connecting scholars with information and tools without themselves understanding how research is done, the nature of scholarly communications, and the tools used. In the past, the relationship between scholars, faculty researchers and librarians was based on a service model: the ‘user’ would approach the librarian for information and receive it. Today, that relationship must evolve into a collaborative model, as ‘users’ now need information from their own or other data sets, and come to the library for help in analyzing and/or extracting it. This means librarians need to become skilled in data best practices, including data management and analysis during their formal educational training. This also means that existing librarians require ongoing professional development to stay up to date on the evolving landscape of skills and tools, such as OpenRefine, Python, R, and SQL, and data-intensive approaches to librarianship. https://www.imls.gov/sites/default/files/grants/re-85-17-0121-17/proposals/re-85-17-0121-17-full-proposal-documents.pdf
- Carpentries has developed a learning model over the past almost 20 years. Whilst a crammed two day workshop Community of practice model For novices – safe environment Peer learning and assistance Early easy wins Learning model – carpentry core elements , Delivered over four segments 9 different classes at different stages of completeness as developed over time by a community of volunteers
- Case study one Extracting specific data from xml files from our Research data repository. Examples of possible use of Open Refine by librarians at QUT Fit might make isbns easier in matching for data sets or some tricky publishing questions! Making our ILRS millenium weeding lists tighter and easier to read Some of the editing things are much easier than in excel en masse is fabulous. I'd like to learn how to merge two datasets - this would be directly useful to my HDR student so I might have a play
- Github allowed a group