Code-Literacy for GIS Librarians: A Discussion of Languages, Use Cases, and Competencies

Abstract

Geospatial librarianship has always been inherently tied to technology, requiring that GIS librarians have specialized computer literacy. In recent years, the push for open science, transparency, and improved reproducibility in research has led to increased use of open source geospatial technology. These developments have led to a blending of GIScience with the emerging field of Data Science, and many students and researchers are increasingly using free and open source programming languages to complement or replace traditional GIS software. New data formats, modern modes of data exchange, and the data as a service trend require an intricate understanding of computer science. If GIS librarians are to meet the needs of current and future patrons, code-literacy will soon be a necessity, yet a discussion of these tools and skills are lacking in the literature of geospatial librarianship. This paper discusses the present revolution in geospatial technology, recommending an integration of coding skills into the most elemental levels of the Core Competencies for GIS Librarianship. We review two programming languages, R and Python, for their suitability for librarians wishing to advance their technical skills by either learning a new language or learning to program for the first time. Drawing from our own experiences, we discuss the potential of coding to transform how GIS librarians engage with their work.

Keywords:

• Librarianship
• GIS
• Geospatial data
• Programming
• Data science

Notes

1 https://www.colorado.edu/earthlab

2 https://r-arcgis.github.io/

3 https://pypi.org/

4 https://osgeo.org/projects

5 See https://developers.google.com/maps/documentation/javascript, https://leafletjs.com/, https://docs.mapbox.com/help/glossary/mapbox-gl-js/ for more information.

6 https://www.mountainproject.com/

7 https://earthengine.google.com/

8 https://www.rstudio.com/, https://www.spyder-ide.org/, https://www.jetbrains.com/pycharm/, https://atom.io/

9 https://jupyter.org/