Bibliography – Data Notebooks

Selected DH research and resources bearing on, or utilized by, the WE1S project.
(all) Distant Reading | Cultural Analytics | Sociocultural Approaches | Topic Modeling in DH


Koenzen, Andreas, Neil Ernst, and Margaret-Anne Storey. “Code Duplication and Reuse in Jupyter Notebooks.” ArXiv:2005.13709 [Cs], 2020. http://arxiv.org/abs/2005.13709. Cite
Chattopadhyay, Souti, Ishita Prasad, Austin Z. Henley, Anita Sarma, and Titus Barik. “What’s Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities.” In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–12. CHI ’20. Honolulu, HI, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3313831.3376729. Cite
DePratti, Roland. “Jupyter Notebooks versus a Textbook in a Big Data Course.” Journal of Computing Sciences in Colleges 35, no. 8 (2020): 208–20. https://dl.acm.org/doi/abs/10.5555/3417639.3417658. Cite
Willis, Alistair, Patricia Charlton, and Tony Hirst. “Developing Students’ Written Communication Skills with Jupyter Notebooks.” In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 1089–1095. SIGCSE ’20. Portland, OR, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3328778.3366927. Cite
Wang, April Yi, Anant Mittal, Christopher Brooks, and Steve Oney. “How Data Scientists Use Computational Notebooks for Real-Time Collaboration.” Association for Computing Machinery, 2019. https://doi.org/10.1145/3359141. Cite
Bouquin, Daina, Sophie Hou, Matthew Benzing, and Lee Wilson. “Jupyter Notebooks: A Primer for Data Curators,” 2019. http://conservancy.umn.edu/handle/11299/202815. Cite
Pimentel, João Felipe, Leonardo Murta, Vanessa Braganholo, and Juliana Freire. “A Large-Scale Study about Quality and Reproducibility of Jupyter Notebooks.” In Proceedings of the 16th International Conference on Mining Software Repositories, 507–517. MSR ’19. Montreal, Quebec, Canada: IEEE Press, 2019. https://doi.org/10.1109/MSR.2019.00077. Cite
Rule, Adam, Amanda Birmingham, Cristal Zuniga, Ilkay Altintas, Shih-Cheng Huang, Rob Knight, Niema Moshiri, et al. “Ten Simple Rules for Writing and Sharing Computational Analyses in Jupyter Notebooks.” PLOS Computational Biology 15, no. 7 (2019): e1007007. https://doi.org/10.1371/journal.pcbi.1007007. Cite
Mendez, Kevin M., Leighton Pritchard, Stacey N. Reinke, and David I. Broadhurst. “Toward Collaborative Open Data Science in Metabolomics Using Jupyter Notebooks and Cloud Computing.” Metabolomics 15, no. 10 (2019): 125. https://doi.org/10.1007/s11306-019-1588-0. Cite
Dombrowski, Quinn, Tassie Gniady, and David Kloster. “Introduction to Jupyter Notebooks.” Programming Historian, 2019. https://programminghistorian.org/en/lessons/jupyter-notebooks. Cite
Wigham, Mari, Liliana Melgar, and Roeland Ordelman. “Jupyter Notebooks for Generous Archive Interfaces.” In 2018 IEEE International Conference on Big Data (Big Data), 2766–74, 2018. https://doi.org/10.1109/BigData.2018.8622203. Cite
Rule, Adam, Aurélien Tabard, and James D. Hollan. “Exploration and Explanation in Computational Notebooks.” In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems  - CHI ’18, 1–12. Montreal QC, Canada: ACM Press, 2018. https://doi.org/10.1145/3173574.3173606. Cite
Kery, Mary Beth, Marissa Radensky, Mahima Arya, Bonnie E. John, and Brad A. Myers. “The Story in the Notebook: Exploratory Data Science Using a Literate Programming Tool.” In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1–11. CHI ’18. Montreal QC, Canada: Association for Computing Machinery, 2018. https://doi.org/10.1145/3173574.3173748. Cite
Perkel, Jeffrey M. “Why Jupyter Is Data Scientists’ Computational Notebook of Choice.” Nature 563, no. 7729 (2018): 145–46. https://doi.org/10.1038/d41586-018-07196-1. Cite
Liu, Alan, Scott Kleinman, Jeremy Douglass, Lindsay Thomas, Ashley Champagne, and Jamal Russell. “Open, Shareable, Reproducible Workflows for the Digital Humanities: The Case of the 4Humanities.Org ‘WhatEvery1Says’ Project.” In Digital Humanities 2017 Conference Abstracts. Montreal: Alliance of Digital Humanities Organizations (ADHO), 2017. Cite
Randles, Bernadette M., Irene V. Pasquetto, Milena S. Golshan, and Christine L. Borgman. “Using the Jupyter Notebook as a Tool for Open Science: An Empirical Study.” In 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 1–2, 2017. https://doi.org/10.1109/JCDL.2017.7991618. Cite
Jupyter, Project. “Project Jupyter: Computational Narratives as the Engine of Collaborative Data Science.” Medium, 2017. https://blog.jupyter.org/project-jupyter-computational-narratives-as-the-engine-of-collaborative-data-science-2b5fb94c3c58. Cite
Kluyver, Thomas, Benjamin Ragan-Kelley, Fernando Pérez, Brian Granger, Matthias Bussonnier, Jonathan Frederic, Kyle Kelley, et al. “Jupyter Notebooks – a Publishing Format for Reproducible Computational Workflows.” Positioning and Power in Academic Publishing: Players, Agents and Agendas, 2016, 87–90. https://doi.org/10.3233/978-1-61499-649-1-87. Cite