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006

Bibliography & other Resources

Readings, tutorials, tools and datasets for the workshop.

Entry
No. 006
Part
Reference
Status
Entered

Mandatory readings

Rother, Lynn, Max Koss, and Fabio Mariani. “Taking Care of History: Toward a Politics of Provenance Linked Open Data in Museums.” In Perspectives on Data, edited by Emily Lew Fry and Erin Canning. Art Institute of Chicago, 2022.
https://www.artic.edu/digital-publications/37/perspectives-on-data/25/taking-care-of-history

Schich, Maximilian, Christian Huemer, Patryk Adamczyk, Lev Manovich, and Yang-Yu Liu. “Network Dimensions in the Getty Provenance Index.” arXiv (2017).
https://arxiv.org/abs/1706.02804

Getty Provenance Index tutorials

  • Introduction to the Getty Provenance Index
  • Artists, Collectors & Dealers in the GPI
  • Using the Getty Provenance Index Databases
  • Getty Provenance Index Explained: A Walkthrough

Bibliography

Ahnert, Ruth, and Sebastian E. Ahnert. Tudor Networks of Power. Oxford University Press, 2023.
https://doi.org/10.1093/oso/9780198858973.001.0001

Ahnert, Ruth, Sebastian E. Ahnert, and Catherine Nicole Coleman. The Network Turn. Cambridge University Press, 2021.
https://doi.org/10.1017/9781108866804

Barabási, Albert-László, et al. “Quantifying Reputation and Success in Art.” Science 362, no. 6416 (2018): 825–829.
https://doi.org/10.1126/science.aau7224

Barabási, Albert-László, et al. Network Science.
http://networksciencebook.com/

Bishop, Claire. “Against Digital Art History.” International Journal for Digital Art History 3 (2018).
https://doi.org/10.11588/dah.2018.3.49915

Cairo, Alberto. How Charts Lie: Getting Smarter About Visual Information. W. W. Norton, 2020.

D’Ignazio, Catherine, and Lauren F. Klein. Data Feminism. MIT Press, 2023.
https://data-feminism.mitpress.mit.edu/

Drucker, Johanna. Graphesis: Visual Forms of Knowledge Production. Harvard University Press, 2014.
https://www.hup.harvard.edu/books/9780674724938

Huemer, Christian. “The Provenance of Provenances.” In Collecting & Provenance: A Multidisciplinary Approach, edited by Jane C. Milosch and Nick Pearce. Rowman & Littlefield, 2019.
https://www.academia.edu/43252971/The_Provenance_of_Provenances

Karsdorp, Folgert. Python Programming for the Humanities.
https://www.karsdorp.io/python-course/

Karsdorp, Folgert, Mike Kestemont, and Allen Riddell. Humanities Data Analysis: Case Studies with Python. Princeton University Press, 2021.
https://www.humanitiesdataanalysis.org/

Lincoln, Matthew D. “Tangled Metaphors: Network Thinking and Network Analysis in the History of Art.” In The Routledge Companion to Digital Humanities and Art History, Routledge, 2020.

Love, Heather. “Close but Not Deep: Literary Ethics and the Descriptive Turn.” New Literary History 41, no. 2 (2010): 371–391.
https://doi.org/10.1353/nlh.2010.0003

Mariani, Fabio. “Introducing VISU: Vagueness, Incompleteness, Subjectivity, and Uncertainty in Art Provenance Data.” In Computational Methods in the Humanities 2022, CEUR Workshop Proceedings, 3602 (2023).
https://ceur-ws.org/Vol-3602/

Mariani, Fabio, Max Koss, and Lynn Rother. “People Information in Provenance Data: Biographical Entity Linking with Wikidata and ULAN.” Život Umjetnosti 114, no. 1 (2024): 148–161.
https://doi.org/10.31664/zu.2024.114.07

Mariani, Fabio, Lynn Rother, and Max Koss. “Teaching Provenance to AI: An Annotation Scheme for Museum Data.” In AI in Museums: Reflections, Perspectives and Applications, edited by Sonja Thiel and Johannes Bernhardt. Transcript Verlag, 2023.
https://doi.org/10.1515/9783839467107-014

McNeill, J. R., and William H. McNeill. The Human Web: A Bird’s-Eye View of World History. W. W. Norton, 2003.

Meirelles, Isabel. Design for Information. Rockport Publishers, 2013.

Poirier, Lindsay. “Ethnographies of Datasets: Teaching Critical Data Analysis Through R Notebooks.” 2020.
https://jitp.commons.gc.cuny.edu/ethnographies-of-datasets-teaching-critical-data-analysis-through-r-notebooks/

Porras, Stephanie. “Keeping Our Eyes Open: Visualizing Networks and Art History.” Artl@s Bulletin 6, no. 3 (2017).
https://docs.lib.purdue.edu/artlas/vol6/iss3/3

Ricaurte, Paola. “Data Epistemologies, the Coloniality of Power, and Resistance.” Television & New Media 20, no. 4 (2019): 350–365.
https://doi.org/10.1177/1527476419831640

Rother, Lynn. “Uncanny Provenance: Art History and Its Double / Unheimliche Provenienz: Kunstgeschichte und ihr Doppelgänger.” Texte zur Kunst 32, no. 128 (2022): 84–97.

Rother, Lynn. “Institutionalisierte Institutionskritik: Lynn Rother über ‘Wege der Kunst’ im Museum Rietberg, Zürich, sowie ‘Zerrissene Moderne’ und ‘Der Sammler Curt Glaser’ im Kunstmuseum Basel.” Texte zur Kunst 33, no. 131 (2023): 214–219.

Rother, Lynn, Max Koss, and Fabio Mariani. “Interpreting Strings, Weaving Threads: Structuring Provenance Data with AI.” In Sammlungsforschung im Digitalen Zeitalter, edited by Stefan Alschner and Katharina Günther. Wallstein Verlag, 2024.
https://doi.org/10.15499/kds-005-008

Shekhtman, Louis Michael, and Albert-László Barabási. “Philanthropy in Art: Locality, Donor Retention, and Prestige.” Scientific Reports 13, no. 1 (2023): 12157.
https://doi.org/10.1038/s41598-023-38815-1

Other resources

  • CARE Principles for Indigenous Data Governance
  • CIDOC CRM, Version 7.3
  • Creating a Data Cleaning Workflow
  • Dataviz Project
  • Getty Vocabularies (AAT, ULAN, TGN)
  • Linked Art — Linked Art Community
  • Programming Historian
  • The FAIR Guiding Principles for Scientific Data Management and Stewardship
  • The Virtual International Authority File (VIAF)
  • Visualizing Historical Networks
  • Voyant Tools
  • Wikidata: A Free and Open Knowledge Base
Brought forward005 Visualising Data
 

© 2026 Coding Provenance Workshop — Licensed under a Creative Commons Attribution 4.0 International License.
Reuse is encouraged — we happily promote changes of custody. Just be sure to write a good provenance record and cite this workshop.
The painting reproductions are not covered by this licence; see the credit with each one.