A Role-Based Model for Successful Collaboration in Digital Art History

  • Alison Langmead (Author)
    University of Pittsburgh
    http://orcid.org/0000-0002-9159-9797
  • Tracey Berg-Fulton (Author)
    Carnegie Museum of Art
  • Thomas Lombardi (Author)
    Washington and Jefferson College
  • David Newbury (Author)
    Carnegie Museum of Art
  • Christopher Nygren (Author)
    University of Pittsburgh

Identifiers (Article)

Abstract

Sustained dialogue and collaborative work between art historians and technologists has a great deal to offer both fields of inquiry. In this paper, we propose that effective collaborations in Digital Art History, however, require more than just a humanist and a technologist to succeed. Indeed, we find that there are four different roles that need to be filled: Humanist, Technologist, Data Steward, and Catalyst. Our approach is predicated on a few foundational convictions. First, we believe that art historians and technologists occupy distinct problem spaces. As we will outline, although these realms are distinct they are not of necessity in opposition to one another. Second, we bring to the fore essential questions about the status and function of data that must be addressed by the collaborators: what sort of data are being used? What counts as effective and compelling analysis of this data? Third, we recognize that there are certain structural impediments to collaboration, such as different reward structures and motivations. Finally, we assert that each of the participants must have a deep commitment to their particular engagement with the project, which requires sustained effort and the maintenance of disciplinary respect. We firmly believe that the most effective of these projects will not be based on technological solutionism, but rather will be founded in the most humanistic of tools: empathy and respect.

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References

Art Tracks Project, “The CMOA Digital Profenance Standard,” draft version 0.2, published October 14, 2016, http://www.museumprovenance.org/reference/standard/.

Gordon Bell, Tony Hey, and Alex Szalay, “Beyond the Data Deluge,” Science 323, no. 5919 (2009): 1297–98, doi:10.1126/science.1170411.

Tracey Berg-Fulton, David Newbury, and Travis Snyder. "Art Tracks: Visualizing the Stories and Lifespan of an Artwork," MW2015: Museums and the Web 2015, published January 15, 2015, http://mw2015.museumsandtheweb.com/paper/art-tracks-visualizing-the-stories-and-lifespan-of-an-artwork/.

James Cuno, “How Art History Is Failing at the Internet,” The Daily Dot, November 19, 2012, http://www.dailydot.com/via/art-history-failing-internet/.

Li Deng and Dong Yu, “Deep Learning: Methods and Applications,” Foundations and Trends in Signal Processing 7, no. 3–4 (2014): 197–387, doi:10.1561/2000000039.

Martin Hilbert, “Big Data for Development: A Review of Promises and Challenges,” Development Policy Review 34 (January 2016): 135–174, doi:10.1111/dpr.12142.

Matthew K. Gold and Lauren F. Klein, eds., Debates in the Digital Humanities, 2nd edition (Minneapolis: University of Minnesota Press, 2016), http://dhdebates.gc.cuny.edu/debates/2.

Matthew L. Jockers, Macroanalysis: Digital Methods & Literary History (Urbana, Chicago and Springfield: University of Illinois Press, 2013), 31.

Bruno Latour, “Circulating Reference: Sampling the Soil in the Amazon Rainforest,” in Pandora’s Hope: Essays on the Reality of Science Studies (Cambridge and London: Harvard University Press, 1999), 24-79.

Bruno Latour, On the Modern Cult of the Factish Gods (Durham: Duke University Press, 2010).

David Lazer et al., “The Parable of Google Flu: Traps in Big Data Analysis,” Science 343, no. 6176 (March 13, 2014): 1203, doi:10.1126/science.1248506.

Thomas Lombardi, “Interdisciplinary Approaches to Metadata,” Computational Visual Aesthetics Workshop (Pittsburgh, PA, November 13, 2015), https://sites.haa.pitt.edu/cva/interdisciplinary-approaches-to-metadata-tom-lombardi/.

Thomas Lombardi, “Interdisciplinary Approaches to Metadata,” professional paper given at Keystone DH 2016, Pittsburgh, PA, 2016, http://keystonedh.network/2016/.

Lev Manovich, “Data Science and Digital Art History,” International Journal for Digital Art History 1 (June 2015): 13-35, http://dx.doi.org/10.11588/dah.2015.1.21631.

Max Marmor (responding to Hubertus Kohle), “Art History and the Digital Humanities: Invitation to Debate,” Zeitschrift für Kunstgeschichte 79 (2016): 151-163, cited at 155.

Neil Postman, Technopoly: The Surrender of Culture to Technology (New York, NY: Vintage Books, 1993).

Alex Potts, Flesh and the Ideal: Winckelmann and the Origins of Art History (New Haven and London: Yale University Press, 1994).

Alois Riegl, Problems of Style: Foundations for a History of Ornament, translated by Evelyn Kain (Princeton: Princeton University Press, 1992), 4.

Alois Riegl, Late Roman Art Industry, translated from the original Viennese edition with foreword and Annotations by Rolf Winkes (Rome: Giorgio Bretschneider, 1985), 9.

Aimee Kendall Roundtree, Computer Simulation, Rhetoric, and the Scientific Imagination: How Virtual Evidence Shapes Science in the Making and in the News (Lexington Books, 2013).

Galit Shmueli, “To Explain or Predict?” Statistical Science 25, no. 3 (2010): 289–310.

A. M. Turing, “On Computable Numbers, with an Application to the Entscheidungsproblem,” Proceedings of the London Mathematical Society, 1936, 230–65.

Scott Weingart, “Lessons From Digital History’s Antecedents,” The Scottbot Irregular, October 30, 2016, http://scottbot.net/lessons-from-digital-historys-antecedents/.

Herbert I. Weisberg, Willful Ignorance: The Mismeasure of Uncertainty (New York: Wiley, 2014).

Bernard Williams, Truth and Truthfulness: An Essay in Genealogy (Princeton and Oxford: Princeton University Press, 2002).

Johann Joachim Winckelmann, History of the Art of Antiquity, translated by Harry Francis Mallgrave (Los Angeles: Getty Research Institute, 2006), 76.

Section
Language
en
Contributor or sponsoring agency
IMLS
Keywords
Digital Art History, Collaborations, Interdisciplinary Work, Interdisciplinary Respect
How to Cite
Langmead, Alison, Tracey Berg-Fulton, Thomas Lombardi, David Newbury, and Christopher Nygren. 2018. “A Role-Based Model for Successful Collaboration in Digital Art History”. International Journal for Digital Art History, no. 3 (July). https://doi.org/10.11588/dah.2018.3.34297.