Gugelmann Galaxy
An Unexpected Journey through a collection of Schweizer Kleinmeister
GLAM institutions all over the world are digitizing their collections. As the number of items in such a collection amounts to tens or even hundreds of thousands, providing comprehensible access and presentation becomes increasingly difficult. At the same time, a steadily growing amount of this data is openly available. This gives rise to various projects approaching the hidden treasures in these collections with computational tools. The project presented here, Gugelmann Galaxy, lets the user explore an entire collection of digitized images and their textual metadata in an immersive three-dimensional cloud, whose configuration can be rearranged according to different criteria. The project questions traditional models of categorization and curating and implements alternative approaches prototypically.
Copyright (c) 2016 International Journal for Digital Art History
This work is licensed under a Creative Commons Attribution 4.0 International License.
More Citation Formats
BBC. 2014. "YourPaintings." Accessed 6. Aug. http://www.bbc.co.uk/arts/yourpaintings/paintings/search.
Bernhard, Mathias, Nikola Marinčić, and Jorge Orozco. 2015. "ANY-FOLD: On Curation, Literacy & Space." trans, 84-87.
Bernhard, Mathias, Nikola Marinčić, Jorge Orozco, and Sonja Gasser. 2015. "Schweizer Kleinmeister: An Unexpected Journey." opendata.ch. http://make.opendata.ch/wiki/project:schweizer_kleinmeister:an_unexpected_journey.
Cleveland, Carter, and Sebastian Cwilich. 2010. "The Art Genome Project." https://www.artsy.net/about/the-art-genome-project.
Crowley, Elliot J., and Andrew Zissermann. 2014a. "In Search of Art." In Workshop on Computer Vision for Art Analysis, ECCV.
Crowley, Elliot J., and Andrew Zissermann. 2014b. "The State of the Art: Object Retrieval in Paintings using Discriminative Regions." British Machine Vision Conference.
Dalal, N, and B Triggs. 2005. "Histograms of Oriented Gradients for Human Detection." IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA.
Elgammal, Ahmed, and Babak Saleh. 2015. "Quantifying Creativity in Art Networks." The Art and Artificial Intelligence Laboratory, Department of Computer Science, Rutgers University.
Erbuer, Moenen, and Tobias Boonstoppel. 2012. Curiator - The World's Greatest Collaborative Art Collection New York, NY.
Freeland, Cynthia A. 2001. But Is It Art? Oxford, New York: Oxford University Press.
Fried, Ohad, Stephen DiVerdi, Maciej Halber, Elena Sizikova, and Adam Finkelstein. 2015. "IsoMatch: Creating Informative Grid Layouts." Computer Graphics Forum (Proc. Eurographics) 34 (2).
Gurian, Elaine Heumann. 2006. "The Essential Museum." Museums Aotearoa Conference, Hawke's Bay, New Zealand.
Horaczek, Stan. 2013. "How Many Photos Are Uploaded to The Internet Every Minute?" Popular Photography, 6. Aug. http://www.popphoto.com/news/2013/05/how-many-photos-are-uploaded-to-internet-every-minute.
ImageNet. 2010. "Summary and Statistics." Last Modified April 30, 2010 Accessed 6. Aug. http://www.image-net.org/about-stats.
Karayev, Sergey. 2013. "Vislab - Computer Vision Group." Berkeley, University of California Accessed 6. Aug. http://vislab.berkeleyvision.org/tutorial.html.
RasterFairy 1.0.2. Klingemann, Mario (Quasimondo), GitHub.
Komar, Vitaly, and Alexander Melamid. 1994. UNITED STATES: MOST WANTED PAINTING. Dia Center for the Arts.
Konvitz, Ezra. 2012. ArtStack.
Kräutli, Florian. 2015. "MoMA on GitHub." YYYY-MM-DD Time/Data/Visualization. http://research.kraeutli.com/index.php/2015/09/moma-on-github/.
Manovich, Lev. 2015. "Data Science and Digital Art History." International Journal for Digital Art History (1).
MoMA. 2015. The Museum of Modern Art (MoMA) collection data. doi:10.5281/zenodo.21147.
Norvig, Peter. 2011. The Unreasonable Effectiveness of Data. YouTube: UBCCPSC.
Pedregosa, F., G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011. "Scikit-learn: Machine Learning in Python." Journal of Machine Learning Research 12:2825 - 2830.
Saleh, Babak, Kanako Abe, Ravneet Singh Arora, and Ahmed Elgammal. 2014. "Toward Automated Discovery of Artistic Influence." In Multimedia Tools and Applications. Springer US.
Saleh, Babak, and Ahmed Elgammal. 2015. "Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature." Department of Computer Science, Rutgers University.
Schlecht, Joseph, Bernd Carqué, and Björn Ommer. 2011. "Detecting Gestures in Medieval Images." IEEE International Conferene on Image Processing (ICIP 2011), Brussels, Belgium.
Tenenbaum, Joshua B., Vin de Silva, and John C. Langford. 2000. "A Global Geometric Framework for Nonlinear Dimensionality Reduction." Science 290 (5500):2319-2323. doi: 10.1126/science.290.5500.2319.
van der Maarten, L.J.P., and G. E. Hinton. 2008. "Visualizing High-Dimensional Data Using t-SNE." Journal of Machine Learning Research 9:2579-2605.
WikiArt. 2010. WikiArt - Encyclopedia of fine arts. http://www.wikiart.org.
Yarlagadda, Pradeep, Antonio Monroy, Bernd Carqué, and Björn Ommer. 2012. "Towards a Computer-Based Understanding of Medieval Images." In Scientific Computing and Cultural Heritage.
Copyright (c) 2016 International Journal for Digital Art History
This work is licensed under a Creative Commons Attribution 4.0 International License.
