Data-Driven Curated Video Catalogs: Republishing Video Footage

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Gabriele Colombo
Federica Bardelli


This project illustrates data-driven curated video catalogs as an approach for the analysis of video footage. Having rich and diverse collections of videos as inputs, data-driven catalogs seek to identify common objects and reorganize them into thematic clusters displayed in a video format. The technique takes inspiration from two scientific practices (core sampling and light diffraction) and two publishing formats (supercuts and visual catalogs). Data-driven curated video catalogs are used to republish a collection of found footage of 2019 Veniceʼs high water that devastated the city in an unprecedented way. Starting from an editorial selection of footage culled from YouTube, various algorithmic processes are used to demarcate and reorganize the material into thematic video series (people, boats, and birds). The resulting video catalogs support a type of visual analysis that goes beyond traditional forms of measurement while, at the same time, carrying an expressive power.


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How to Cite
Colombo, G., & Bardelli, F. . (2021). Data-Driven Curated Video Catalogs: Republishing Video Footage. Diseña, (19), Article.4.
Author Biographies

Gabriele Colombo, University of Amsterdam, Faculty of Humanities, Media Studies Department

MA in Communication Design, Politecnico di Milano. Ph.D. in Design, Politecnico di Milano. He is affiliated with DensityDesign, a research lab at the Design Department of Politecnico di Milano, and with the Department of Architecture and Arts of the Università IUAV di Venezia. From March 2019 to June 2021, he has been a researcher at the University of Amsterdam in the European research project ODYCCEUS. At Politecnico di Milano he is also a lecturer in the Communication Design Master’s Degree, where he teaches Digital Methods and Communication Design. His research focuses on the design of visualizations in support of digital social research. He is a founding member of the Visual Methodologies Collective at the Amsterdam University of Applied Sciences and has a long-standing collaboration with the Digital Methods Initiative at the University of Amsterdam. Some of his latest publications include: ‘Dutch Political Instagram. Junk News, Follower Ecologies and Artificial Amplification’ (with C. De Gaetano; in The Politics of Social Media Manipulation; Amsterdam University Press, 2021) and ‘Studying Digital Images in Groups: The Folder of Images (in Advancement in Design Research at Polimi; Franco Angeli, 2019).

Federica Bardelli, University of Amsterdam, Faculty of Humanities, Media Studies Department

Visual designer and visual artist (New Art Technologies), Accademia di Belle Arti di Brera. MA in Communication Design at Politecni­co di Milano. She collaborated with the research department Density Design Lab. She also has taught Communication Design at Politecnico di Milano and worked with IED (Istituto Europeo di Design), the Italian Visual Arts school. From March 2019 to June 2021, she has been a researcher at the University of Amsterdam in the European research project ODYC­CEUS. Her work focuses on new visual languages applied to research, specializing in information and data visualization strategies with digital methods. Currently she works at the intersection of digital and multimedia arts, deriving common languages between research and artistic practices. Some of her latest publications include: ‘Confronting Bias in the Online Representation of Pregnancy’ (with L. Bogers, S. Niederer, and C. De Gaetano; Convergence: The International Journal of Research into New Media Te­chnologies, Vol. 26, Issue 5-6) and ‘Corpi digitali - Un campionario di tecniche di produzione. Digital Bodies - An Inventory of Production Techniques’ (with G. Co­lombo and C. De Gaetano; Progetto Grafico, Issue 31).


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