Development of technological ecosystems for cultural analysis: The case of Expofinder system and art exhibitions

Ortega, Nuria Rodríguez; Rodríguez, Antonio Tomás Bustamante

doi:10.1093/llc/fqy018

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…The fourth data set consists of a sample of actual data we have gathered from the available data belonging to art institutions in Spain in a given period. For that, we used the Expofinder system, which comprises a large data repository of exhibitions held in Spain during the 20th and 21st Centuries (Rodríguez‐Ortega & Cruces‐Rodríguez, 2018). We also ran stress tests by changing the number of connections, exploiting scenarios in multiple order of tens and over millions of connections.…”

Section: Conceptual and Mathematical Formalization Of An Art‐exhibitimentioning

confidence: 99%

Counting is not Enough. Modelling Relevance in Art Exhibition Ecosystems

Ortega¹,

Suárez²,

Gómez³

2020

Curator The Museum Journal

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The authors present a conceptual and mathematical model for an art institution relevance index that quantifies the institution's ability to manage and leverage its loan relationships with other art institutions, art collectors, and curators. The propose that their model innovates on prior methods descriptions of institution relevance based on the depth or size of an institution's collections, by introducing a more complex combination of the institution's ability to manage the type, frequency and range of lending and borrowing practices. Their mixed methods approach is based on combining traditional methods of art history that have relied on subjective accounts of an institution's collection value with a more formalized methodological approach to quantifying what was once a discourse of practice. The show that a limitation in traditional approaches to evaluating institutional impact relied on subjective interpretation and is not scalable and therefore cannot account for the importance of the global art exhibition ecosystems.

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Section: Conceptual and Mathematical Formalization Of An Art‐exhibitimentioning

confidence: 99%

Counting is not Enough. Modelling Relevance in Art Exhibition Ecosystems

Ortega¹,

Suárez²,

Gómez³

2020

Curator The Museum Journal

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“…Discusses some semiotic reflections in painting that can be used for aesthetics and analysis in the field of visual arts, and also the possibility of transforming each semiotic element into a communication tool to increase the understanding of the pictorial form [18]. Rodríguez-Ortega Nuria et al present a technical device, the Expofinder system, that can be used to check the information about art exhibits and point out that the best way to make the methods and mechanisms of management decisions transparent is to enhance digital research paths [19].…”

Section: Introductionmentioning

confidence: 99%

A study on the analysis and understanding of art works based on graph neural networks

2024

Applied Mathematics and Nonlinear Sciences

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With the development of the Internet, many art works are uploaded for people to enjoy. To make it more convenient for viewers to understand and analyze the content of art works. In this paper, we use the GNN graph neural network analysis model to extract the art style, creation period, color expression and other features of the works through the work feature saliency attention module, and classify them using the similarity metric. At the same time, we put forward the GNNMMVisRe model to explore the works from the visual multimodality. The analysis results concluded that the Impressionist style of art works had its heyday in the 18th-19th centuries, when the number of works reached 11,674. The Baroque classicism style reached its heyday in the mid-18th century with 5,921 pieces. In terms of color use, low saturation and low luminance color palettes were selected, with average values of 81.3% and 83.4%, respectively. Using the GNN model to categorize, analyze and study the art works improves the understanding and appreciation of the works. It is also significant for the further development of art.

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Virtual Reality Enables the Dissemination and Preservation of Early Works of Art

Cai

2024

Applied Mathematics and Nonlinear Sciences

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With the rapid development of digitalization and information technology, virtual reality (VR) technology has shown unique potential in disseminating and conserving early works of fine art, changing people’s traditional ways of appreciating and conserving fine art. The article examines the use of virtual reality technology in disseminating and preserving early works of art. The objective is to improve the accessibility and conservation efficiency of art works by using digitization methods. The study uses VR technology to digitize works that are more vivid and easy to disseminate in terms of visual communication, with a 35% increase in audience acceptance, and digital protection effectively reduces the rate of work attrition to about 20%. Through empirical analysis, it has been found that the digital platform that relies on VR technology improves art works’ dissemination effect and protection efficiency. Virtual reality technology is effective at protecting and disseminating early works of fine art, promoting the public’s appreciation and understanding of art, and providing a new method for the digital transformation of fine art works.

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Development of technological ecosystems for cultural analysis: The case of Expofinder system and art exhibitions

Cited by 4 publications

References 2 publications

Counting is not Enough. Modelling Relevance in Art Exhibition Ecosystems

Counting is not Enough. Modelling Relevance in Art Exhibition Ecosystems

A study on the analysis and understanding of art works based on graph neural networks

Virtual Reality Enables the Dissemination and Preservation of Early Works of Art

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