Manufacturas sederas en la Europa ilustrada: el caso de Lyon y Valencia. Posibilidades para su estudio mediante inteligencia artificial
The Spanish court adapted the French illustrated model as a mechanism through which to promote national workshops and generate new manufactures. The creation of the Royal Silk Factory of the Five Guilds of Madrid in Valencia and the creation of the School of Flowers and Ornaments of the Academy of Fine Arts of San Carlos, by Royal Order of October 24, 1778, was intended to train artists in the study of flowers and ornaments for application to textiles. The application of computer media, proposed by the SILKNOW project, to the study of these decorative repertoires allows a new look at the relationship between French models and Valencian translations.
Alba, E., Gaitán,M.,León, A., Sebastián, J. (2021).Manufacturas sederas en la Europa Ilustrada: el caso de Lyon y Valencia. Posibilidades para su estudio mendiante la inteligencia artificial. En: XXIII Congreso Nacional de Historia del Arte. UNIVERSITAS. LAS ARTES ANTE EL TIEMPO, Universidad de Salamanca, España.
Explainable Zero-Shot Topic Extraction Using a Common-Sense Knowledge Graph
Pre-trained word embeddings constitute an essential building block for many NLP systems and applications, notably when labeled data is scarce. However, since they compress word meanings into a fixed-dimensional representation, their use usually lack interpretability beyond a measure of similarity and linear analogies that do not always reflect real-world word relatedness, which can be important for many NLP applications. In this paper, we propose a model which extracts topics from text documents based on the common-sense knowledge available in ConceptNet [Speer et al., 2017] – a semantic concept graph that explicitly encodes real-world relations between words – and without any human supervision. When combining both ConceptNet’s knowledge graph and graph embeddings, our approach outperforms other baselines in the zero-shot setting, while generating a human-understandable explanation for its predictions through the knowledge graph. We study the importance of some modeling choices and criteria for designing the model, and we demonstrate that it can be used to label data for a supervised classifier to achieve an even better performance without relying on any humanly-annotated training data. We publish the code of our approach at https://github.com/D2KLab/ZeSTE and we provide a user friendly demo at https://zeste.tools.eurecom.fr/.
Harrando, I, Troncy, R.(2021). Explainable Zero-Shot Topic Extraction Using a Common-Sense Knowledge Graph. In 3rd Conference on Language, Data and Knowledge (LDK).
TOMODAPI: A Topic Modeling API to Train, Use and Compare Topic Models
From LDA to neural models, different topic modeling approaches have been proposed in the literature. However, their suitability and performance is not easy to compare, particularly when the algorithms are being used in the wild on heterogeneous datasets. In this paper, we introduce ToModAPI (TOpic MOdeling API), a wrapper library to easily train, evaluate and infer using different topic modeling algorithms through a unified interface. The library is extensible and can be used in Python environments or through a Web API.
Préserver et diffuser le patrimoine textile européen grâce aux technologies numériques. La réutilisation des données patrimoniales par le projet SILKNOW
Le projet SILKNOW. Web sémantique et valorisation du patrimoine de la soie en Europe
Silk Road Museums: Design of Inclusive Heritage and Cross-Cultural Education
This work is the result of a study on the characteristics that define some of the museums created on the Silk Road. The approach to these museums has focused especially on the observation of the educational and heritage aspects that define these institutions. Since 1988, numerous actions related to the Silk Road have been promoted by UNESCO. This old trade route has now become a route of dialogue between cultures. Each museum studied is characterized by promoting local and national issues that define it. Educational issues stand out, since the tradition of silk production is very important in each place. Another aspect observed is that heritage issues manage to strengthen the characteristic features of each community. I have interviewed those responsible and personally observed their facilities and collections. Each museum has chosen to highlight local differential factors, enhancing the aesthetic arguments of cultural identity. Finally, I examine the specific case of the Valencia Silk Museum, the most recent creation museum but also the oldest institution. In the conclusions, I highlight the importance of education in most of these institutions.
Virtual Loom: a tool for the interactive 3D representation of historical fabrics
3D modelling of man-made objects is widely used in the cultural heritage sector, among others. It is relevant for its documentation, dissemination and preservation. Related to historical fabrics, weaves and weaving techniques are still mostly represented in forms of 2D graphics and textual descriptions. However, complex geometries are difficult to represent in such forms, hindering the way this legacy is transmitted to new generations. In this paper, we present the design and implementation of SILKNOW’s Virtual Loom, an interactive tool aimed to document, preserve and represent in interactive 3D forms historical weaves and weaving techniques of silk fabrics, dating from the 15th to the 19th centuries. To that end, our tool only requires an image of a historical fabric. Departing from this image, the tool automatically subtracts the design, and allows the user to apply different weaves and weaving techniques. In its current version, the tool embeds five traditional weaving techniques, 39 weaves and six types of yarns, which have been defined thanks to close collaboration of experts in computer graphics, art history and historical fabrics. Additionally, users can change the color of yarns and produce different 3D representations for a given fabric, which are interactive in real time. In this paper, we bring the details of the design and implementation of this tool, focusing on the input data, the strategy to process images, the 3D modelling of yarns, the definition of weaves and weaving techniques and the graphical user interface. In the results section, we show some examples of image analysis in order to subtract the design of historical fabrics, and then we provide 3D representations for all the considered weaving techniques, combining different types of yarns. Keywords 3D modelling . Fabrics . Designs . Interaction . Image analysis
Multi-Purpose Ontology-Based Visualization of Spatio-Temporal Data: A Case Study on Silk Heritage
Due to the increasing use of data analytics, information visualization is getting more and more important. However, as data get more complex, so does visualization, often leading to ad hoc and cumbersome solutions. A recent alternative is the use of the so-called knowledge-assisted visualization tools. In this paper, we present STMaps (Spatio-Temporal Maps), a multipurpose knowledge-assisted ontology-based visualization tool of spatio-temporal data. STMaps has been (originally) designed to show, by means of an interactive map, the content of the SILKNOW project, a European research project on silk heritage. It is entirely based on ontology support, as it gets the source data from an ontology and uses also another ontology to define how data should be visualized. STMaps provides some unique features. First, it is a multi-platform application. It can work embedded in an HTML page and can also work as a standalone application over several computer architectures. Second, it can be used for multiple purposes by just changing its configuration files and/or the ontologies on which it works. As STMaps relies on visualizing spatio-temporal data provided by an ontology, the tool could be used to visualize the results of any domain (in other cultural and non-cultural contexts), provided that its datasets contain spatio-temporal information. The visualization mechanisms can also be changed by changing the visualization ontology. Third, it provides different solutions to show spatio-temporal data, and also deals with uncertain and missing information. STMaps has been tested to browse silk-related objects, discovering some interesting relationships between different objects, showing the versatility and power of the different visualization tools proposed in this paper. To the best of our knowledge, this is also the first ontology-based visualization tool applied to silk-related heritage.
El hilo de la historia: del patrimonio mueble al intangible. Rescatando el patrimonio textil sedero
El patrimonio de la seda constituye un tipo de patrimonio patrimonio integral, es decir, en él que se pueden encontrar elementos tangibles e intangibles además de ser un patrimonio vivo fuertemente conectado con su comunidad. Es además un caso paradigmático, ya que tiene asociados elementos inmateriales que van desde literatura, a la recogida de la morera, o las técnicas tradicionales de tejido. Además, el desarrollo de su actividad ha dejado una impronta en diversas ciudades con monumentos e incluso marca el urbanismo de las mismas. Es un patrimonio vivo presente en diversas comunidades y constituye un elemento de creatividad presente en los diseños más contemporáneos de la moda actual. En este artículo se abordan los principales resultados del proyecto SILKNOW, financiado por la Unión Europea en el marco de Horizonte 2020 y se da valor a este patrimonio proponiendo la elaboración de un plan nacional que garantizará la salvaguarda de técnicas y saberes ligados a las técnicas de tejido, a través de la memoria oral y los procesos de conservación, documentación y registro. Buscando la comprensión de esas técnicas a través de la tecnología para hacer ese conocimiento accesible, al tiempo que se potencia el conocimiento de la seda.
Pagán, E.;,Gaitán, M., León, A., Sebastián, J. (2021). El hilo de la historia: del patrimonio mueble al intangible. Rescatando el patrimonio textil sedero. In A. Lerma, V. López-Menchero, A. Maldonado, Actas del I Simposio anual de Patrimonio Natural y Cultural ICOMOS España,València, Editorial Universitat Politècnica de València, https://doi.org/10.4995/icomos2019.2020.12513
From Silk to Digital Technologies: A Gateway to New Opportunities for Creative Industries, Traditional Crafts and Designers. The SILKNOW Case.
Nowadays, cultural heritage is more than ever linked to the present. It links us to our cultural past through the conscious act of preserving and bequeathing to future generations, turning society into its custodian. The appreciation of cultural heritage happens not only because of its communicative power, but also because of its economic power, through sustainable development and the promotion of creative industries. This paper presents SILKNOW, an EU-H2002 funded project and its application to cultural heritage, as well as to creative industries and design innovation. To this end, it presents the use of image recognition tools applied to cultural heritage, through the interoperability of data in the open-access registers of silk museums and its presentation, analysis and creative process carried out by the design students of EASD Valencia as a case study, in the branches of jewellery and fashion project, inspired by the heritage of silk.
From Historical Silk Fabrics to Their Interactive Virtual Represent
The documentation, dissemination, and enhancement of Cultural Heritage is of great relevance. To that end, technological tools and interactive solutions (e.g., 3D models) have become increasingly popular. Historical silk fabrics are nearly flat objects, very fragile and with complex internal geometries, related to different weaving techniques and types of yarns. These characteristics make it difficult to properly document them, at the yarn level, with current technologies. In this paper, we bring a new methodology to virtually represent such heritage and produce 3D printouts, also making it highly interactive through the tool Virtual Loom. Our work involves sustainability from different perspectives: (1) The traditional production of silk fabrics respects the environment; (2) Virtual Loom allows the studying of silk heritage while avoiding their degradation; (3) Virtual Loom allows creative industries to save money and materials; (4) current research on bioplastics for 3D printing contributes to environmental sustainability; (5) edutainment and gaming can also benefit from Virtual Loom, avoiding the need to acquire the original objects and enhancing creativity. The presented work has been carried out within the scope of the SILKNOW project to show some results and discuss the sustainability issues, from the production of traditional silk fabrics, to their dissemination by means of Virtual Loom and 3D printed shapes.
Extracting structured metadata from multilingual textual descriptions in the domain of silk heritage
In this paper, we present a methodology for extracting structured metadata from museum artifacts in the field of silk heritage. The main challenge was to train on a relatively small and noisy data corpus with highly imbalanced class distribution by utilizing a variety of machine learning techniques. We have evaluated the proposed approach on real-world data from five museums, two English, two Spanish, and one French. The experimental results show that in our setting using traditional machine learning algorithms such as Support Vector Machines gives comparable and in some cases better results than multilingual deep learning algorithms. The study presents an effective approach for categorization of text described artifacts in a niche domain with scarce data resources.
Assessing the Semantic Similarity of Images of Silk Fabrics Using Conventional Neural Networks
This paper proposes several methods for training a Convolutional Neural Network (CNN) for learning the similarity betweenimages of silk fabrics based on multiple semantic properties of the fabrics. In the context of the EU H2020 project SILKNOW(http://silknow.eu/), two variants of training were developed, one based on a Siamese CNN and one based on a triplet architecture.We propose different definitions of similarity and different loss functions for both training strategies, some of them also allowingthe use of incomplete information about the training data. We assess the quality of the trained model by using the learned imagefeatures in a k-NN classification. We achieve overall accuracies of 93-95% and average F1-scores of 87-92%.
Virtual Loom, from Historical Fabrics to Interactive 3D Models
In the field of Cultural Heritage, the documentation of historical fabrics and their weaving techniques, usually lack of a 3D representation. In many cases, it is enough to document such objects in 2D graphics or textual descriptions. However, there are geometries and details of greater complexity that require more complete models to understand the techniques and be able to preserve them over time. In this area, the Virtual Loom tool has been created within the SILKNOW European Project. The demo that we present allows us to show weaving techniques from the 15th to the 19th century in a 3D representation and later we can explore it in different ways. The tool includes a variety of historical weaves, weaving techniques and threads. All this has been created based on the knowledge of experts in historical fabrics, art history and computer graphics.
Applying Axial Symmetries to Historical Silk Fabrics: SILKNOW’s Virtual Loom
Symmetry is part of textile art in patterns and motifs that decorate fabrics, which are made by the interlacement of warp and wefts. Moreover, the 3D representation of fabrics have already been studied by some authors; however, they have not specifically dealt with preserving historical weaving techniques. In this paper, we present the SILKNOW’s Virtual Loom, a tool intended to document, preserve and reproduce silk historical weaving techniques from the 15th to the 19th centuries. We focus on the symmetry function and its contribution to art history, textile conservation, and modern design. We analyzed 2028 records from Garin 1820 datasets—a historical industry that still weaves with these techniques—and we reconstructed some historical designs that presented different types of defects. For those images (including fabrics and drawings) that had a symmetrical axis, we applied the symmetry functionality allowing to reconstruct missing parts. Thanks to these results, we were able to verify the usefulness of the Virtual Loom for conservation, analysis and new interpretative advantages, thanks to symmetry analysis applied to historical fabrics.
Los catálogos de museo, una gran oportunidad para el conocimiento abierto… si se abren
El patrimonio histórico tiene especial necesidad de un tipo de repositorios abiertos: los catálogos digitales de museos y colecciones. La riqueza de información que atesoran estos recursos queda en muchos casos limitada a especialistas, pero su adecuada difusión mediante repositorios y agregadores digitales puede ayudar a aumentar sustancialmente su visibilidad entre distintos tipos de audiencias. Basándose en los aprendizajes de SILKNOW, un proyecto europeo dedicado a la puesta en valor del patrimonio sedero mediante herramientas digitales, este texto aboga por una mayor implicación de los museos y las instituciones del patrimonio en la difusión del conocimiento abierto.
SILKNOW, tejiendo el pasado hacia el futuro
La historia europea está tejida en seda. Aunque se suele asociar la Ruta de la Seda a sus orígenes asiáticos, sus ramificaciones europeas fueron fundamentales para la construcción de la Europa actual gracias a los numerosos intercambios comerciales derivados de dichas rutas. La herencia de estas rutas ha dejado un legado incalculable: un ejemplo único de patrimonio donde la memoria, la identidad, la creatividad y el conocimiento confluyen en una única pieza. Sin embargo, a pesar de su enorme importancia, este patrimonio no ha sido lo suficientemente
valorado, esto aunado a su propia naturaleza física lo hace más frágil frente a otro tipo de elementos culturales como pinturas o esculturas. Para hacer frente a estos retos, nace SILKNOW, un proyecto de investigación financiado con fondos europeos, pretende mejorar la comprensión, la conservación y la difusión del patrimonio de seda europeo del siglo xv al siglo xix, basado en registros de catálogos existentes.
Understanding and preserving the European Silk Heritage: producing accessible, interoperable and reusable Cultural Heritage data with the SILKNOW ontology
Silk played an important role in European history, mostly along the Western SilkRoad’s network of production and market centres. Silk, however, has become a se-riously endangered heritage. Although many European specialized museums are de-voted to its preservation, they usually lack size and resources to establish networks orconnections with other collections. The H2020 SILKNOW project (Silk her-itage in the Knowledge Society: from punched card to Big Data, DeepLearning and visual/tangible simulations)(http://silknow.org/) aimsto produce an intelligent computational system in order to improve our understandingof European silk heritage
Facilitating the Exchange of Perspectives between Heritage Professionals and Researchers
Reuse cases presented by arts and humanities scholars : The SILKNOW project
Producing accessible, interoperable and reusable Cultural Heritage data with the SILKNOW ontology to preserve the European Silk Heritage
SILKNOW. Designing a Thesaurus about Historical Silk for Small and Medium-Sized Textile Museums.
The cultural heritage domain in general, and the silk textile in particular, is characterized by large, rich and heterogenous data sets. Silk heritage vocabulary comes from multiple sources that had been mixed up across time and space. This has led to the use of different terminology in specialized organizations in order to describe their artefacts. This makes data interoperability between independent catalogues very difficult. Moreover, the interaction level of existing resources is low, complex queries are not possible and results are poorly shown. In this regard, a recent EU-funded research project titled SILKNOW is building a multilingual thesaurus related to silk textiles. It is being carried out by experts in textile terminology and art historians, and computationally implemented by experts in text mining and multi-/cross-linguality and semantic extraction from text. This paper presents the rationale behind the realization of this thesaurus.
Spanish Religious Textiles from the 18th and the 19th centuries: the Garín case
Clothes and textiles make up a very relevant part or religious cultural heritage. This paper presents a selection of liturgical textiles from the 18thand 19thcenturies. They were created by Garín, a Spanish factory still active today. Thedesigns and weaving techniques employed in them have provided the starting point for a research project, SILKNOW, in operation between 2018 and 2021. It aims to apply cutting-edge computing technologies to textile heritage, including the religious and liturgical, and thus establish new historical and artistic connections
Technological tools for the conservation of silk heritage: Improving the conservation of European Religious Textile Cultural Heritage
This paper presents the interdisciplinary H2020 SILKNOW project coordinated by the Universitat de València with researchers from the ICT and SSH fields. SILKNOW is a three-year project funded by the EU’s Horizon 2020 Programme under the two-stage call SC6-CULT-COOP-09 “European cultural heritage, access and analysis for a richer interpretation of the past”. The consortium has a total of nine partners from six different European countries (Spain, France, Germany, Slovenia, Poland and Italy). There are a total of three universities, two SMEs, one international institution, and three research institutes. In this paper, we introduce SILKNOW which has as a goal to promote, conserve and disseminate silk textiles; secondly, we introduce a set of interactive tools related to the project that will especially enhance conservation of this heritage.
Multi-task deep learning with incomplete training samples for the image-based prediction of variables describing silk fabrics
This paper presents a method for the classification of images of silk fabrics with the aim to predict properties such as the place and time of origin and the production technique. The proposed method was developed in the context of the EU project SILKNOW (http://silknow.eu/). In the context of classification, we address the problem of limited as well as not fully labelled data and investigate the connection between the distinct variables. A pre-trained Convolutional Neural Network (CNN) is used for the feature extraction and a classification network realizing Multi-task learning (MTL) is trained based on these features. The training procedure is adapted to enable the consideration of images that do not have a label for all tasks. Additionally, MTL with fully labelled training data is investigated for the classification of silk fabrics. The impact of both MTL approaches is compared to single-task learning based on two different class structures. We achieve overall accuracies of 92–95 % and average F1-scores of 88–90 % in our best experiments.
Towards the Preservation and Dissemination of Historical Silk Weaving Techniques in the Digital Era
The aim of this paper is to propose a mathematical modelling of historical weaving techniques by means of matrices in order to be easily mapped to a virtual 3D representation. The work focuses on historical silk textiles, ranging from the 15th to the 19th centuries. We also propose a computer vision-based strategy to extract relevant information from digital imagery, by considering different types of images (textiles, technical drawings, and macro images).
SILKNOW – Multilingual Text Analysis for Silk Heritage
We present results of collaborative work bringing together semantic technologies, machine learning and cultural heritage to enable advanced search and visualization of textual descriptions of museum artifacts related to silk fabrics. Proposed is a multilingual txt analysis approach where the developed domain-specific multilingual thesaurus and domain-specific ontology are utilized in data representation and analysis. In addition, a general multilingual semantic annotation tool Wikifier is applied on thesaurus definitions and descriptions of silk-related museum artefacts. The validation on real-world data of several museums confirms suitability of the developed thesaurus and the ontology.
A Proposal to Model Ancient Silk Weaving Techniques and Extracting Information from Digital Imagery – Ongoing Results of the SILKNOW Project
Three dimensional (3D) virtual representations of the internal structure of textiles are of interest for a variety of purposes related to fashion, industry, education or other areas. The modeling of ancient weaving techniques relevant to understand and preserve our heritage, both tangible and intangible. However, ancient techniques cannot be reproduced with standard approaches, which usually are aligned with the characteristics of modern, mechanical looms. The aim of this paper is to propose mathematical modeling of ancient weaving techniques by means of matrices in order to be easily mapped to a virtual 3Drepresentation. The work focuses on ancient silk textiles, ranging from the 15thto the 19th centuries. We also propose a computer vision-based strategy to extract relevant information from digital imagery, by considering different types of images (textiles, technical drawings, and macro images.
SILKNOWViz: Spatio-temporal data ontology viewer
Interactive visualization of spatio-temporal data is a very active area that has experienced remarkable advances in the last decade. This is due to the emergence of fields of research such as big data and advances in hardware that allow better analysis of information. This article describes the methodology followed and the design of an open source tool, which in addition to interactively visualizing spatio-temporal data that are represented in an ontology, allows the definition of what to visualize and how to do it. The tool allows selecting, filtering and visualizing in a graphical way the entities of the ontology with spatiotemporal data, as well as the instances related to them. The graphical elements used to display the information are specified on the same ontology, extending the VISO graphic ontology, used for mapping concepts to graphics objects with RDFS/OWL Visualization Language (RVL). This extension contemplates the data visualization on rich real-time 3D environments, allowing different modes of visualization according to the level of detail of the scene, while also emphasizing the treatment of spatio-temporal data, very often used in cultural heritage models. This visualization tool involves simple visualization scenarios and high interaction environments that allow complex comparative analysis. It combines traditional solutions, like hypercube or time-animations with innovative data selection methods.
Deep Learning zur Analyse von Bildern von Seidenstoffen für Anwendungen im Kontext der Bewahrung des kulturellen Erbes
Der vorliegende Beitrag befasst sich mit der Klassifikation von Bildern mittels Deep Learning. Exemplarisch wird hier die bildbasierte Prädiktion der Entstehungs-epoche von Seidenstoffen und Fertigungsskizzen betrachtet. An diesem Beispiel wird die Problemstellung von nicht eindeutig definierten Klassen sowie uneindeutigen Trainingsbei-spielen aufgegriffen und ein Lösungsansatz vorgestellt. Dieser basiert auf einer erweiterten Verlustfunktion, mit welcher die uneindeutigen Trainingsbeispiele während des Trainings genutzt werden können. Hierzu werden während der Trainingsphase übergreifende Klassen definiert. Die durchgeführten Experimente zeigen, dass hiermit die Genauigkeit der Klassi-fikation ohne die übergreifenden Klassen verbessert werden kann. Da der exemplarische Datensatz relativ wenig Daten umfasst wird ein vortrainiertes Convolutional Neural Network verwendet und eine Augmentierung der Daten durchgeführt. Der Einfluss der Aug-mentierung sowie der entwickelten Verlustfunktion wird in einer Kreuzvalidierung evaluiert.
Innovación social en patrimonio cultural y museos de la seda en Europa: una mirada conectada con las industrias creativas
Esta contribución se enmarca dentro del proyecto H2020 Silknow que coordina la Universitat de València a través de un equipo multidisplicinar conformado por investigadores de las TIC y del ámbito de las humanidades y de las ciencias sociales. Hoy el concepto de patrimonio cultural está más que nunca ligado al presente, como punto de partida que nos vincula con nuestro pasado cultural a través del acto consciente de preservar y legar a las generaciones futuras, convirtiendo a la sociedad en custodia. Este acto emerge con la ambición de permanecer en un mundo cada vez más cambiante y mutable, pero en medio de esta corriente surge cada vez con más presencia la apreciación del patrimonio no solo a través de su poder comunicativo que nos liga con nuestro pasado, sino también con su potencial como propiciador de economías innovadoras, a través del desarrollo sostenible y el impulso de las industrias creativas. Centrado en el patrimonio de la seda, se analiza este pasado desde el presente y como motor de desarrollo futuro.
Alba, E. ; Pitarch, M.D; Sebastian, J.; Arnandis, R.; Portalés, C.; Gaitán, M. (2019). Innovación social en patrimonio cultural y museos de la seda en Europa: una mirada conectada con las industrias creativas. In. Boix, R. International Conference on Regional Science. Hacia un modelo económico más social y sostenible. Asociación Española de Ciencia Regional, Valencia.
Interactive Tools for the Preservation, Dissemination and Study of Silk Heritage—An Introduction to the SILKNOW Project
Silk was a major factor for progress in Europe, mostly along the Western Silk Road’s network of production and market centers. The silk trade also allowed for the exchange of ideas and innovations, having impacts at economic, technical, functional, cultural and symbolic levels. However, silk has today become a seriously endangered heritage. Although many European specialized museums are devoted to its preservation, they usually lack the size and resources to take advantage of state-of-the-art digital technologies. The aim of this paper is twofold; firstly, we introduce SILKNOW, an interdisciplinary project that has been recently funded by the H2020 Programme of the European Union in order to preserve and promote the heritage of silk textiles; secondly, we introduce a set of interactive tools related to the project.
Pintores y ornatos para los Tejidos de seda en la Ilustración y la Academia valenciana de Bellas Artes
Durante el siglo XVIII, Valencia se convirtió en el principal centro manufacturero español de tejidos de seda. Con el fin de proporcionar modelos originales para los mismos se creó en el seno de la Academia de Bellas Artes de San Carlos la “Escuela de Flores, Ornatos y otros diseños adecuados para Tejidos” en 1784. El presente artículo atiende a sus precedentes, sus principales protagonistas y analiza su funcionamiento, además de considerar la relación que mantuvo a lo largo de su trayectoria con la industria de la seda.