A vocabulary of the aesthetic experience for modern dance archives

This research falls within the field of digital humanities; the arts and information science engage in dialogue. In the last few decades, dance has become a distinct research subject. Dance research needs data. Dance performances remain elusive, and the traces they leave in their wake need to be documented. However, the documentation practices of performance remain unsatisfactory (Couch 1994: 42; Rowat 2005; Desalme 2007: 13; Chaffee 2011: 125), and the specificity of performing arts such as dance is rarely and quite imperfectly taken into account (Le Boeuf 2002; Miller and Le Boeuf 2005).
Dance description in archives needs to be improved because, in this era of massive digital information, the quality of the description impinges on access to the documentation. Description is entangled with access. The better the description, the more efficient the access will be for information seekers. As Nena Couch (2004: 53) once said about dance collections, “If there is no standard language through which a patron may communicate his or her search, the material may be as lost as if the library had never acquired it.” Knowledge extraction seems to offer new opportunities in this regard.
Objectives

The goal of this research is to contribute to the development of information management tools by evaluating the relevance of knowledge extraction in information resources maintenance and development for performing arts such as dance. Aesthetic experience is an essential part of art; a part, however, that is hard to define, let alone describe, in an archives context. Through knowledge extraction, we obtain a vocabulary for describing the aesthetic experience of modern dance in archives. Choreographic works were described using this vocabulary.
Methodology

Many contemporary artists include archival material in their artistic practices (Poinsot 2004; Lemay 2009). Performing arts archives and archivists must be as creative as the art they keep records of (Johnson and Fuller Snyder 1999; Jones, Abbott and Ross 2009: 166; Chaffee 2011: 125). Artists are inspired by archives, and archivists should be inspired by artists in return.
To obtain a vocabulary for representing the aesthetic experience of modern dance, we drew on modern literature and modern art. At the end of the 19th century, French writer Stéphane Mallarmé praised in Autre étude de danse the dazzling performances of Loïe Fuller, a pioneer of modern dance. Mallarmé was an artist and an aesthete (Delfel 1951), a “métaphysicien du ballet” (Levinson 1983). His work is an aesthetic experience in itself, and is related to dance in many ways (Richard 1961; Kristeva 1974: 537; Block 1977: 96; Levinson 1983; Zachmann 2001). Writing about Mallarmé, Mary Ann Caws (1998: 86) says, “[w]hat he gives us is everything that comes after him.” Gayle Zachmann (2001: 188) mentions that “writers and critics […] have highlighted this poet’s contributions to the theoretical underpinnings and reading of modern dance and/or the significance of his writings on dance for his own aesthetic.” His work foreshadowed the spring of modern dance.
We worked from a corpus of texts that includes Mallarmé’s collections Divagations (1897 edition published by Eugène Fasquelle) and Poésies (1899 edition published by Émile Deman) for a total of 119 documents (comprising poetic prose, poem, dialogue), 11,850 types on 70,507 tokens (before lexical filtering) and 7,238 types (after lexical filtering). This corpus has been linked to modern dance for decades, and artists as well as experts in the field of dance studies have drawn on it for inspiration.
The vocabulary was obtained through knowledge extraction methods; to be specific, text mining algorithms combining term extraction and clustering. Documents were grouped into clusters using discriminant features (terms). Clustering is the method of choice for thematic discovery and terminology building (Ibekwe-SanJuan 2007; Forest 2012) and, as such, a bottom-up hierarchical clustering method was used. Once the cluster structure was created, characteristic terms were extracted from each cluster to use as the basis for building a basic structured vocabulary of the aesthetic experience of modern dance.
Results

Two main clusters emerged from the corpus, one of 75 documents, the other of 34 documents. From the 75-document class were drawn three qualifiers, one for each subcluster, of the aesthetic experience of modern dance: petit (small), seul (in solo), beau (beautiful). The antonyms were then drawn directly from the corpus: grandiose (grandiose, great), en couple (in duo) or en troupe (in a body), laid (ugly). From the 34-document class were drawn nine topics related to the aesthetic experience: corps (body), idéal (ideal), nature (nature), nudité (nudity), pureté (purity), rire (laughter), solitude (solitude, loneliness), temps (time), voix (voice). The terms allow the description of what is happening visually onstage beyond the storyline, that is, the visual experience.

Fig. 1: Vocabulary of the aesthetic experience extracted from Mallarmé’s work
We were able to describe choreographic works with the vocabulary. For example, we described Dave St-Pierre’s Un peu de tendresse, bordel de merde! using the following terms: troupe, voix, nudité, rire. St-Pierre’s work is known for theatrical staging, shocking nudity and dark humour.
Exploring Mallarmé’s vocabulary has allowed us to better describe dance performance and to develop minimal yet innovative access points to traditional archives. Thus this initial experiment supports the relevance of knowledge extraction in information resources maintenance and development for performing arts such as dance. Knowledge extraction is one of many solutions for creating a vocabulary for dance archives.
Conclusion

In this research, we delved into the core of an art, literature, to find a vocabulary for describing art. Humanities computing and non-computing approaches are complementary here. The field of digital humanities, recent advances in information technology and opportunities offered by knowledge extraction all contribute to the possibility of exploring innovative solutions to improve the description of dance performance in archives, as well as fostering a better understanding of the art of dance. In this way, information science empowers the arts while the arts empower information science.
References

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