10th Berlin Biennale: Mapping an Exhibition Network  

by Prof. Dr. Eleonora Vratskidou and Dr. Anne Luther

Introduction

The Berlin Biennale is a contemporary art exhibition first organized by Klaus Biesenbach (Director of MoMA PS1 in New York), Nancy Spector (Chief Curator at the Solomon R. Guggenheim Museum in New York) and Hans Ulrich-Obrist (Artistic Director at the Serpentine Galleries in London) in 1998. The creation of the Berlin Biennale in the mid-1990s stands at the outset of a significant increase in number and geographical dispersal of such large-scale perennial exhibitions ─a phenomenon that fully partakes in the global flows of objects and people, the expansion of neoliberal economic structures, urban development, social engineering, and city branding. No more than ten in number around the early 1990s, biennales are today more than a hundred to take place more or less regularly around the world, [1] becoming the standard format for producing and displaying contemporary art.

With every Biennale a specific network of actors takes shape, involving curatorial and research teams, artists and their galleries, funding bodies, artistic collaborators and other public and private support bodies, institutions and their curators that are invited for a one time facilitation of the exhibition, graphic designers and media experts, technicians, transporters and installation teams, art writers and art historians, mediators and art educators, invigilators, etc. An inquiry into the network of actors that biennales bring together is the foundation to understanding how these exhibitions are made.

The information that is released about the number and kind of actors involved in the production of each show is a conscious decision communicated in press material, their website and publications. This decision is related to the labor politics and work ethos to which each biennial subscribes as well as to the self-image it seeks to broadcast.

The proliferation of biennials has not yet been thoroughly examined. A number of studies, based often on individual cases, focus mainly on curatorial practices and discourses ─or the discrepancies between discourses and practices─, but more empirical approaches regarding the involved actors, issues of connectivity and work ethics are still rare. The acknowledgement of internationally active artistic and curatorial networks is certainly a given, but their actual study is not yet systematically pursued. This inquiry seeks to contribute in this direction, based on the example of the 10th  Berlin Biennale, that took place in summer 2018 (June 9 – September 9, 2018) .

Under the title We don’t need another hero, the last edition of the show was curated by Johannesburg-based curator, artist and art educator Gabi Ngcobo. Upon her appointment by the international selection committee in November 2016, she invited four fellow curators, with whom she had collaborated individually in the past  to join her in the direction of the show: Nomaduma Rosa Masilela, Serubiri Moses, Thiago de Paula Souza, and Yvette Mutumba. The discourse of the exhibition put the emphasis on collectivity, collaboration and collective authorship and promoted dialogue as generative force. To this ethos testify most prominently the “curatorial conversations” published in the catalogue. Instead of an extended curatorial statement, the conversations serve to illustrate the reasoning mode and the collaborative generation of ideas at work among the members of the curatorial team.[2]  Similar attitudes were adopted among the artists: they were manifest in the production of the exhibited works, such as the programmatic installation piece by Dineo Seshee Bopape at the KW, which hosted works by three other artists (Jabu Arnell, Lachell Workman, and Robert Rhee), an initiative which was qualified by the curatorial discourse as “a gesture of hospitality and collaboration”. [3]

Interested in the collaborative ethos promoted by the show, we decided to pursue an investigation into the specific information made visible about the makers of the 10th Berlin Biennale, as an example of communication of a specific biennale network. The article introduces a network visualization based on the information on the collaborating actors mentioned in the website of the Berlin Biennale 10. We collected and structured data from the website in a format that allows to develop a node-link network of the various actors and their relationships. The following will introduce the data collection, node types and link relationships for the exploration of the interactive network graph of the Berlin Biennale 10.

Data Collection

The interactive network graph that we created maps out the relationships between the actors that made the 10th Berlin Biennale based on the information drawn from their website http://www.berlinbiennale.de. More specifically, we collected and manually structured the data that is displayed on the introduction pages of every participating artist. These pages contain the following elements: artist name, image of presented work or installation view and image credit, text to each participating artist and their exhibited work, name of the author, exhibition venue, list of works with or without courtesy and credits of various roles.[4]The artists’ pages communicate specific information on funding, support and art production regarding the making of the 10th Berlin Biennale that are by default linked to an artist’s name. In the structuring of our data, we considered this communication logic and defined the various node types (listed below) according to their corresponding artist.

The information provided on the website concerns the production and funding of the works and projects presented by each artist; the representation of the artists (galleries/courtesy) as well as the production of curatorial discourse (texts), involving 26 invited authors along with the members of the curatorial team.

We focused on artists’ pages, since this is an important point of contact between artistic and curatorial agency. While in the texts, members of the curatorial team and invited authors sought to place/situate the contribution of each participating artist within the larger curatorial project, artists were themselves responsible for the information communicated regarding those implicated in the making of the presented works, their various collaborators and supporters. The amount of contributors in the actual production of the works surely depends on their nature and media: a drawing is in this respect less demanding than an installation, a performance or a video. Diverging attitudes regarding crediting among the artists become most evident in the case of film and video works, which are per se collective enterprises. To cite only one example, Cynthia Marcelle names 48 collaborators (director, camera, steadicam, camera assistant and grip, production and production assistants, sound design, music research, editing, stills, musicians, drivers, etc.) involved in the production of her video Cruzada (2010, 8’35’’), while no collaborators are named for Emma Wolukau-Wanambwa’s video Promised Lands (2015, 22’). (We are not able to account for such differences at this point.)

The Βerlin Biennale is organized by KUNST-WERKE BERLIN e.V. and funded, since its 4th iteration in 2006, by the Kulturstiftung des Bundes (German Federal Cultural Foundation), the amount allotted to the show being augmented from 2,5 to 3 million euro starting with the last iteration.[5] This funding agency will not appear in our graph, since it is a given for every iteration of the exhibition, while what is of interest for us here is the way each curator and/or curatorial team appropriates the institution of the Berlin Biennale anew and shapes a network of actors depending on their own position and connectivity within the art world. Equally not considered are other public and private sponsors mentioned in the catalogue, such as the Berlin’s Senate Department for Culture and Europe or the car industry BMW (as Corporate Partner), since no information is disclosed regarding the concrete way they are connected to the various participating artists and exhibition related projects.

Data structure

The data from the website was structured in the specific format typical for the construction of node-link networks, as required by the digital tool Graph Commons. A node is an actor, entity or object within a network that is connected to other nodes with a specific link, which is called an ‘edge’. The ‘node type’ describes the actor in the network such as art institution or gallery, while the ‘edge type’ describes the relationship between actors. In order to illustrate how this database was structured, let us take as an example the participation of Basir Mahmood. In the credits on the artist page (http://www.berlinbiennale.de/artists/b/basir-mahmood), we find the following information: “Commissioned and produced by Sharjah Art Foundation”. Sharjah Art Foundation is the name of a node with the node type “Institution” that is linked to the node name Basir Mahmood with the node type “Person” by the edge (or relationship) “Commissioned and produced”.

While for the names of nodes and edges we closely followed the vocabulary adopted by the biennale for communicating the roles and relations involved in the making of the exhibition, we proceeded to the necessary classification of nodes and edges into types. We assembled all descriptions in two following node types:

Institutions include:

  • Art institutions: Primary function: supporting, hosting (pe. residency), conserving (pe. museum), archiving (pe. museum) and exhibiting art. Art schools have also been categorized under art institutions.
  • Cultural Institution: Largely educational function – active beyond the field of fine and performing arts. Many of them are involved in international cultural relations/exchange.
  • Political Institution: Its primary function is in the political realm.
  • Enterprise: Its primary function is in the economic realm.
  • Gallery: Its primary function is selling art.
  • Collection: Everything that has been qualified as such by the Berlin Biennale

Persons include:

  • Artists that are participating as such in the Berlin Biennale 10.
  • Curators
  • Authors of artists texts in the catalogue and for the website.
  • Persons active in the production or support of exhibited work.

Regarding the edges, we grouped the various descriptions found in the website into four big categories: Commission, production and support; Courtesy; Art Production and Text. These meta-descriptions are indicated by color coding in the network graph. Concretely, we assembled the following phrasings under:

Commission and production and support: : 15 Commissioned and coproduced; 12 Commissioned and produced; 1 Produced; 3 Commissioned; 6 Coproduced; 4 Coproducer; 1 Produced in partnership; 1 Produced with the support; 1 Existing works as well as commissioned works produced; 1 Existing works as well as commissioned works coproduced; 54 With the support; 3 In-kind support; 1 Funded; 13 Thanks.

Courtesy: 75 Courtesy; 14 In (Collection).

Text: 45 Text.

Art Production: Production, 3 Producer, 1 Production, 5 Production Assistants, 6 Production Team, 2 Artistic Production. Performers:24 Featuring, 7 Performed, 1 Choreography, 16 Musicians, 30 Activator. Director/Camera:1 Director, 2 Assistant Directors, 2 Cinematographer, 3 Camera, 3 Camera Assistant, 1 Camera Assistant and Grip, 1 Grip, 1 Steadicam. Screenplay:2 Screenplay, 1 Screenwriters, 1 Script, Direction, and Editing, 1 Line Producer. Editing: 2 Editor, 1 Editing, 1 Video Editing (Coloring), 1 Video Editing (Editing). Music/Sound: 5 Sound, 1 Sound Assistant, 1 Sound Design, 1 Sound Designer, 1 Sound engineer, 1 Music, 1 Music Director, 1 Music Research, 1 Spatialization and mix by, 16 Musicians. Light/Photography: 7 Light, 1 Film and Lighting Technician, 4 Director of Photography, 3 Stills. Costumes, make-up, design: 1 Costumes, 1 Costumes stitched, 1 Costume Designer, 1 Make-up, 1 Project Design Collaborator, 1 Set Design, 1 Backdrops painted by. Varia: 3 In cooperation, 3 Including works, 2 Collaborator: Vibratory installation, 1 Collaborators: Fluffy sculptures, 1 Printed and published, 1 Poster, 1 Driver, 1 Water Truck Operator, 1 Assistant, 1 Project Liaison.

We chose to adopt the ‘original’ description that the Berlin Biennale displays as information about the making of the exhibition: every link displays the wording that is also displayed on the website of the Berlin Biennale. The node types that we display in the graph use descriptions that are the closest to what we could find on the website. We did not use our own interpretations of roles in the art world but rather chose to display descriptions from the Berlin Biennale website. These descriptions of art world roles are displayed in a network view.

The visual representation of the network of actors is displayed in a Force Directed Graph, which is a visually pleasing method. The nodes are forced in a direction that gives space to comprehend edges and nodes in distinguishable ways. Nodes with a higher degree of centrality, which is determined by the number of edges connected to a node, are displayed closer to the center of the network.

Disconnected nodes are drawn to the outside. In Graph Commons, it is possible to view the Degree Centrality of each node displayed in a chart by in-degree centrality, out-degree centrality and betweenness centrality. In-degree centrality shows the number of edges that are directed towards a node and out-degree centrality shows the number of edges that are directed from a node. In this particular graph, analyzing the nodes by in-degree centrality, we can therefore see how many actors were involved with an exhibiting artist as co-producers, art production or authors (to name but a few). Analyzing the nodes by out-degree centrality, we can ask the network graph questions about the funding bodies who supported the most artists or how many galleries had more than one represented artist in the exhibition.

Clusters are nodes that are connected with each other with a higher number of edges. The betweenness centrality shows nodes that connect clusters with each other. Graph Commons allows the user to view these clusters in detail in the analysis tab.

The visualization of actors of the 10th Berlin Biennale is a platform to ask further questions and develop a broader inquiry into the networking, politics and funding of the exhibition and international biennale structures more generally. The authors will develop a deepened investigation and publish the results in peer-reviewed journals with a focus on art and technology.

 

Notes

[1] Panos Kompatsiaris, The Politics of Contemporary Arts Biennials: Spectacles of Critique, Theory and Art, New York and London, Routledge, 2016, p. 9.

[2] Gabi Ngcobo, Nomaduma Rosa Masilela, Serubiri Moses, Thiago de Paula Souza, and Yvette Mutumba, “Curatorial Conversations”, in: 10th Berlin Biennale for Contemporary Art, We don’t need another hero, exhibition catalogue, p. 31-41  (English part).

[3] Portia Μalatjie, “Dineo Seshee Bopape”, in: 10th Berlin Biennale for Contemporary Art, We don’t need another hero, exhibition catalogue, 2018, p. 62 (English part).

[4] This information is also provided in the catalogue, though not structured in the same way: in the main body of the catalogue one finds the texts on each artist –the website contains only short versions of the printed texts–, but the list of works by artist and information on courtesy, funding and production are given at the end of the essays section. Out of convenience, we used the website as our main source where all relevant information is grouped together.

[5] Gabrielle Horn, “Introduction”, in: 10th Berlin Biennale for Contemporary Art, We don’t need another hero, exhibition catalogue, p. 15 (English part).

 

‘Activating Museums’ Data for Research, Scholarship, and Public Engagement

A vast number of Digital Humanities projects have emerged in the last few decades that digitized museum collections, archives, and libraries and made new data types and sources possible. Interdisciplinary labs such as the medialab at Sciences Po focus on the development of new tools that cater to methods and research in the Humanities. They especially address the regressive gap that has become evident in the current tools needed to analyze, comprehend, and present these new digital sources. Provenance and translocation of cultural assets and the social, cultural, and economic mechanisms underlying the circulation of art is an emerging field of scholarship encompassing all humanities disciplines.

‘With the migration of cultural materials into networked environments, questions regarding the production, availability, validity, and stewardship of these materials present new challenges and opportunities for humanists in contrast with most traditional forms of scholarship, digital approaches are conspicuously collaborative and generative, even as they remain grounded in the traditions of humanistic inquiry, this changes the culture of humanities work as well as the questions  that can be asked of the materials and objects that comprise the humanistic corpus.’

Internationally researchers concerned with the ‘social, cultural, and economic mechanisms underlying the circulation of art’ work with object-based databases that describe, document and store information about objects, operations, movements and provenance of objects. The scholarship working with those databases is grounded foremost in disciplines of the Humanities and Social Sciences: Sociology of Art studying the social worlds that construct a discourse of art and aesthetics; closely related to it the Social History of Art concerned with the social contribution to the appearance of certain art forms and practices; Economics and Art Business exploring global economic flow and the influence of wealth and management strategies on art; Art Theory developing discourse on concepts relating to a philosophy of art and therefore closely related to curating and art criticism; and Art History with research in provenance, image analysis and museum studies.  

Although established methods for collecting, analysing and storing of various data sources differ with the methodological approach each researcher takes, it can be said that the need for new computational tools that allow the analysis, storage, sharing and understanding of the new digital data sources are needed. Digital data collections can not be studied without tools that are appropriate for the analysis of digital textual, pictorial and numeric databases. Borgman (2015) illustrates the current discourse on Big Data/Little Data and the associated methodological approaches in current research communities and identifies much like Anne Burdick (2012) “there exists not one method, but many” for digital data analysis in the Humanities.

The research project uses the infrastructure of digital databases produced with methods in the DH but will advance a primary focus in computer-aided research with the development of current web based software development standards. Only in the past 7 years researchers started to develop “standardized, native application programming interfaces (APIs) for providing graphics, animation, multimedia, and other advanced features.” This standardization allows researchers to develop tools and applications that can be used in multiple different browsers and on different devices. This is to show that the digitization of object based collections (museum collections, libraries and archives etc.) has an established history but nevertheless the development of tools to access, display and analyse these digitized collections is just at the beginning of current  possibilities due to the development of web standards across browsers and devices. The research group will bring this standard to the work with digital museum collections and in general with digital object based collection.

Museums produce phenomenal amounts of data.

They do so by tradition, research about the provenance, narrative, material, production and cultural embeddedness are attached to every piece in a museum collection. By digitizing we do not only consider pictorial surrogates for the works or economic value (acquisition prize, insurance value and other administrative costs that keep a work of art in a specific physical condition) but rather, researchers have produced knowledge, a history and institutional contextualization about works of art in institutions. The mode of shareability of knowledge and access to a corpus of information about works of art in a museum context is, at the moment, unsatisfying but inevitable.

Another development is the creation of a data capitalism that we find in a current museum context especially through applications such as Google’s Art and Culture face detection software in which the private company asks their users to trade a face match with museum portraits for their user data and facial images which is believe to be used to “train and improve the quality of their facial recognition AI technology.” In contrast to this research projects in the Humanities have the aim to find and produce solutions for accessibility to information dissemination of museum collections that work based on the research, methods and data structures of the institution.     

But, the advent of digitization and digital modes of exhibitions have only exacerbated the possible facets of the work of art. Researchers from all disciplines in the humanities analyse and explore object based databases with a variety of quantitative and qualitative methods and data analysis tools. The proposed project aims to produce new digital tools for interdisciplinary and mixed method research in the digital humanities, working with extensive data sets that allow the inclusion of a variety of methods, data types and analysis tools.

In its preliminary phases, the project between three institutions is interested in exploiting databases of cultural material to pave the way for new research tools in contemporary art history. The collaborating institutions, The Médialab, Sciences Po, Paris Translocation Cluster at the Technische Universität Berlin and the Center for Data Arts, The New School, New York City will organize data sprints that started in Paris in Fall 2017.

The Data Sprints

This methodology in the overview of methods in the social sciences was borrowed from the development of free software and has been adapted to the new constraints weigh on researchers venturing into the world of digital data. It takes the form of a data sprint, a form of data-centered workshop designed to deliver a better understanding of datasets and conducive to formulate research questions based on their complex exploration. It is the interdisciplinary development of new digital tools for the humanities, a sequence mixing in a short duration, typically over one week: data mining, their (re) shaping and production of descriptive statistics and data visualizations.

“Data-sprints are intensive research and coding workshops where participants coming from different academic and non-academic backgrounds convene physically to work together on a set of data and research questions.”

The six phases of a data sprint are 1) Posing research questions; 2) Operationalizing research questions into feasible digital methods projects; 3) Procuring and preparing datasets; 4) Writing and adapting code; 5) Designing data visualizations and interface and 6) Eliciting engagement and co-production of knowledge.

History of the project

The Medialab, Sciences Po, in coordination with the Centre national des arts plastiques (CNAP) and videomuseum (Consortium of modern and contemporary public art collections), has already tested the possibility of exploiting a data management infrastructure to tease out research questions in art history and sociology of art during a data sprint organized in September 2016 in Paris. This workshop produced an initial study of the Goûts de l’État – the tastes of the State, for once a better rhyme in English than in French – by exploiting the rich documentation of the acquisition and circulation of contemporary art (about 83,956 works in its Fonds national d’art contemporain or FNAC, managed by the CNAP) by the French State since the revolution. The experience has been positive for both the art historians participating and for the CNAP cadres who have also learned quickly about many aspects of their database from the new formats and visualizations tried by the programmers and designers. Several research projects emerged as a result of this encounter between art historians, programmers and designers.

Data Sprint at the MediaLab at Sciences Po in November 2017

Since April 2017, the researchers involved in the project are working together to connect with museums as partnering institutions to the project, strategize data sprints, and generate a team of researchers that will be invited to the ongoing data sprints. The MediaLab at Sciences Po organized the first data sprint in November 2017 inviting over 25 participants including museum staff of the Centre Pompidou. The participants gathered for one week at Sciences Po and developed over 50 visualizations and two working software prototypes based on their preliminary research and on site data analysis.

Research Questions in the First Data Sprint included:
  • Provenance and the translocation of cultural assets
  • Modalities and temporality of acquisition
  • Exhibition in the museum and circulation outside of the museum
  • Artistic groups and collectives in the museum
  • Social, cultural and historical embeddedness of the collection

Small working groups focused on at least on one of the following approaches:

Mixed-Method approaches

Qualitative and quantitative methods are used on the same issue and with the same priorities. Quantitative methods give insight into a data set and qualitative methods are used for single cases. Both the qualitative approach can lead to research questions that can be utilized for structuring the quantitative analysis and vice versa. Machine learning and quantitative methods are practiced as forms of ‘distant reading’ that allow the qualitative researcher a ‘deep dive’ with an understanding of patterns of the entire dataset.  

Machine Learning: Natural Language Processing

The method in natural language processing that will be focussed on in the workshop is ‘Named entity recognition (NER)’ to detect entities such as people, places or organizations in large text based data sets. NER will make it possible to map these entities according to geo locations, expressions of time or their category (attributes). After the first data sprint, a group of researchers begun to work on a forthcoming focus in image recognition as a tool for authentication in art history:

Machine Learning: Image recognition

In recent years the digitization of cultural collections (archives, museum collections, libraries etc.) has produced a massive amount of digital images. These surrogates for the material objects can be analyzed with qualities (shapes, color, theme, etc.) that the digital object has and can lead to categorization and the identification of patterns in large scale data sets.

The data that the partnering institution, Centre Pompidou in Paris, made available for the interdisciplinary team of researchers contains “over 100,000 works, the collections of the Centre Pompidou (musée national d’art moderne – centre de création industrielle) which make up one of the world’s leading references for art of the 20th and 21st centuries.

 

Local Data Design: An Interview with Professor Yanni Loukissas

Dr. Anne Luther spoke with Professor Yanni Loukissas by phone to discuss his research focus on critical data studies and local readings of data collections. Yanni Loukissas is an assistant professor of digital media in the School of Literature, Media, and Communication at Georgia Tech, where he directs the Local Data Design Lab. He teaches courses in Digital Media, Computational Media, Human-Computer Interaction, and Science, Technology, and Society.

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