Digital art posterity: building a data model for digital art corpora
Louise Fauduet

Céline Thomas

Chu-Yin Chen

Bibliothèque nationale de France
Francelouise.fauduet@bnf.fr

Université Paris 8
Franceceline_thomas@gmx.fr

Université Paris 8
Francechu-yin.chen@univ-paris8.fr

Adèle Sicre

Nola N’Diaye

Florent Aziosmanoff

Université Paris 8
Franceadele.sicrevidalou@gmail.com

École nationale des chartes
Francenolandiaye@gmail.com

Living Art Lab
Franceflorent.aziosmanoff@gmail.com

ABSTRACTThe research project “Digital art and posterity”, February 2015February 2018, aims to contribute to perpetuating digital artistic
heritage by developing a general descriptive system of digital
works of art which provides a way to model the technical andartistic characteristics of the work, its significant properties and its
formal principles in text form.
This research is performed in collaboration between three
institutions: the National Library of France (Bibliothèquenationale de France, BnF), the INRéV laboratory of Paris 8
University and the Living Art Lab. The partners come fromdifferent fields — those of conservation, of artistic creation and of
academic research — and combine their skills and experiences todevise a conceptual model and a data model true to thespecificities of the project’s corpora.
This paper presents the main attributes of the proposed
information model and ontology, so that all institutions involvedin the collection, preservation and diffusion of digital art can
provide input regarding its pertinence and interoperability.

CCS CONCEPTS• Information systems~Document topic models • Information
systems~Content analysis and feature selection • Information
systems~Ontologies• Applied computing~Performingarts• Applied computing~Media arts
• Appliedcomputing~Digital libraries and archives

KEYWORDS
Digital Art, Information Model, Data Model, Interactivity,
Transdisciplinarity, Versioning

1

INTRODUCTION

In recent years, there have been an increasing number of
papers at iPRES on the topics of emulation solutions and digitalart preservation [1]-[6]. Both issues are often intertwined, as
computer-generated audiovisual artistic creations that are of acomposite nature (sound, picture, video, motion picture, etc.)

require preservation processes ranging from emulating theoriginal to recreating the code and/or replacing the input andoutput devices with technologies of another nature. The
obsolescence of hardware and software involved in thepresentation of digital art is extremely rapid. And yet we need toensure that future generations will be able to experience theseworks while maintaining the possibility to interact with thetechnical and artistic content, in order to affect the course of its
performance.
“Art numérique et postérité” (“Digital art and posterity”) is a
project based on collaboration between a national library, auniversity department and a private creation and research partner.
The project aims to contribute to the preservation of digital art byworking on its description.
We are aware that there is a wide range of definitions of digitalart among the different communities of artists, researchers andcurators. The relevance of the information model we aredeveloping may be biased by the corpora and the professional
environment of the project’s partners, even though the members
come from different backgrounds and the collections are diverse.
We will include in this paper a presentation of the partners, theirwork environment and the art used in the project to give an
accurate picture of the information model’s immediate
applicability.
We will then present the conceptual model designed in the
project. The main characteristics of an information model forcontemporary digital art are the place given to the artist’s
intentions for the presentation of the artwork, as reconstituted by
the curators or as expressed in his or her own words, and theimportance of accounting for successive versions of an artwork.
We will discuss the challenges associated with the modelingprocess, and the way building a database and an ontology from theconceptual model impacts the overall description of digital art.

2

RESEARCH AS A MÉNAGE À TROIS

We will first introduce the actors of the project “Digital Art
and Posterity”, their contributions and missions. We then will
clarify the meaning of “art numérique” as we defined it using thecorpora of each collaborator as a representative panel of digitalart. We will explain the specificities of digital art in order tohighlight the challenges related to its preservation. Finally, we
discuss the issue of the mass treatment of digital artworks.

2.1

A versatile project teamThe research project “Digital Art and Posterity” is a project
shared between three institutions: the Bibliothèque nationale deFrance (BnF, the National Library of France), the Images
Numériques et Réalité Virtuelle research team (INRéV, Digital
Images and Virtual Reality), part of the Arts des Images et Art
Contemporain laboratory (AIAC E4010, Images Arts andContemporary Art) of Paris 8 University, and the Living Art Lab,an independent art studio.
This project was made possible thanks to the Labex Arts-H2H,
cluster of excellence in arts and human mediations1, laureate of
the program “Investing for the Future” since 2011 2 . All of theLabex’s research projects are built around the principle oftransdisciplinarity between different fields in the humanities. This
experimental dynamic made it possible for the project partners tomeet and to collaborate.
The first partner is the BnF, the project leader, and specificallyits Audiovisual department. The BnF has a mandate to collect avast array of publications. Over the years, it has developed bestpractices to describe documents ranging from manuscripts tovideo games. The Audiovisual department has built expertise in
the field of digitized and born-digital heritage preservation. In thepast few decades, the BnF has been gathering a digital artwork
collection through legal deposit. It is mostly composed of
documents on a physical medium but also entails web archiving
and contents distributed online. One of its objectives in our
project is to enrich its collection of digital art. It also aims at
bettering access to its collections using more standardized
description and access processes.
The second partner is the INRéV research team of Paris 8
University. For 30 years, this team has been developing a uniquemanner of apprehending digital creation. The laboratory’s aim
was and remains to continuously create, innovate and hybridize
art, science and technology. This team’s main figures areprotagonists of French digital art history. Their artistic practices
have given them an insider knowledge of digital techniques andtheir evolutions. One of the specificities developed by the researchteam over the years is interactive art with an autonomous andsometimes intelligent behaviour coupled with a reflexion on thecreative process. Combined with the undergraduates’ andgraduates’ productions at the Arts et Technologies de l’Image
department3 (ATI, Computer Graphic and Art Department), theseartworks constitute a remarkable corpus. INRéV joined the projectto start working on its preservation strategy as none is in place at
the University.

1

http://www.labex-arts-h2h.fr
2
http://www.enseignementsup-recherche.gouv.fr/pid24578/investissements-davenir.html
3
http://www.ati-paris8.fr/index.php?lang=en

The third partner is the Living Art Lab, an independent studiowhich was previously part of Le Cube, a center for digital art
creation. Le Cube, through the Living Art Lab, directed andproduced interactive art installations, by offering the creators
financial resources and IT skills. With experience in fostering andfacilitating digital art, the Living Art Lab brings to the project its
vision of digital art and its creations. Its goal is to promote andpreserve Living Art installations. These form a coherent corpus
with a specific approach to interaction which broadens our
project’s panel.
In addition to this original trio, we called on other skills toenrich the project by recruiting interns and experts with various
backgrounds: contemporary art philosophy, data processing andinformation science, management of audiovisual archives,computer science, art history, art conservation and digital
humanities.
The versatility of the project team makes for a stronger
scientific project. We rely on collective intelligence, which leads
us to interesting moments of constructive misunderstandings andallows us to move forward to better solutions.
First and foremost, the “art numérique” that the partners want
to describe and preserve had to be defined and matched with thecorpora.

2.2

What is “art numérique”?

A conventional definition of “digital art” would be a diverse
set of artistic creations based on the specificities of the computer
language and the IT system. It characterizes artworks produced bycomputers and that can be rendered with electronic devices. Thisart genre began to be produced in the early 1960s and has notceased developing since then through a wide range of artistic
expressions. In Québec art médiatique is seen as a whole, and art
numérique is understood specifically as online art. In the UnitedStates and in the UK, cultural institutions manage time-based
media art as an ensemble4, of which software-based art is a subset.
In France, art numérique or digital art is currently the most widelyused category [7]. Its history encompasses the permanent
evolution of digital technologies (for instance, virtual reality oraugmented reality) and the developments in connecteddisciplinary fields (such as artificial intelligence, artificial life,
cognitive science or robotics).
While we agree with this definition, it isn’t precise enough to
fit the complexity of our corpora. Among the properties we needto express in our description are the characteristics related to theinitial publication and production of the artwork, since the corporaof the partners have different publication histories: publishedworks at the BnF, research results at the ATI-INRéV, exhibited
objects at the Living Art Lab.
The first essential element of any description of digital art isthat computer programming is at its center. In the project, we
4

http://mattersinmediaart.org, https://www.nyu.edu/gsas/dept/fineart/events/timebased-media.htm

incorporate both interactive, intelligent or behavioral artwork andthe computer-animated image, since all these art forms arecomputer-based. The same artistic impulse governed theircreation, as is shown in the ATI-INRéV corpus. They have to bepreserved together according to specific strategies, and thecomputer systems used to create such moving images have to be
described in the information packages.
Furthermore, building on earlier research on the role of theviewer in creation [8], digital art explores the ability to create aninteractive relationship between the program and its external
environment and in particular with the spectator [9]. The BnF’s
corpus offers good examples of elementary multimedia interactive
artworks with its art CD-ROMs collection, produced in the 1990s.
Although these artworks are described in the BnF’s catalog, theirbibliographic records are based on a common model for all
electronic documents. The existing technical information isenough to render the discs in the reading rooms now, but
insufficient to allow long-term preservation. There is, for instance,
no record of the basic procedural rules needed to replay the art,
although changes in technological context gradually limit ourability to perceive the artwork as intended.
Another expression of the interactive relationship that can beproduced by digital art may be defined as “intelligent”,“behavioral” or even “autonomous”. Artworks in this category,more experimental, have been created within the ATI-INRéV and
Living Art laboratories since the mid-1980s. They require captors
and actuators, and/or virtual or augmented reality systems; their
3D images are generated in real-time by artificial life or
intelligence algorithms. From these artworks emerge autonomousor intelligent behaviors that have been defined as a new form ofinteractivity. Couchot, Tramus and Bret named it “second
interactivity” [10]; Aziosmanoff prefers the term of “Living Art”
[11], [12], and Chen, using the concepts of complexity andenaction [13], calls it “enactive digital art” [14]. The descriptionof these artworks has to include their behaviors, their selfactualization processes, and the interaction systems.

Figure 1: La Funambule virtuelle, Alain BERTHOZ, Michel
BRET, Marie-Hélène TRAMUS, 2000. Interactive installation.
Interaction with the spectator through position and rotation

captors attached to a belt, with an intelligent 3D computeranimated character developing a rebalancing strategy in realtime [15]. Uses a neural network program (Anyflo)5.
The most complex description and preservation challenges wehave to face come from parts of the corpora heavily reliant on
fundamental research on the art-science themes. Researchdomains such as artificial art/life, artificial art/intelligence,art/enaction, art/emergence have led to very unique andinnovative artworks. Examples in our corpora use made-tomeasure software (“Anyflo” by Bret 6 , “Rodin” by Huitric andNahas [16]), devices and platforms.

Figure 2: Morphogénèse, Chu-Yin CHEN, 1996 (film; 7’13).
Generative artwork, artificial life. Software: Anyflo. Result ofresearches on the creation of a virtual world (biosphere)
within which the virtual creatures self-generate according to
genetic algorithms [17][18].
While interaction gives the artworks the appearance of
unpredictability and instability due to the individualized
experience of the spectator, the real instability of the digital
objects comes from their successive versions in different softwareand hardware. In the thirty-odd years of INRéV’s existence, theartist-researchers have had to either update their artworks or letthem die. Whether at the artist’s initiative or at a museum’s orgallery’s request, repairing artworks for a new exhibition requires
different strategies: migration, emulation, recreation. Changes tothe original art range from slight modifications to complete
distortions. Over time, the successive versions of the artwork candiverge from replicas to form something akin to a series based on
the same concepts. Describing versioning of complex objects is
one of the main challenges of our project.
Along with this challenge emerges another of our issues: how
can we make the distinctive nature of digital artworks work withmass processes?

56

http://www.anyflo.com/bret/art/2000/fun/fun.htm
http://www.anyflo.com/bret/art/1986/Anyflo.htm

2.3

Dealing with mass

The project partners have very different processes forcollecting, describing, preserving and accessing their digital art
collections. None of them are currently geared towards presenting
digital art in an exhibition context, although it has happened andmay happen again.
The Preservation & Art - Media Archaeology Lab (PAMAL7)
at the Avignon School of Art has restored digital works of arts ina media archeology perspective, to study the impact of thematerial context of creation on the artworks’ reception [19]. But
the partners of our research project have different constraints, andsystematic recreation of artworks on software and hardware
matching the original is not practical given the volume ofcollections concerned, and access requests that are relatively
unpredictable compared to a planned exhibition project, forinstance.
The National Library of France has existing data and metadata
repositories, and access systems. Any solution tailored for digitalart must be included in these generic systems that combine dataon all types of materials, and specific information might lose
visibility in the process. There is a catalog and a data repository
using semantic web technologies8. There are two digital archives,
the Scalable Preservation and Archiving Repository (SPAR) [20]and the audiovisual archive. The latter is the current repository for
digital art content, but has limited metadata querying capabilities.
It is combined with a display system for the audiovisual researchreading room, where emulation processes are only very partiallyautomated. Library assistants deal with requests for materials
requiring emulation, and have the tools and skills to provide
access to relatively standardized content such as CD-ROMs fromthe 1990s. Any other level of installation and emulation currently
requires the intervention of a technician or engineer on a case bycase basis.
In contrast, INRéV has no preexisting processes, repositories
or tools for preserving its digital art collections, even though it
values the works created by its faculty and students highly, bothas art and as teaching devices.
Working on an information model for digital art is a mutually
beneficial project. It can improve the quality of preservation at the
BnF as the information requirements are implemented throughout
the digital preservation process with the input of digital art
specialists. It can also help the Paris 8 University and the Living
Art Lab develop new research on the properties of digital art, andhelp them evaluate whether the BnF can be a partner in theirpreservation needs.
The resulting data model has to be both generic enough todescribe any digital artwork despite the variety of techniques andapproaches in this field, and specific to allow the descriptive andpreservation metadata collected to be used for preservation
planning and prompt choices of access solutions.

3

The data model we have to build can only be constructed after
we have set a conceptual structure. To describe it here, we will
introduce our working methodology: we drew up an inventory ofthe digital artworks from our corpora, identified the informationnecessary for their preservation, and collected as much data as
was judged useful. The structure of the conceptual model thatorganizes the gathered information was then developed. It wasconstructed according to the digital artwork’s lifecycle andrespects its fluctuating nature from genesis to exhibition.

3.1

http://pamal.org/wiki/Accueil
8
catalogue.bnf.fr; data.bnf.fr

Awakening sleeping beauties“Once upon a time, our artworks were forgotten, asleep in the
midst of a wild forest. Going through the brambles, we managed
to discover marvelous hidden collections; and now the awakening
begins...”The project’s team first needed to identify the “sleeping
beauties” of our corpora.
The history of creation at the ATI-INRéV has been
documented through exhibitions and the memory of thisinstitution has been transmitted by the artist-teachers. However,an inventory of the artworks created by the professors andstudents has never been made.
The Living Art Lab has always been concerned with
documenting the works it fostered. The artworks have been
described on the Cube’s website at the time of their exhibition9.
The Living Art Lab’s method includes a focus on collecting
artists’ and IT engineers’ testimonies10. Nevertheless, there is no
digital archive of the collection.
As for the BnF, there was no typology or keywords in theircatalog that marked documents as digital art.
We inventoried over 300 works: around 200 from the BnF,
120 from the ATI-INRéV, 70 from the Living Art Lab. We
established a limited number of categories: 3D computeranimated films; generative artworks; interactive, intelligent or
behavioral installations; virtual reality and augmented reality
artworks; gaming creations; interactive multimedia artworks.
In order to evaluate the information and data required for theidentification of the artworks, we compared the descriptive
records of institutions outside the project, such as the ones createdon Navigart and reachable on Videomuseum’s website11, and weinterviewed curators. Simultaneously, we had to design a test
sample which was technically, historically and aesthetically
representative of our corpora, but also narrow enough to allow us
to analyze it thoroughly and to specify the information necessary
for the preservation of digital artworks
This identification of data performed, we had to awake ourbeauties; not with a kiss, but with documentation and data
9

7

THE CONCEPTUAL MODEL

http://lecube.com/fr/coproductions_151
http://lecube.com/fr/living-art-lab_154
http://www.videomuseum.fr

1011

collection. The lack of existing information has led us, as others
before, to try to capture information at the source: from the living
artists or contributors. We could rely on previous research fromthe museum community, such as the “The Variable Media
Questionnaire” of the Variable Media Network 12 [21], the“Questionnaire for New Media Works” of the DOCAM Research
Alliance (Documentation and conservaton of the media arts
heritage) 13, or the recommendations of Matters in Media Art 14.
Through several case studies, the Digital Art Conservation
project15, initiated in 2010 by the ZKM (Zentrum für Kunst undMedientechnologie Karlsruhe), was able to apply concrete
preservation strategies for a wide range of digital works based on
artist interviews [22]. Discussions with researchers and curators in
Québec and New York have confirmed this approach to becommon practice among heritage institutions.

phrases for the essential characteristics to maintain through eachgeneration of the piece, instinctively or deliberately.

Technical information about the artwork seemed the aspect themost often absent from records. We began by sending a technicalquestionnaire on digital artworks to the artists, producers andcontributors to gather information on how the work and its system
operate (required IT environment, peripheral devices andinterfaces, mode of interaction and mode of installation, etc.). We
then interviewed them in person, as they were interacting with
their artworks; this strategy has been well received so far. We
record both the play-through of the emulated artwork on thecomputer and the artist interview on video. Our partners at the
ATI-INRéV have also introduced the method known as the“entretien d’explicitation” (“clarifying interview technique”) [23]to the project. The entretien d’explicitation is an introspective
interview technique designed to lead the interviewee to accesspreviously unconscious memories of the creation process and pastactions. We aim at retrieving data on both the objective steps ofcreation and of the implicit knowledge related to the act.

The descriptive system we wish to devise includes theconcepts and key principles of digital art together withpreservation information related to the digital objects. It captures
the artwork from its creation to its diffusion, in various possible
contexts: exhibitions, classes, reading rooms and so on. We
designed our information model around two states of the artwork:
the artwork during the creative process, or “artwork-to-be”, andthe artwork we encounter as a spectator. We present here the“creation process” section of the model, followed by the“reception process” section.

Digital artists are aware of the ephemeral nature of their art.
Many have chosen to reassess and recreate their works in order tocontinue to exhibit or perform them, but nevertheless proceed indifferent ways. For instance, some of them are forced to slow
down technological improvements when they reactivate theirworks in order to respect the aesthetic aspects of the techniques
used at the origin of the creation, while others push forward theirworks with technological evolution and overwrite previous
versions of the artworks, etc. To evaluate artists’ different
preservation and description requirements according to the beliefs
and ideas on which their creative process was based, we organizeda study day on December 8 201616. These international artists anddigital art pioneers, discussing their expectations and theirinvolvement regarding the future of their artworks, have shown astrong interest in digital art preservation. They have defined thesignificant properties of their artworks, although they use different

Whether the artist is the only legitimate source for thedescription of the works and for preservation strategies choices
remains to be determined. Part of our efforts in building an
information model for digital art has certainly been dedicated tobalancing the artist’s word and objective data. While this is not abreakthrough discovery, we aim at translating this line ofreasoning into concrete rendering of the data model. It will also bea valuable tool to determine what preservation quality level the
BnF is ready to grant to digital artworks, and whether certain
types of digital art are more suited to the (relative) mass processesof a library.

3.2

GenesisThe knowledge and experience of the project partners dealing
in artistic creation have given us an opportunity to explore thecreative process in detail. Our aim is to preserve and give accessto the craftsmanship within the artwork. The first part of oursystem thus describes the artwork in its creative process: it begins
by the “conceptual artwork”, where we develop the genesis of theartwork, and then continues to the “realized artwork”, where we
detail the production process.

12

http://variablemediaquestionnaire.net
http://www.docam.ca/fr/outils/questionnaire-de-conservation.html
14
http://mattersinmediaart.org/acquiring-time-based-media-art.html
15
http://www.digitalartconservation.org/index.php/en.html
16
http://artnumeriqueposterite.labex-arts-h2h.fr/fr/content/programme
13

Figure 3: Simplified conceptual model: creative processWe need to describe the abstract idea of the artwork. This“conceptual artwork” emerges from the individuality of theauthor(s), their cultural and technical backgrounds, their artistic
and scientific references and influences, their intention, etc. In thisentity, we highlight the intellectual approach of the artist: theconcept that the artworks are intended to convey and the starting
point of the artistic project.
This abstract idea is materialized through digital tools andmedia; it evolves according to the reality it encounters. We named
this information entity “realized artwork”. For instance, it
encompasses the processes involved in the collaboration between
the artists and the programmers, technicians, mathematicians, etc.
Their contribution has to be understood not as merely technicallyproficient but also as creative: they too belong to the genesis of
the artwork.
Another meaningful element of the creative process is thecontext of creation: the date, place, event or occasion of
execution, the financial model and the production circuit it reliedon.
The heart of the piece is the computer program — which is notnecessarily written by the artist. We naturally include information
entities dedicated to the artwork’s internal and external tools,
whether already existing or produced specifically for the work,and the way they were used. “Internal system” describes all thesoftware, algorithms and their evolutions. “External system”
covers any type of hardware included in the artwork.
Parts of the corpora comprise art generated according tocomplex theoretical models, which forms a real challenge todefining a general descriptive system. For instance, artificial
intelligence is based on algorithmic techniques such as neuralnetworks; and artificial life uses genetic algorithms. Beyond
considerations of aesthetics or techniques, the conceptual modelneeds to accommodate complex relationships between entities.
We choose to build a network model where information is ranked
from the general to the specific. Our information model has to beopen and flexible in order to conform to any digital artwork type.

3.3 Performed, exhibited, rendered: the many
lives of the artwork
We designed our information model around two states of theartwork: the artwork during the creative process, or “artwork-tobe”, and the artwork we encounter as a spectator. This second partof the model, describing the reception process, further
distinguishes between the “performed artwork” and the“experienced artwork”.

Figure 4: Simplified information model: reception process
Once the artwork has been materialized, it is presented to the
public. This is the best-known state of the piece, which we call the“performed artwork”. Many of the works in our corpora are basedon the concepts of movement, real-time execution and interaction.
Their appearance changes continuously and also adapts to the
public with whom the work interacts; the works exist under acertain form at a certain time. Thus they are not just artefacts but
relationships, connecting the virtual environment and the realworld.
We describe the IT environment and system required to run the
artwork. We also describe the material environment which
supports it: the hardware, components and peripheral devices andtheir networked system. A significant number of digital art
installations also require other non-digital equipment andmaterials which have to be specified. Documentation such as
installation plans have to be integrated into our model. The modelallows for description of the scenography: space requirements andrestrictions (dimensions and characteristics), lightning (lightsource, luminous atmosphere…), noise level, etc.
The description of the “performed artwork” also needs, inorder for our model to be pertinent, to be completed byinformation on the system that allows the artwork’s relationship to
the spectator and participant, and/or the environment. The“system” entity is designed to record the precise role of eachinterface. The input interfaces characterize the interaction mode:
the work can react to a presence, a precise or generic gesture, aposition in space, a sound, and so on, and is not restricted to one
spectator. The output interfaces describe the perceived reaction of
the artwork: the moving image on a display, the sounds fromspeakers, etc.

performed artworks, which will generate an unlimited number ofexperienced artworks.

Figure 5: Input-output
installation)systemdiagram(interactive

The interaction protocol has to be precisely described to keep
replay and recreation options open. It can be graded on different
levels of complexity that go from the simple action-reaction to an
actual relationship between two equal objects with their own
behavior: the human and the intelligent digital system [24].
Our model links the performed artwork to an entity that
represents the performance event; an exhibition, a festival, aconference, and so on. There is a close relationship between thecircumstances of the event and the characteristics of theperformed artwork: its hardware changes, its backdrop and setting
are modified. In addition, it evolves over time, whether is it partly
or entirely emulated or recreated to conform to existing
contemporary technology.
To complement the description of the conditions of theartwork’s performance, we created an entity dedicated to thereception of the piece by the spectator: “experienced artwork”.
Since the artwork modifies itself anytime it meets an audience, it
only exists because someone “read” it, “played” it or with it,“used” it: because someone took part in its full realization. The
number of possible experiences is limitless; the implementation ofthis information entity could include a few representative
testimonies.
Textual information on the exhibition materials may be all that
documents the artwork if and when it enters the BnF’s collections:the library is not well suited to preserving made-for-measure
hardware, or even series of working contemporary computers.
By analyzing the existence of the artwork from its conception
to its concrete temporal instances, we can grasp the essence of thepiece and thus ensure that its description will be relatively stablethrough time and with different technologies. The information
model is built on the description of the different stages of theartwork’s life: conceptual, realized, performed and experienced. It
is both rhizomic and exponential; it is built to allow for thedescription of the artwork’s consecutive and/or parallel versions.
One conceptual artwork can generate an unlimited number ofrealized artworks, which can generate an unlimited number of

Figure 6: Artwork Lifecycle Diagram.

4

IMPLEMENTING THE INFORMATION
MODEL

The conceptual model was our first step towards machineactionable data models. We discuss here the adaptation of ourconceptual model into a database and an ontology, and how thespecificities of digital art influenced our choices.

4.1

Data models

Our first aim in building a database model and an ontology
was to test the conceptual model through different types of
implementation. On one hand, this process helped us consolidate
our model and define our concepts; on the other hand, it raised
new questions. The relational database and the ontology had to be
developed in parallel, and they had to encapsulate all the different
scenarios offered by a digital work of art that is based on theunpredictable. Ontologies and databases both have their limits, but
the most difficult challenge came with the database: to prevent
any recurrence or duplication, and moreover to avoid empty tables
and keys in the database.
The digital artwork’s lifecycle creates a problem ofterminology, in this field of art history where computer
technologies are preeminent. It is essential to distinguish the
hardware and software used for the creation of the artwork, thoseused for the initial performance during an exhibition or a festival,
those used for later versions of the work, and finally those we may
use for purposes of emulation. In the ontology, we get theopportunity to render this distinction by applying the FRBR
model. We can link technical metadata to the entities Work,
Expression, Manifestation and Item as needed.
In the relational database, we choose to distinguish the
hardware and the software as specific tables, and then to separate
them from the tables that describe the implementation of hardware
and software used by the artwork (“technical set up”) or
individual performances of artworks (“event”). This simplifies thedescription of versions in the database: using junction tables,
software and hardware can be ascribed to a specific setup and/or
event. By detailing technical metadata at several points of theartwork's lifecycle — conception, performance and emulation —,we create more opportunities for future research in the fields of art
history and computer sciences.
However this level of detail, and the tests we performed in
populating the database, gave rise to a new issue: defining thecore of the digital artwork. All the artworks in our corpora rely oninteractivity, and this cannot be expressed only in terms ofhardware and software, even if it is strongly related to both. The
table “System” aims at filling this void, by describing theintention governing the conception of the program, the cognitive
system within which the artist operated, the actions and reactionsof the audience, etc. We believe future researchers will value astandardized description of the type of interactivity to search for
artworks in the corpora, even as free text describing theexperience of the work remains irreplaceable in certain cases.

hardware etc. were not encapsulated in, and thus tied to, the table
describing the genesis of the artwork, when we need to use thesame information types to describe technical setups or emulation
instances. Besides, there would have simply been too many
elements in the one table to make it manageable.
One last example of the way our database and our ontology
affected the logic of our information or conceptual model is how
is allows us to see its flaws. We have difficulties modelingaesthetic currents and notions: the history of digital art is still
being made, and at the moment, it is impossible for us to establish
definite styles or movements and to fill fields of the sort in a
database or an ontology. This underscores the need of agreementin the wider community on several key definitions in digital art,
through a thesaurus for example.

4.2

What choices for our ontology?

We have additional objectives in working on an ontology
derived from our conceptual model: making our information
model interoperable, making our information machine-actionable,
and evaluating the proportion of data that can be standardized.
From this evaluation, we wish to assess how this ratio of free text
to controlled data affects the quality of preservation.
Achieving interoperability of the data model depends in parton an accurate assessment of the importance given to the free-text
description of interaction and behavior of the artwork. We want
the ontology to be precise enough to describe the project’s corpora
while opening it up to the possibility of being used in othercontexts. Interaction plays an important part in our description, as
it is the common denominator to our three collections. But weinclude in our model the possibility of artworks without
interactivity, with Pierre Morelli's table “Complexity Levels”. The
first level is indeed: “The object is unresponsive and without any
activity. It is totally inert”.

Figure 7: System table.
In our ontology, information relating to interactivity type andconceptual system is linked to the “Item” entity, as it is applicableto the preservation context of a specific instance of the artwork.
Implementing a database has led to retrospective changes in
the conceptual model: we now distinguish between conception, as
an intellectual activity, and production. Our initial “conception”
entity was too vague, encapsulating the intellectual and thetechnical aspects of the created work. We had to make sure
information items such as programs, algorithms, software,Manageability and interoperability also depend on choices
relating to integrating existing ontologies. We use a fair numberof preexisting classes and properties, some widely used anddescribing general concepts, some specific to information scienceand digital preservation. In the first category are SKOS and
FOAF17. In the second are FRBR-oo [25], Consumer Electronics
Ontology and the PREMIS ontology 18 . Used in major research
projects such as Biblissima 19 [26] and Doremus 20 , FRBR-oo
responds to our versioning issue, using the Work and Expression
classes. As for the PREMIS ontology, it is designed to address“metadata that a digital archive needs to know for preserving
objects” [27], which is at the center of our project. We areparticularly interested in “premis:Hardware”, describing the IT
equipment, “premis:Environment”, as the environmental context
17

https://www.w3.org/TR/skos-reference, http://www.foaf-project.org/
http://new.cidoc-crm.org/frbroo/home-0, http://wiki.goodrelationsvocabulary.org/Vocabularies, http://id.loc.gov/ontologies/premis.html
19
http://www.biblissima-condorcet.fr/
20
http://www.doremus.org/
18

and its documentation, both essentials to make digital objects
usable and in “premis:ObjectCharacteristics” to express
information about the format, size, fixity or else the creating
application of our different files composing the artworks.

will have to be full text. Indeed, it does not seem feasible oradvisable to express the creation process, or the user’s experience,as a set vocabulary, even if concepts have begun to emerge. We
will also have to add documentation (images, videos, testimonies,etc.) to the information package in order to satisfy the digital art
historians. A better understanding of the proportion of full text todocuments to controlled data in our descriptions will emerge inthe third year of the project, as we scale up our tests on thecorpora. The right proportion will be the one which satisfies theartist’s, the researcher’s and the archivist’s needs.

4.3

Figure 8: Proposed additional classes and properties.
We choose to limit the creation of classes and properties tothose absolutely necessary to express the particularities of digitalart with an interactive dimension. The terms “Behavior”,“AutonomyLevel” or “InteractionMode” represent these two
wishes. They express how an artwork behaves itself and two
components of this behavior: its capability of autonomous action(or reaction) and the way it interacts with the audience. In otherwords, we want to transpose the process and functioning ofinteraction: how many people it can connect with, what triggers
the interaction (breath, heat, movement) etc.
However, some of the data experts we are working with arereevaluating the priority given to class and property reuse. They
contend that, except for RDF vocabs widely used (such as Dublin
Core, SKOS, FOAF or even PREMIS), the data needs would bebetter served by dedicated classes and properties, rather than using
other vocabularies in a “Frankenmonster ontology”, as a matter ofmastering our data. Indeed, it would be almost safer to manage
our own classes and properties rather than using small ontologies
that, even if they already exist in the linked data world, are notmaintained on a regular basis. Furthermore, we are not aware of
any institution that has used the FRBR-oo or CIDOC-CRM
ontologies in its processes.
Implementing the conceptual model as a database and an
ontology raises the question of the coexistence of controlled
vocabularies and full text fields: what degree of standardization isefficient? This depends on several factors: at the art community
level, are concepts sufficiently stable to create a precise
thesaurus? At the preservation community level, are existing data
models adapted to the digital art field? Is there a stable source fornormalized information on formats, software and hardware? At
the institutional level, are there enough staff to implement thedescription in a variety of controlled fields? What fields will be
useful to index and propose to the users as a request entry point?
The technical and artistic fields in our model are designed withthe aim of populating them with controlled vocabularies, but some

Our to-do list

We are aware that our three-year research project will not lead
us to a complete data model implementation at the end of 2017.
Sorting the partners’ corpora, gathering data and preparing our
test corpus has been more time consuming than anticipated.
However, we do expect to revise the information model and theontology within this year, using the input we get from additional
artists’ testimonies as well as recommendations from fellow art
historians, librarians, and experts from the digital preservation
community.
We will try to experiment a mapping from the conceptualmodel to the BnF’s catalog format, INTERMARC. Description
formats and tools are currently being revised to facilitate theadoption of practices compatible with FRBR models, which is an
opportunity for our project, as our model has a work / expression /manifestation / item structure. We will also scale up the tests ofthe data model on the project’s corpora, using the test set which
has been defined in the second year of our research.
The closing conference for “Art numérique et postérité” inDecember will give us a chance to share our results with the art
and information science communities. We intend to show
artworks from the corpora through virtualization and emulation,and discuss the delta between the extent of our standardized
metadata and the aspects of the work that can only be rendered byfree text descriptions.

5

CONCLUSIONS

We are aware that the mix of artists, art historians andlibrarians in the project is both an asset and a liability. Therefore,
we are tracking another type of result, which we hope to foster:
the partners have experienced vast acculturation to one another’s
preoccupations. While the members of INRéV had no knowledgeof international best practices in digital preservation at the
beginning of the project, they are now discussed in the curriculumof the ATI Department. The importance of gathering informationon the artwork as it is being made is presented to the masters
students who are studying the technologies of digital art creation.
Conversely, the library staff had little knowledge of thesignificant properties of interactive digital art, which madedefining the information packages and evaluating the quality ofemulation and virtualization difficult. A first training session withthe library assistants in charge of facilitating access to the
documents in the audiovisual research reading room has allowed
us to consolidate the procedure for giving access to the emulated

artists’ CD-ROMs collection. Others will follow as more corpora
are ingested in the BnF’s archive.
In the future, we will have to monitor our information and data
models to ensure that they remain applicable as digital art evolves.
We have built the models to encompass a large array of digitalart creations, and have tried to articulate interaction systems,
hardware and software in a way that allows for fast-evolving
technologies. Yet we are keenly aware that preservation is acontinuous process and that we have to balance the requirements
for a stable model with the multifaceted and ephemeral nature ofdigital art.

ACKNOWLEDGMENTS
We would like to thank the team who made this project possible:
Élodie Bertrand, Marie Saladin, Jean-Philippe Humblot, Bertrand
Caron, Sébastien Peyrard, Pierre Choffé, Françoise Leresche at
the BnF; Marie-Hélène Tramus, Vincent Meyrueis, EdmondCouchot and Michel Bret at Paris 8 University.
Our interns brought new skills to our research: CatherineChampenois, Juliette Fattal, Tigran Ghaplanyan, Catherine
Helmer, Yu-Ci Huang, Gaétan Lemaitre, Victor Martin, Julie
Milhiet, Nola N’Diaye, Laetitia Perez.
We received invaluable help from the Arts-H2H Labex team andour external collaborators: Pauline Cellard, Peter Stirling, Mehdi
Bourgeois, Jean-Luc Soret.
Finally we would like to thank the artists and researchers, who are
the very heart of our project.

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