Applying Effective Data Modelling Approaches for the Creation of a Participatory Archive Platform

Abstract

The development of a participatory archive platform such as the one being carried out for the PIA research project requires a flexible infrastructure allowing genuine data curation and a robust underlying data model. A strong assumption to achieve this is to primarily leverage Linked Open Usable Data (LOUD) standards, such as IIIF, Linked Art or the Web Annotation Data Model, which help in the dissemination and reuse of cultural heritage resources as well as contributing that digital humanities initiatives become more sustainable.

Full text

Applying Eective Data Modelling Approaches for the
Creation of a Participatory Archive Platform
JULIEN ANTOINE RAEMY,University of Basel, Switzerland
The development of a participatory archive platform such as the one being carried out for the PIA research
project requires a exible infrastructure allowing genuine data curation and a robust underlying data model.
A strong assumption to achieve this is to primarily leverage Linked Open Usable Data (LOUD) standards, such
as IIIF, Linked Art or the Web Annotation Data Model, which help in the dissemination and reuse of cultural
heritage resources as well as contributing that digital humanities initiatives become more sustainable.
CCS Concepts: •Theory of computation
→
Data modeling;•Information systems
→
Semantic web
description languages;RESTful web services;Ontologies;Thesauri;Digital libraries and archives;•
Software and its engineering →Interoperability.
Additional Key Words and Phrases: Citizen Science, Cultural Heritage, Digital Sustainability, International
Image Interoperability Framework (IIIF), Linked Art, Linked Open Usable Data (LOUD), Schema.org
1 INTRODUCTION
The digitisation of cultural heritage resources by memory organisations, such as libraries, archives
and museums, has greatly beneted the research community, enabling them to answer previously
elusive research questions, to raise entirely new ones, and to engage in critical reection on the
consequences of digital transformation.
While cultural heritage resources often have the advantage of being in the public domain or
licensed for digital processing and publication, the challenges of accessing - which is ultimately the
purpose of preservation - and reusing these outputs in the long term are generally not guaranteed
because infrastructures to ensure this type of process are lacking [
10
]. Although there are many
institutional or eld-specic repositories, generally only a part of the research data is preserved,
usually bound to a Data Management Plan (DMP), if not frozen.
The FAIR
1
Principles [
23
] can help digital humanities to achieve some measure of digital sustain-
ability and keep these data principles as a common thread. However, this is not enough to achieve
the exibility that an infrastructure and the underlying data model should have with regard to
sustainability.
One of the strategies to have a constant maintenance of research data in digital humanities is to
leverage the architecture of the Web [
9
], specically using Linked Open Data (LOD) approaches
and ontologies such as CIDOC-CRM [4,12].
This paper will look at how the human dimensions around the project titled Participatory
Knowledge Practices in Analogue and Digital Image Archives (PIA) can impact data modelling as well
as identifying the requirements for developing a participatory archive platform where web-based
standards play a key role in the dissemination and re-usability of knowledge [20].
2 PARTICIPATORY KNOWLEDGE PRACTICES IN ANALOGUE AND DIGITAL IMAGE
ARCHIVES (PIA)
PIA is a four-year interdisciplinary research project - running from February 2021 to January
2025 - funded by the Swiss National Science Foundation (SNSF)2. The project is conducted by the
1Findable, Accessible, Interoperable, Reusable (FAIR)
2SNSF. Participatory Knowledge Practices in Analogue and Digital Image Archives. https://p3.snf.ch/Project-193788
Author’s address: Julien Antoine Raemy, julien.raemy@unibas.ch, University of Basel, Digital Humanities Lab, Spalenberg
65, CH-4051, Basel, Switzerland.

2 Julien A. Raemy. Human Factors in Digital Humanities, PhD Seminar @EPFL, Dec 2-3, 2021
Institute for Cultural Anthropology and European Ethnology and the Digital Humanities Lab of
the University of Basel as well as the Bern University of the Arts.
The purpose of PIA is to design a visual interface with machine learning-based tools to make it
easy to annotate, contextualize, organise, and link both images and their metadata, to deliberately
encourage the participatory use of archives. It focuses on three very diverse photographic collections
of the Swiss Society for Folklore Studies (SSFS)3, namely:
•
SGV_05: The Atlas of Swiss Folklore consisting of 256 maps and 1000 pages of commentary.
This collection, which hasn’t yet been digitised, was commissioned by the SSFS to do an
extensive survey of the Swiss population in the 1930s and 1940s on many issues pertaining,
for instance, to everyday life, local laws, superstitions, celebrations or labour;
•
SGV_10: Kreis Family comprises approximately 20,000 loose photographic objects, mostly
kept in photo albums, from a wealthy Basel-based family and spanning from the 1850s to
the 1970s. The pictures were taken by studio photographers as well as by family members
themselves;
•
SGV_12: Ernst Brunner is a donation of about 48,000 negatives and 20,000 prints to the SSFS
from a professional photographer who lived from 1901 to 1979 and who documented mainly
in the 1930s and 1940s a wide range of folkloristic themes.
The fact that part of these collections still has to be digitised alongside the project will be an
opportunity to investigate the digital transformation processes, the generation of digital surrogates
and their associated metadata as well as how the underlying materiality aspects may or may not be
preserved.
More specically, there are two main goals within PIA: the rst having a theoretical focus on the
systematic analysis and description of the analogue and digital photo archives and the second an
implementation focus related to the design of a participatory image archive.
PIA is as much about traditional crowdsourcing as it is about creating a modern Citizen Science
platform that enables new uses and helps to streamline the research process of scholars. For this
purpose, a user interface and various application programming interfaces (APIs) will be deployed
to accommodate various forms of re-use by third parties [17].
3 IDENTIFIED REQUIREMENTS FOR DEPLOYING A CITIZEN SCIENCE
INFRASTRUCTURE
Substantial preliminary work, particularly with regard to data cleaning and reconciliation, needs to
be carried out prior to truly deploying an infrastructure that ensures content re-usability, whether
by the scientic community or for the wider public [
16
]. Notably, one of the intentions of PIA is to
adopt metadata standards and web-based specications that are well established within the cultural
heritage eld [
13
,
15
] in the interests of providing a high level of interoperability. To this end, the
following list of requirements inuencing the data modelling and the overarching architecture of
the infrastructure has been identied:
•Management of existing (non-controlled) keywords and the forthcoming folksonomy;
•
Creation of controlled vocabularies using the Simple Knowledge Organization System
(SKOS) for all PIA-related collections where dedicated terminology can complement existing
LOD taxonomies and thesauri, such as the Getty Vocabularies;
•Metadata correction and enrichment through crowdsourcing;
•
Validation of metadata created by Machine Learning methods (notably Object Detection
and Visual Text Co-Embedding) through the content-based multimedia retrieval system
vitrivr [8];
3The photo archive of the SSFS can be consulted online at https://archiv.sgv-sstp.ch/

Applying Eective Data Modelling Approaches for the Creation of a Participatory Archive Platform 3
•
Annotation and transcription of digital surrogates and born-digital content that are com-
patible with the W3C Web Annotation Data Model;
•
Reconciliation of entities (e.g. agent, concept, place) on the basis of the existing data model
and the user-generated metadata;
•
Making digitised collections of the SSFS as well as resources uploaded by end users compli-
ant with the Image and Presentation APIs 3.0 of the International Image Interoperability
Framework (IIIF) [1,2,21];
•
Leveraging the IIIF Change Discovery API 1.0, which is an Activity Streams endpoint, to
notify amendments to IIIF resources and make them more easily discoverable in a machine-
readable manner [3,7].
The identication of these requirements provides the framework for establishing an infrastructure
that could be in line with the FAIR principles. Furthermore, one of the cornerstones of the project
is also the synchronisation of the enriched data between the PIA infrastructure and the Data &
Service Center for the Humanities (DaSCH), which is in charge of the long-term preservation of
the SSFS (digitised or digital-born) photographs and their associated metadata.
4 THE PIA DATA MODEL
In the context of the database migration from Salsah to the DaSCH Service Platform (DSP) and to
anticipate the needs of the PIA project, it was decided to add new classes and properties within the
RDF-based SSFS ontology, to rename some of them with the
CamelCase
practice, to delete some not
or hardly used properties as well as to identify a common denominator with the PIA data model
4
,
which is still a work in progress [
6
]. We believe that the best candidate for this mapping, which
will be done using the
rdfs:subClassOf
and
rdfs:subPropertyOf
predicates, is Schema.org, a
vocabulary providing a very extensive number of classes and properties as well as having the added
benet of being easily indexed by search engines like Google, Bing or Yandex [22].
Fig. 1. Partial Representation in Linked Art of [Katze auf einer Mauer], SGV_12N_19553, https://archiv.sgv-
sstp.ch/resource/441788 - object that will have a IIIF Image API 3.0 digital service on the PIA platform
4
The PIA Data Model GitHub repository is available at: https://github.com/Participatory-Image- Archives/pia-data- model/

4 Julien A. Raemy. Human Factors in Digital Humanities, PhD Seminar @EPFL, Dec 2-3, 2021
If Schema.org is also going to be used within the PIA project and notably by embedding a
JSON-LD serialization within the resources’ web pages, we also want to provide a representation
of the activities surrounding the collections with a focus on their provenance. Thus, Linked Art,
which is both a community-based eort and an application prole based on CIDOC-CRM as well
as providing an API in JSON-LD [5], will be deployed.
Another advantage of Linked Art is that we can integrate other digital services, such as IIIF
(see Figure 1, which is based on the Linked Art Digital Integration component). As announced in
the previous chapter, we also want to make the annotations compatible with the Web Annotation
Data Model, which can be easily used in conjunction with the IIIF APIs. The three specications
(Linked Art, IIIF, Web Annotatioin Data Model) can be leveraged seamlessly in unison and all
enable published data to be easily consumed by both machines and humans. Moreover, these
technologies adhere to the design principles of Linked Open Usable Data (LOUD), term coined by
Robert Sanderson - which attempts to extend the principles of LOD and who has been working on
these specications [19].
Last but not least, another aspect of the PIA Data Model will be to address specic needs of
the SGV_05, SGV_10 or SGV_12 collections in terms of controlled vocabularies. For the SGV_12
Ernst Brunner collection, there is a prominent interest since the photographer had decided to
develop his own terminology to structure and classify his photographs. These terms have so far not
been included in the metadata. A thesaurus in SKOS has therefore been created and published via
SkoHub-Vocabs [
14
]. It will be rened over the next few months and the items will be connected to
this classication for research purposes.
5 CONCLUSION
A exible data model in digital humanities projects requires seeing the Web as a technology on
which other building blocks can be developed (e.g. RESTful APIs) and preferably on LOD for
enabling inferences, and even better moving towards specications that conform to the LOUD
design principles for publishing data that is truly usable and which will consequently improve the
accessibility and sustainability of digital cultural heritage resources.
The limitation to deploying and maintaining an infrastructure with LOUD standards remains
that organisations need to dene access persistence policies, notably by assigning cool URIs or
persistent identiers (PIDs) that could at least resolve to alternative web pages containing the
associated metadata should they disappear [11,18].
ACKNOWLEDGMENTS
PIA is made possible thanks to a SNSF Sinergia grant and I would like to thank all my colleagues,
especially my supervisors (Peter Fornaro and Walter Leimgruber), the ve other fellow PhD
candidates (Murielle Cornut, Birgit Huber, Fabienne Lüthi, Florian Spiess and Max Frischknecht)
and our software developer (Adrian Demleitner), working on this research project.
Many thanks as well to Yumeng Hou, Doctoral Assistant at the Laboratory for Experimental
Museology of the Ecole Polytechnique Fédérale de Lausanne (EPFL), for organising the PhD seminar
on Human Factors in Digital Humanities both on site and online on December 2-3, 2021.
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