Hi everyone, my name is Julien Raemy and I am a PhD Candidate in Digital Humanities at the University of Basel. I'm happy to present what I'm doing as part of my thesis on Linked Open Usable Data for Cultural Heritage, but I'm not going to go into too much technical detail, but rather look at what I've already covered in my literature review and provide some overview of it.

Here is the complete working title of my PhD thesis. I am looking into two perspectives, namely community practices and semantic interoperability. I am affiliated with the doctoral programme of the Graduate School of Social Sciences and the main reason is that I would like to leverage a tehoretical framework using the Actor-Network Theory.

My research is grounded as part of the Participatory Knowledge Practices in Analogue and Digital Image Archives (PIA) research project, which aims to develop a Citizen Science platform around three photographic collections of the Cultural Anthropology Switzerland (CAS), formerly the Swiss Society for Folklore Studies (SSFS).  PIA is a Sinergia project funded by the Swiss National Science Foundation (SNSF) led by the University of Basel, the Uni, the Bern Academy of the Arts, and the Swiss Society for Folklore Studies. PIA wants to connect the world of data and things in an interdisciplinary manner. We explore the phases of the analogue and digital archive from the perspectives of cultural anthropology, technology and design. The common goal of this project is to design a visual interface with machine learning-based tools to make it easy to annotate, contextualize, organize, and link both images and their meta-information, to deliberately encourage the participatory use of archives.

I'm first going to talk about the ways that data can be interlinked on the web in terms of vision and standards, then I will deconstruct a little bit the definition of what is cultural heritage data and finally talk about two communities active in the cultural heritage field that develop and maintain web standards. And then we'll have some time for discussion.

From cultural heritage to cultural heritage data.

A broad definition of Cultural Heritage, often limited to its tangibility or materiality. In thinking about the concept of cultural heritage, I find this definition particularly resonant. This broader perspective is motivated by my interest in Linked Open Usable Data standards as a research area, particularly because of their notable agnosticism towards data. The background image is a Male Face Mask from the Guro culture that embody tangible and intangible aspects as it is worn on the occasion of a man’s second funeral.

As a fundamental characteristic, heterogeneity signifies the diverse forms and origins that shape heritage. E.g. Different techniques and varying viewpoints in treating data modelling.

Every dataset embodies an underlying potential that research and interpretation bring to light. A noticeable divide, especially within cultural heritage, exists between the generation of data, description of it and its use, owing to the diverse array of unforeseen applications. This second characteristic also highlights the temporal dimension, presenting cultural heritage data as a repository of latent knowledge awaiting discovery and interpretation. Notably, not all artefacts are – or should be – digitised, and even among those that are, (mis)representation and challenges in interconnecting them persist.

This dimension reinforces the essential role played by a variety of entities, predominantly CHIs, in safeguarding and managing resources, ensuring their preservation and accessibility for present and future generations. However, it's crucial to acknowledge the great divide in terms of resources, with indigenous and local communities often facing challenges in custodianship responsibilities.

The web, created in 1989 by Tim Berners-Lee, started with the philosophy that much academic information should be freely available to anyone.

This Web, which has claimed to be a Semantic Web for several years now, has a centrepiece known as Resource Description Framework (RDF), a general method for describing and exchanging graph data. The Semantic Web offers major opportunities for scholarship as it allows data to be reasoned together, that is to be understood by machines via those RDF-based ontologies, a formal way to represent human-like knowledge.

With RDF, everything goes in threes, the data model contains so-called triples: that is subject, predicate, object that form graphs. Most of the components of these triples use Uniform Resource Identifiers (URIs) and are generally web-addressable, whether for naming subjects and objects (which may themselves also be objects of other triples) or relationships

5-star open data scheme  1) make your stuff available on the Web (whatever format) under an open license 2) make it available as structured data 3) make it available in a non-proprietary open format (e.g., CSV instead of Excel 4) use URIs to denote things, so that people can point at your stuff 5) link your data to other data to provide context

The Semantic Web remains a compelling concept, offering powerful capabilities for modelling reality, enabling computers to infer novel information more effectively. However, querying RDF graphs is complicated, requiring a prior understanding of the structure. The overall idea of LOUD is to make data easy to use for humans, especially for developers. JSON-LD allows for some mapping of ontological constructs into JSON, which is the lingua-franca of modern developers and is a cornerstone technology of LOUD. Five design principles to promote data consumption have been conceived. To be part of the Web, not just on the Web.

Three systems have been identified to adhere to the LOUD design principles. They are complementary and can be used either separately or in conjunction.

IIIF is a community-driven initiative, which brings together key players in the academic and CH fields, and has defined open and shared APIs to standardise the way in which image-based resources are delivered on the Web. Implementing the IIIF APIs enables institutions to make better use of their digitised or born-digital material by providing, for instance, deep zooming, comparison, full-text search of OCR objects or annotation capabilities. An API is like a set of rules or protocols for how different software applications communicate and share data. It's similar to a common language or set of procedures that allows different programs to understand each other and work together efficiently.

The Linked Art data model, in its domain-specific application, particularly resonates with five facets: what, where, who, how, and when. This focus facilitates a nuanced tracking and interpretation of the key aspects of data provenance.

An important proposition arises from the observation that adherence to the \ac{LOUD} design principles makes specifications more likely to be adopted. The primary benefit of adopting \ac{LOUD} standards lies in their grassroots nature. The development and maintenance of \ac{LOUD} standards by dedicated communities are characterised by collaboration, consensus building, and transparency. This grassroots approach not only aligns with the core values of openness and collaboration within the \ac{DH} community but also serves as a common denominator between \ac{DH} practitioners and \acp{CHI}. This unique alignment fosters a sense of shared purpose and common ground. However, it's essential to acknowledge that while \ac{LOUD} and its associated standards, including IIIF, hold immense promise, their limited recognition in the wider socio-technical ecosystem may currently hinder their full potential impact.