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PurposeThis paper proposes a new perspective on the enormous and unresolved challenge to existing practices of publication and documentation posed by the outputs of digital research projects in the humanities, where much good work is being lost due to resource or technical challenges.Design/methodology/approachThe paper documents and analyses both the existing literature on promoting sustainability for the outputs of digital humanities projects and the innovative approach of a single large-scale project.FindingsThe findings of the research presented show that sustainability planning for large-scale research projects needs to consider data and technology but also community, communications and process knowledge simultaneously. In addition, it should focus not only on a project as a collection of tangible and intangible assets, but also on the potential user base for these assets and what these users consider valuable about them.Research limitations/implicationsThe conclusions of the paper have been formulated in the context of one specific project. As such, it may amplify the specificities of this project in its results.Practical implicationsAn approach to project sustainability following the recommendations outlined in this paper would include a number of uncommon features, such as a longer development horizon, wider perspective on project results, and an audit of tacit and explicit knowledge.Social ImplicationsThese results can ultimately preserve public investment in projects.Originality/valueThis paper supplements more reductive models for project sustainability with a more holistic approach that others may learn from in mapping and sustaining user value for their projects for the medium to long terms.

This paper presents an attempt to provide a generic named-entity recognition and disambiguation module (NERD) called entity-fishing as a stable online service that demonstrates the possible delivery of sustainable technical services within DARIAH, the European digital research infrastructure for the arts and humanities. Deployed as part of the national infrastructure Huma-Num in France, this service provides an efficient state-of-the-art implementation coupled with standardised interfaces allowing an easy deployment on a variety of potential digital humanities contexts. Initially developed in the context of the FP9 EU project CENDARI, the software was well received by the user community and continued to be further developed within the H2020 HIRMEOS project where several open access publishers have integrated the service to their collections of published monographs as a means to enhance retrieval and access. entity-fishing implements entity extraction as well as disambiguation against Wikipedia and Wikidata entries. The service is accessible through a REST API which allows easier and seamless integration, language independent and stable convention and a widely used service-oriented architecture (SOA) design. Input and output data are carried out over a query data model with a defined structure providing flexibility to support the processing of partially annotated text or the repartition of text over several queries. The interface implements a variety of functionalities, like language recognition, sentence segmentation and modules for accessing and looking up concepts in the knowledge base. The API itself integrates more advanced contextual parametrisation or ranked outputs, allowing for the resilient integration in various possible use cases. The entity-fishing API has been used as a concrete use case to draft the experimental stand-off proposal, which has been submitted for integration into the TEI guidelines. The representation is also compliant with the Web Annotation Data Model (WADM). In this paper we aim at describing the functionalities of the service as a reference contribution to the subject of web-based NERD services. In this paper, we detail the workflow from input to output and unpack each building box in the processing flow. Besides, with a more academic approach, we provide a transversal schema of the different components taking into account non-functional requirements in order to facilitate the discovery of bottlenecks, hotspots and weaknesses. We also describe the underlying knowledge base, which is set up on the basis of Wikipedia and Wikidata content. We conclude the paper by presenting our solution for the service deployment: how and which the resources where allocated. The service has been in production since Q3 of 2017, and extensively used by the H2020 HIRMEOS partners during the integration with the publishing platforms. International audience

Abstract Contemporary discourse points to the central role that heritage plays in the process of enabling groups of various cultural or ethnic background to strengthen their feeling of belonging and sharing in society. Safeguarding heritage is also valued highly in the priorities of the European Commission. As a result, there have been several long-term initiatives involving the digitisation, annotation and cataloguing of tangible cultural heritage in museums and collections. Specifically, for built heritage, a pressing challenge is that historical monuments such as buildings, temples, churches or city fortification infrastructures are hard to document due to their historic palimpsest; spatial transformations, actions of destruction, reuse of material, or continuous urban development that covers traces and changes the formal integrity and identity of a cultural heritage site. The ability to reason about a monument’s form is crucial for efficient documentation and cataloguing. This paper presents a 3D digitisation workflow through the involvement of reality capture technologies for the annotation and structure analysis of built heritage with the use of 3D Convolutional Neural Networks (3D CNNs) for classification purposes. The presented workflow contributes a new approach to the identification of a building’s architectural components (e.g., arch, dome) and to the study of the stylistic influences (e.g., Gothic, Byzantine) of building parts. In doing so this workflow can assist in tracking a building’s history, identifying its construction period and comparing it to other buildings of the same period. This process can contribute to educational and research activities, as well as facilitate the automated classification of datasets in digital repositories for scholarly research in digital humanities.

Abstract 3D Heritage Online Presenter (3DHOP) is a framework for the creation of advanced web-based visual presentations of high-resolution 3D content. 3DHOP has been designed to cope with the specific needs of the Cultural Heritage (CH) field. By using multiresolution encoding, it is able to efficiently stream high-resolution 3D models (such as the sampled models usually employed in CH applications); it provides a series of ready-to-use templates and examples tailored for the presentation of CH artifacts; it interconnects the 3D visualization with the rest of the webpage DOM, making it possible to create integrated presentations schemes (3D + multimedia). In its design and development, we paid particular attention to three factors: easiness of use, smooth learning curve and performances. Thanks to its modular nature and a declarative-like setup, it is easy to learn, configure, and customize at different levels, depending on the programming skills of the user. This allows people with different background to always obtain the required power and flexibility from the framework. 3DHOP is written in JavaScript and it is based on the SpiderGL library, which employs the WebGL subset of HTML5, implementing plugin-free 3D rendering on many web browsers. In this paper we present the capabilities and characteristics of the 3DHOP framework, using different examples based on concrete projects.