A recurrent demand in many archaeological digital documentation systems is the need for an accurate as possible registration of data. Somehow, contrary to this request, are efforts led by various computer science groups dealing with 3D documentation and focusing on developing fast and cheap solutions to record 3D models of archaeological assets. The aim of the article is to highlight the importance of aligning the 3D documentation strategy to the archaeological aims, by detailing all factors to be considered when deciding on one documentation strategy over another. The archaeological question discussed here, part of the PhD thesis of one of the co-authors (MP), relates to the Cypro-Minoan signatory and its diachronic variability. The 3D geometric characterization of signs and subsequent shape analysis is the method chosen to reach this goal. A major effort to be invested in correctly determining the shape and variability of each sign, is in assuring that the 3D captured shape is as close as possible to the archaeological reality, which is a common problem not only in palaeographical analysis but also in other fields, where features of interest are in the sub-millimetre range. The paper will illustrate how different data acquisition approaches and post-processing steps such as alignment methods and error treatment may distort the visualised result and thus have a negative impact on planned analysis. Thus, it will argue for the importance of more detailed paradata to allow an informed assessment of the reliability of 3D models and it proposes a list of values and decision-making steps that help make the 3D digitization process more robust and verifiable.
Digital transformation in government has brought an increase in the scale, variety, and complexity of records and greater levels of disorganised data. Current practices for selecting records for transfer to The National Archives (TNA) were developed to deal with paper records and are struggling to deal with this shift. This article examines the background to the problem and outlines a project that TNA undertook to research the feasibility of using commercially available artificial intelligence tools to aid selection. The project
AI for Selection
evaluated a range of commercial solutions varying from off-the-shelf products to cloud-hosted machine learning platforms, as well as a benchmarking tool developed in-house. Suitability of tools depended on several factors, including requirements and skills of transferring bodies as well as the tools’ usability and configurability. This article also explores questions around trust and explainability of decisions made when using AI for sensitive tasks such as selection.
Extensive research on mobile guides for museums has explored the potential of technology to offer some of the services that have been traditionally provided by human guides, including guiding visitors in the museum space, providing information about the exhibits, and using more advanced interpretative approaches such as digital storytelling and gamified techniques. However, the majority of these approaches either ignores or tries to substitute entirely the role of the human guide. In this work, we present a user study with 10 experienced tour guides, currently working in the museum of modern art of the Basil & Elise Goulandris Foundation. Based on a three-phase procedure, the study is designed to empower professionals into envisaging their work in symbiosis with current technological developments. First, we attempt to identify existing challenges guides face and to capture their tacit knowledge in addressing emerging problems in guided tours. In the second and third stage, through a reflective and productive discussion, we employ a set of contemporary innovative digital applications as a starting point to elicit their views on their role in an envisaged symbiotic future of human-led hybrid digital experiences.
VR/AR technology is a key enabler for new ways of immersively experiencing cultural heritage artifacts based on their virtual counterparts obtained from a digitization process. In this article, we focus on enriching VR-based object inspection by additional haptic feedback, thereby creating tangible cultural heritage experiences. For this purpose, we present an approach for interactive and collaborative VR-based object inspection and annotation. Our system supports high-quality 3D models with accurate reflectance characteristics while additionally providing haptic feedback regarding shape features of the object based on a 3D printed replica. The digital object model in terms of a printable representation of the geometry as well as reflectance characteristics are stored in a compact and streamable representation on a central server, which streams the data to remotely connected users/clients. The latter can jointly perform an interactive inspection of the object in VR with additional haptic feedback through the 3D printed replica. Evaluations regarding system performance, visual quality of the considered models, as well as insights from a user study indicate an improved interaction, assessment, and experience of the considered objects.
Social networks constitute a valuable source for documenting heritage constitution processes or obtaining a real-time snapshot of a cultural heritage research topic. Many heritage researchers use social networks as a social thermometer to study these processes, creating, for this purpose, collections that constitute born-digital archives potentially reusable, searchable, and of interest to other researchers or citizens. However, retrieval and archiving techniques used in social networks within heritage studies are still semi-manual, being a time-consuming task and hindering the reproducibility, evaluation, and open-up of the collections created. By combining Information Retrieval strategies with emerging archival techniques, some of these weaknesses can be left behind. Specifically, pooling is a well-known Information Retrieval method to extract a sample of documents from an entire document set (posts in case of social network’s information), obtaining the most complete and unbiased set of relevant documents on a given topic. Using this approach, researchers could create a reference collection while avoiding annotating the entire corpus of documents or posts retrieved. This is especially useful in social media due to the large number of topics treated by the same user or in the same thread or post. We present a platform for applying pooling strategies combined with expert judgment to create cultural heritage reference collections from social networks in a customisable, reproducible, documented, and shareable way. The platform is validated by building a reference collection from a social network about the recent attacks on patrimonial entities motivated by anti-racist protests. This reference collection and the results obtained from its preliminary study are available for use. This real application has allowed us to validate the platform and the pooling strategies for creating reference collections in heritage studies from social networks.
Computational technologies have revolutionized the archival sciences field, prompting new approaches to process the extensive data in these collections. Automatic speech recognition and natural language processing create unique possibilities for analysis of oral history (OH) interviews, where otherwise the transcription and analysis of the full recording would be too time consuming. However, many oral historians note the loss of aural information when converting the speech into text, pointing out the relevance of subjective cues for a full understanding of the interviewee narrative. In this article, we explore various computational technologies for social signal processing and their potential application space in OH archives, as well as neighboring domains where qualitative studies is a frequently used method. We also highlight the latest developments in key technologies for multimedia archiving practices such as natural language processing and automatic speech recognition. We discuss the analysis of both visual (body language and facial expressions), and non-visual cues (paralinguistics, breathing, and heart rate), stating the specific challenges introduced by the characteristics of OH collections. We argue that applying social signal processing to OH archives will have a wider influence than solely OH practices, bringing benefits for various fields from humanities to computer sciences, as well as to archival sciences. Looking at human emotions and somatic reactions on extensive interview collections would give scholars from multiple fields the opportunity to focus on feelings, mood, culture, and subjective experiences expressed in these interviews on a larger scale.
In recent years, three-dimensional (3D) scanning has become the main tool for recording, documenting, and preserving cultural heritage in the long term. It has become the “document” most in demand today by historians, curators, and art restorers to carry out their work based on a “digital twin,” that is, a totally reliable and accurate model of the object in question. Thanks to 3D scanning, we can preserve reliable models in digital format of the real state of our heritage, some of which are currently destroyed. The first step is to digitize our heritage with the highest possible quality and precision. To do this, it will be necessary to identify the most appropriate technique. In this article, we will show some of the main digitization techniques currently used in sculpture heritage and the workflows associated with them to obtain high-quality models. Finally, a complete comparative analysis will be made to show their main advantages and disadvantages.
In this article, the Mingei Online Platform is presented as an authoring platform for the representation of social and historic context encompassing a focal topic of interest. The proposed representation is employed in the contextualised presentation of a given topic, through documented narratives that support its presentation to diverse audiences. Using the obtained representation, the documentation and digital preservation of social and historical dimensions of Cultural Heritage are demonstrated. The implementation follows the Human-Centred Design approach and has been conducted under an iterative design and evaluation approach involving both usability and domain experts.
The digital transformation is turning archives, both old and new, into data. As a consequence, automation in the form of artificial intelligence techniques is increasingly applied both to scale traditional recordkeeping activities, and to experiment with novel ways to capture, organise, and access records. We survey recent developments at the intersection of Artificial Intelligence and archival thinking and practice. Our overview of this growing body of literature is organised through the lenses of the Records Continuum model. We find four broad themes in the literature on archives and artificial intelligence: theoretical and professional considerations, the automation of recordkeeping processes, organising and accessing archives, and novel forms of digital archives. We conclude by underlining emerging trends and directions for future work, which include the application of recordkeeping principles to the very data and processes that power modern artificial intelligence and a more structural—yet critically aware—integration of artificial intelligence into archival systems and practice.
This article describes the computational and data-related challenges of the “Connected Histories of the BBC” project, an interdisciplinary project aiming to bring into the public realm some of the hidden treasures of the BBC's own Oral History Archive through the creation of an openly accessible, fully searchable and interconnected digital catalogue of this archive. This project stands as an interesting case study on the tensions between “computational” and “archival”, by critically designing and employing computational approaches for an historical, complex Oral History collection of scattered analogue records of various forms with an archival pre-history. From data acquisition, modeling, structuring and enhancement, metadata, data analysis procedures, to web design and legal issues, this paper discusses the various computational challenges, processes and decisions made during this project, while showcasing the principles of (re)usability, accessibility, and collaboration throughout its course.