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Non-fungible tokens (NFTs) make it technically possible for digital assets to be owned and traded, introducing the concept of scarcity in the digital realm for the first time. Resulting from this technical development, this paper asks the question, do they provide an opportunity for fundraising for galleries, libraries, archives and museums (GLAM), by selling ownership of digital copies of their collections? Although NFTs in their current format were first invented in 2017 as a means for game players to trade virtual goods, they reached the mainstream in 2021, when the auction house Christie’s held their first-ever sale exclusively for an NFT of a digital image, that was eventually sold for a record 69 million USD. The potential of NFTs to generate significant revenue for artists and museums by selling effectively a cryptographically signed copy of a digital image (similar to real-world limited editions, which are signed and numbered copies of a given artwork), has sparked the interest of the financially deprived museum and heritage sector with world-renowned institutions such as the Uffizi Gallery and the Hermitage Museum, having already employed NFTs in order to raise funds. Concerns surrounding the environmental impact of blockchain technology and the rise of malicious projects, exploiting previously digitised heritage content made available through OpenGLAM licensing, have attracted criticism over the speculative use of the technology. In this paper, we present the current state of affairs in relation to NFTs and the cultural heritage sector, identifying challenges, whilst highlighting opportunities that they create for revenue generation, in order to help address the ever-increasing financial challenges of galleries and museums.

Purpose - Since its introduction in 2006, messages posted to the microblogging system Twitter have provided a rich dataset for researchers, leading to the publication of over a thousand academic papers. This paper aims to identify this published work and to classify it in order to understand Twitter based research.Design methodology approach - Firstly the papers on Twitter were identified. Secondly, following a review of the literature, a classification of the dimensions of microblogging research was established. Thirdly, papers were qualitatively classified using open coded content analysis, based on the paper's title and abstract, in order to analyze method, subject, and approach.Findings - The majority of published work relating to Twitter concentrates on aspects of the messages sent and details of the users. A variety of methodological approaches is used across a range of identified domains.Research limitations implications - This work reviewed the abstracts of all papers available via database search on the term \"Twitter\" and this has two major implications: the full papers are not considered and so works may be misclassified if their abstract is not clear; publications not indexed by the databases, such as book chapters, are not included. The study is focussed on microblogging, the applicability of the approach to other media is not considered.Originality value - To date there has not been an overarching study to look at the methods and purpose of those using Twitter as a research subject. The paper's major contribution is to scope out papers published on Twitter until the close of 2011. The classification derived here will provide a framework within which researchers studying Twitter related topics will be able to position and ground their work.

Digital Humanities is becoming an increasingly popular focus of academic endeavour. There are now hundreds of Digital Humanities centres worldwide and the subject is taught at both postgraduate and undergraduate level. Yet the term 'Digital Humanities' is much debated. This reader brings together, for the first time, in one core volume the essential readings that have emerged in Digital Humanities. We provide a historical overview of how the term 'Humanities Computing' developed into the term 'Digital Humanities', and highlight core readings which explore the meaning, scope, and implementation of the field. To contextualize and frame each included reading, the editors and authors provide a commentary on the original piece. There is also an annotated bibliography of other material not included in the text to provide an essential list of reading in the discipline. This text will be required reading for scholars and students who want to discover the history of Digital Humanities through its core writings, and for those who wish to understand the many possibilities that exist when trying to define Digital Humanities.

How can digitised assets of Galleries, Libraries, Archives and Museums be reused to unlock new value? What are the implications of viewing large-scale cultural heritage data as an economic resource, to build new products and services upon? Drawing upon valuation studies, we reflect on both the theory and practicalities of using mass-digitised heritage content as an economic driver, stressing the need to consider the complexity of commercial-based outcomes within the context of cultural and creative industries. However, we also problematise the act of considering such heritage content as a resource to be exploited for economic growth, in order to inform how we consider, develop, deliver and value mass-digitisation. Our research will be of interest to those wishing to understand a rapidly changing research and innovation landscape, those considering how to engage memory institutions in data-driven activities and those critically evaluating years of mass-digitisation across the heritage sector.

There is great practical and scholarly interest in the identification of pigments in works of art. This paper compares the effectiveness of the widely used Raman Spectroscopy (RS), with hyperspectral imaging (HSI), a reflectance imaging technique, to evaluate the reliability of HSI for the identification of pigments in historic works of art and to ascertain if there are any benefits from using HSI or a combination of both. We undertook a case study based on six Armenian illuminated manuscripts (eleventh–eighteenth centuries CE) in the Bodleian Library, University of Oxford. RS, and HSI (380–1000 nm) were both used to analyse the same 10 folios, with the data then used to test the accuracy and efficiency of HSI against the known results from RS using reflectance spectra reference databases compiled by us for the project. HSI over the wavelength range 380–1000 nm agreed with RS at best 93% of the time, and performance was enhanced using the SFF algorithm and by using a database with many similarities to the articles under analysis. HSI is significantly quicker at scanning large areas, and can be used alongside RS to identify and map large areas of pigment more efficiently than RS alone. HSI therefore has potential for improving the speed of pigment identification across manuscript folios and artwork but must be used in conjunction with a technique such as RS.

Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. This paper aims to identify published work relating to Twitter within the fields indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Papers on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper's title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain, and aspect. As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focused on Twitter (the others referring to it tangentially). The early Twitter focused papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge discovery methods and data mining techniques to understand vast quantities of tweets: the study of Twitter is becoming quantitative research. This work is to the best of our knowledge the first overview study of medical related research based on Twitter and related microblogging. We have used 5 dimensions to categorize published medical related research on Twitter. This classification provides a framework within which researchers studying development and use of Twitter within medical related research, and those undertaking comparative studies of research, relating to Twitter in the area of medicine and beyond, can position and ground their work.

PurposeThis paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.Design/methodology/approachIn undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.FindingsCatalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.Originality/valueOur research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to provide robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. The tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.

Handwritten Text Recognition (HTR) technology is now a mature machine learning tool, becoming integrated in the digitisation processes of libraries and archives, speeding up the transcription of primary sources and facilitating full text searching and analysis of historic texts at scale. However, research into how HTR is changing our information environment is scant. This paper presents a systematic literature review regarding how researchers are using one particular HTR platform, Transkribus, to indicate the domains where HTR is applied, the approach taken, and how the technology is understood. 381 papers from 2015 to 2020 were gathered from Google Scholar, Scopus, and Web of Science, then grouped and coded into categories using quantitative and qualitative approaches. Published research that mentions Transkribus is international and rapidly growing. Transkribus features primarily in archival and library science publications, while a long tail of broad and eclectic disciplines, including history, computer science, citizen science, law and education, demonstrate the wider applicability of the tool. The most common paper categories were humanities applications (67%), technological (25%), users (5%) and tutorials (3%). This paper presents the first overarching review of HTR as featured in published research, while also elucidating how HTR is affecting the information environment.