Generative systems can produce fluent museum prose, but fluency does not show whether a sentence is warranted by an object record. This article proposes Narrative Licence, a protocol that classifies each candidate sentence as ATTESTED, INFERRED or NOT LICENSED against named metadata fields and withholds unlicensed sentences before public release. The framework comprises an ordered decision procedure, a field-to-licence map, three evidence-partitioned institutional voices, and a matched comparison of an unconstrained prompt with a licence-bounded pipeline. A completed pre-generation audit of the public TimeTravel release (10,250 records) found quoted inscriptions in 14.9%, recorded findspots in 68.2% and all ten licence-bearing fields in 2.9% of records, and showed that 64% of quoted inscriptions come from coin records. A deterministic working sample of 48 records was drawn in three strata. A worked example traces one record from source fields to released gallery text. The planned confirmatory evaluation will estimate the paired difference in released unlicensed-sentence rate, with coherence and readability as secondary outcomes. No effectiveness result is reported. Whether the protocol reduces unlicensed claims without degrading narrative quality remains to be tested.
Generative artificial intelligence (Gen-AI) is a form of AI technology that can automatically generate new content, such as text, images, and audio, based on prompts. This study explores the opportunities and structural challenges of using Gen-AI to promote sustainable design in the field of intangible cultural heritage (ICH) from the perspectives of ICH designers and relevant experts. The research employed a variety of methods, including interviews (n= 40), grounded theory, the Delphi method (n = 20), exploratory factor analysis (n = 312), confirmatory factor analysis (n = 324), and expert interviews (n = 10). The study evaluated deep-seated issues arising from Gen-AI’s intervention in ICH design practices, such as cultural subjectivity, knowledge, power relations, and value circulation, through the lenses of Cultural Ecology, Extraction of Intangible Cultural Heritage Genes, Sustainable Communication, Technology Generation, and Human–Machine Collaborative Design. The results suggest that Gen-AI’s empowerment involves a tension between technological generative capabilities and cultural accuracy, as well as systemic-level transformations such as balancing communication efficiency with cultural depth and human–machine collaboration, and re-configuring the designer’s role.
Raw material supply to pottery workshops may reflect wider regional connections of past communities. This study investigates the provenance of granitoid temper in Late Sarmatian micaceous–pebbly pottery from Tázlár–Templomhegy, Hungary. Previous petrographic analysis suggested that these ceramics were produced at the Nagymágocs–Paptanya pottery workshop, Hungary, but the source of the rock temper was undetermined. Cathodoluminescence (CL) microscopy and spectroscopy were used to examine the luminescence characteristics of K-feldspar and plagioclase in the temper and reference material, including potential source granitoids and archaeological rock samples from the workshop site. Spectral parameters were evaluated using principal component analysis, hierarchical cluster analysis and linear discriminant analysis. CL microscopic observations, spectral data and statistical analyses indicated the greatest similarity between the temper and the Codru granitoid, Romania. The proximity of the workshop to the Codru outcrops, together with the archaeological and historical context, further supports this provenance. CL microscopy and spectroscopy of feldspars appeared promising for differentiating granitoid units. Plagioclase provided more effective discrimination than K-feldspar, although combining their results led to a more comprehensive interpretation. Using CL microscopy and spectroscopy of feldspars with multivariate statistical methods offers a promising approach for determining the provenance of granitoid temper in archaeological ceramics.
Museum fatigue can weaken visitor experience and learning outcomes, yet post-visit questionnaires and controlled experiments often miss early, low-intensity behavioral changes during natural visits. This study proposes a Micro-behavioral Load Decoding Framework (MLD Framework) linking natural-video collection, micro-behavior recognition, action-group representation, load-direction indicators and spatial behavioral signature recognition. Twelve fatigue-related micro-behaviors were grouped into body-load-related, cognitive-load-related and mixed-load action groups, aggregated as events per 100 visitor observations across eight spatial units, and compared with hall-level questionnaire references. The results show distinguishable combinations of body load, cognitive load and behavioral regulation demand across halls. Some spaces showed low overall load, others showed a dominant load dimension, and others showed simultaneous increases in multiple load-related behaviors. These spatial behavioral load signatures describe relative visitor responses across exhibition environments and reveal spatial couplings among physical exertion, cognitive processing and self-regulation. Natural-video micro-behaviors provide non-invasive process evidence for comparing hall-level load structures and diagnosing exhibition rhythm, information density and restorative support.
Heritage can be experienced in many ways. One way is to experience heritage through heritage trails and site visits. Another way is to visit a museum. Artefacts are usually presented in museums. However, they often lack context and real environments. Words cannot describe the whole picture. As a result, visitors cannot connect those artefacts with the places where they were discovered. With AR technology, visitors can better understand the relationship between museum objects and their original context. The purpose of this study is to provide a systematic review of virtual reality (VR) and augmented reality (AR) in museums and related contexts. We used a bibliometric method as a supplementary analysis. PRISMA procedure was used. The search keywords were “virtual reality” or “VR” or “augmented reality” or “AR” or “mixed reality” or “MR” or “extended reality” or “XR” or “immersive reality” or “metaverse” and “museum*”. We searched the Web of Science and Scopus databases in May 2026. In total, 208 publications were identified from Scopus and Web of Science with the time bound of 2000 to 2026. Most articles were published after 2020 and focus on VR and AR technologies. Most publications appear in journals in the fields of cultural heritage, tourism, and technology. The current research themes in VR/AR in museum contexts are extended reality (XR) technologies for cultural and heritage preservation; immersive experience, presence, and visitor engagement; authenticity; education, knowledge acquisition, and learning effectiveness; emotional engagement and well-being; acceptance and adoption of the technology; as well as accessible tourism for people with disabilities. Future research directions include new theoretical models, privacy, gamification, educational learning, and use of artificial intelligence in museums.
