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Background: The air traffic management (ATM) system has historically coped with a global increase in traffic demand ultimately leading to increased operational complexity. When dealing with the impact of this increasing complexity on system safety it is crucial to automatically analyse the losses of separation (LoSs) using tools able to extract meaningful and actionable information from safety reports. Current research in this field mainly exploits natural language processing (NLP) to categorise the reports,with the limitations that the considered categories need to be manually annotated by experts and that general taxonomies are seldom exploited. Methods: To address the current gaps,authors propose to perform exploratory data analysis on safety reports combining state-of-the-art techniques like topic modelling and clustering and then to develop an algorithm able to extract the Toolkit for ATM Occurrence Investigation (TOKAI) taxonomy factors from the free-text safety reports based on syntactic analysis. TOKAI is a tool for investigation developed by EUROCONTROL and its taxonomy is intended to become a standard and harmonised approach to future investigations. Results: Leveraging on the LoS events reported in the public databases of the Comisión de Estudio y Análisis de Notificaciones de Incidentes de Tránsito Aéreo and the United Kingdom Airprox Board,authors show how their proposal is able to automatically extract meaningful and actionable information from safety reports,other than to classify their content according to the TOKAI taxonomy. The quality of the approach is also indirectly validated by checking the connection between the identified factors and the main contributor of the incidents. Conclusions: Authors' results are a promising first step toward the full automation of a general analysis of LoS reports supported by results on real-world data coming from two different sources. In the future,authors' proposal could be extended to other taxonomies or tailored to identify factors to be included in the safety taxonomies.

Although lexical borrowing is an important aspect of language evolution, there have been few attempts to automate the identification of borrowings in lexical datasets. Moreover, none of the solutions which have been proposed so far identify borrowings across multiple languages. This study proposes a new method for the task and tests it on a newly compiled large comparative dataset of 48 South-East Asian languages from Southern China. The method yields very promising results, while it is conceptually straightforward and easy to apply. This makes the approach a perfect candidate for computer-assisted exploratory studies on lexical borrowing in contact areas.

International audience; Named entity processing over historical texts is more and more being used due to the massive documents and archives being stored in digital libraries. However, due to the poor annotated resources of historical nature, information extraction performances fall behind those on contemporary texts. In this paper, we introduce the development of the NewsEye resource, a multilingual dataset for named entity recognition and linking enriched with stances towards named entities. The dataset is comprised of diachronic historical newspaper material published between 1850 and 1950 in French, German, Finnish, and Swedish. Such historical resource is essential in the context of developing and evaluating named entity processing systems. It evenly allows enhancing the performances of existing approaches on historical documents which enables adequate and efficient semantic indexing of historical documents on digital cultural heritage collections.

The primary mission of cultural institutions, including heritage sites and museums, is to perform and perpetuate Cultural Heritage (CH) by ideally transforming audiences into stewards of that heritage. In recent years, these institutions have increasingly turned to Mixed Reality (MR) technologies to expand and democratize public access to Cultural Heritage - a trend that is called upon to accelerate with COVID-19 - because these technologies provide opportunities for more remote outreach, and moreover, can make partial remains or ruins more relatable to the public. But as emerging evaluations indicate, existing MR intangible and tangible Digital Cultural Heritage (DCH) applications are largely proving inadequate to engaging audiences beyond an initial fascination with the immersive 3D visualization of heritage sites and artefacts owing in part to misguided storytelling or non-compelling narratives. They fail to effectively communicate the significance of Cultural Heritage to audiences and impress upon them its value in a lasting way due to their overreliance on an education-entertainment-touristic consumption paradigm. Building on the recent case made for Literature-based MR Presence, this article examines how the literary tradition of travel narratives can be recruited to enhance presence and embodiment, and further elicit aesthetic experiences in Digital Cultural Heritage applications by drawing on recent findings from the fields of Extended Reality (XR), cognitive literary science and new museology. The projected effects of this innovative approach are not limited to an increase in audience engagement on account of a greater sense of presence and embodiment. This approach is also expected to prompt a different kind of public involvement characterized by a personal valuation of the heritage owing to aesthetic experience. As the paper ultimately discusses, this response is more compatible both with MR applications' default mode of usership, and with newly emerging conceptions of a user-centered museum (e.g., the Museum 3.0), thereby providing a narrative roadmap for future Virtual Museum (VM) applications better suited to the primary mission of transmitting and perpetuating Cultural Heritage. © Bertrand, Vassiliadi, Zikas, Geronikolakis and Papagiannakis.

In order to remain alive and relevant, cultural heritage sites have to react and adapt to changing context in a coherent manner, i.e., in a way that is in line with the memory and identity of the place. The incoherent changes, i.e., the transformations that according to the local community do not agree with a character of a place, can be destructive for the long-term vitality of urban cultural heritage. In this study, we test which factors influence social acceptance of different alternations within the context of urban historical gardens that might, in turn, ensure the resilience of the place. Our study focuses on the intangible qualities of the place measured by intrinsic value, perceived essentialism and anti-essentialism as important predictors shaping the response to change. The correlational study was conducted using an online questionnaire designed to empirically grasp intangible qualities of cultural heritage sites. Five hundred twenty-nine responses were included in the analysis. The study shows that perceived historic value, inherent value (uniqueness and importance of the place) and (anti-)essentialist character of a place capture the differences between parks well and enables the finding of interventions that are coherent with a site’s genius loci. Measuring intangible qualities of urban gardens can help to design changes that find higher approval among local community members and users of the site. We discuss how the analysis of an intrinsic value and essentialism allows for planning better spatial interventions that align with the human-centered approach to urban development.

AbstractTonality is one of the most central theoretical concepts for the analysis of Western classical music. This study presents a novel approach for the study of its historical development, exploring in particular the concept of mode. Based on a large dataset of approximately 13,000 musical pieces in MIDI format, we present two models to infer both the number and characteristics of modes of different historical periods from first principles: a geometric model of modes as clusters of musical pieces in a non-Euclidean space, and a cognitively plausible Bayesian model of modes as Dirichlet distributions. We use the geometric model to determine the optimal number of modes for five historical epochs via unsupervised learning and apply the probabilistic model to infer the characteristics of the modes. Our results show that the inference of four modes is most plausible in the Renaissance, that two modes–corresponding to major and minor–are most appropriate in the Baroque and Classical eras, whereas no clear separation into distinct modes is found for the 19th century.

AbstractScientific writings, as one essential part of human culture, have evolved over centuries into their current form. Knowing how scientific writings evolved is particularly helpful in understanding how trends in scientific culture developed. It also allows us to better understand how scientific culture was interwoven with human culture generally. The availability of massive digitized texts and the progress in computational technologies today provide us with a convenient and credible way to discern the evolutionary patterns in scientific writings by examining the diachronic linguistic changes. The linguistic changes in scientific writings reflect the genre shifts that took place with historical changes in science and scientific writings. This study investigates a general evolutionary linguistic pattern in scientific writings. It does so by merging two credible computational methods: relative entropy; word-embedding concreteness and imageability. It thus creates a novel quantitative methodology and applies this to the examination of diachronic changes in the Philosophical Transactions of Royal Society (PTRS, 1665–1869). The data from two computational approaches can be well mapped to support the argument that this journal followed the evolutionary trend of increasing professionalization and specialization. But it also shows that language use in this journal was greatly influenced by historical events and other socio-cultural factors. This study, as a “culturomic” approach, demonstrates that the linguistic evolutionary patterns in scientific discourse have been interrupted by external factors even though this scientific discourse would likely have cumulatively developed into a professional and specialized genre. The approaches proposed by this study can make a great contribution to full-text analysis in scientometrics.

This poster has been awarded with the Best Poster Award at DARIAH2020 virtual annual event https://twitter.com/dariaheu/status/1327290958971609090?s=21 In order to provide the global community of scholars working in this field with a greater understanding of the current Spanish scenario, LINHD has recently promoted a research on the evolution of Digital Humanities in Spain in the last 25 years, a timeframe comparable with Unsworth first formulation of scholarly primitives. More than 1,000 records have been mapped, distributed as follow: 577 researchers; 368 projects; 88 resources; 9 post-graduate courses; and 8 specialised journals. Digital resources (i.e. repositories of documents, collections of artefacts, crowdsourcing platforms, dictionaries, databases, etc.), which are the object of this poster, have been produced, most of the time, with the aim to publish a service to improve the basic of day-to-day research workflow in the Humanities. Our initial objectives were: to classify and describe the digital resources mapped according with the classical and new scholarly primitives, in order to highlight presences, absence and recurring associations of these categories; To visualize the relationships between scholarly primitives and other dimensions in our data, like discipline and typology. to identify how the introduction of digital tools and methods has affected the basic functions of research in the Humanities in Spain over time. Data analysed is part of a larger dataset that can be downloaded at https://doi.org/10.5281/zenodo.3893546 The whole dataset has been extensively analysed in https://doi.org/10.3145/epi.2020.nov.01

One of the keys for supervised learning techniques to succeed resides in the access to vast amounts of labelled training data. The process of data collection, however, is expensive, time- consuming, and application dependent. In the current digital era, data can be collected continuously. This continuity renders data annotation into an endless task, which potentially, in problems such as emotion recognition, requires annotators with different cultural backgrounds. Herein, we study the impact of utilising data from different cultures in a semi-supervised learning ap- proach to label training material for the automatic recognition of arousal and valence. Specifically, we compare the performance of culture-specific affect recognition models trained with man- ual or cross-cultural automatic annotations. The experiments performed in this work use the dataset released for the Cross- cultural Emotion Sub-challenge of the Audio/Visual Emotion Challenge (AVEC) 2019. The results obtained convey that the cultures used for training impact on the system performance. Furthermore, in most of the scenarios assessed, affect recogni- tion models trained with hybrid solutions, combining manual and automatic annotations, surpass the baseline model, which was exclusively trained with manual annotations.

AbstractMany believe that the quality of a scientific publication is as good as the science it cites. However, quantifications of how features of reference lists affect citations remain sparse. We examined seven numerical characteristics of reference lists of 50,878 research articles published in 17 ecological journals between 1997 and 2017. Over this period, significant changes occurred in reference lists’ features. On average, more recent papers have longer reference lists and cite more high Impact Factor papers and fewer non-journal publications. We also show that highly cited articles across the ecological literature have longer reference lists, cite more recent and impactful references, and include more self-citations. Conversely, the proportion of ‘classic’ papers and non-journal publications cited, as well as the temporal span of the reference list, have no significant influence on articles’ citations. From this analysis, we distill a recipe for crafting impactful reference lists, at least in ecology.