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This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC) which comprises over 100 poetic texts with around 2 million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot's poem 'How Lisa Loved the King' and James Joyce's 'Chamber Music', concerning e.g. lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Natural Language Processing or Neurocognitive Poetics, e.g. as training and test corpus, or for stimulus development and control. Comment: 27 pages, 4 figures

In 2018, the European Strategic Forum for research infrastructures (ESFRI) was tasked by the Competitiveness Council, a configuration of the Council of the EU, to develop a common approach for monitoring of Research Infrastructures' performance. To this end, ESFRI established a working group, which has proposed 21 Key Performance Indicators (KPIs) to monitor the progress of the Research Infrastructures (RIs) addressed towards their objectives. The RIs were then asked to assess their relevance for their institution. The paper aims to identify the relevance of certain indicators for particular groups of RIs by using cluster and discriminant analysis. This could contribute to development of a monitoring system, tailored to particular RIs. To obtain a typology of the RIs, we first performed cluster analysis of the RIs according to their properties, which revealed clusters of RIs with similar characteristics, based on to the domain of operation, such as food, environment or engineering. Then, discriminant analysis was used to study how the relevance of the KPIs differs among the obtained clusters. This analysis revealed that the percentage of RIs correctly classified into five clusters, using the KPIs, is 80%. Such a high percentage indicates that there are significant differences in the relevance of certain indicators, depending on the ESFRI domain of the RI. The indicators therefore need to be adapted to the type of infrastructure. It is therefore proposed that the Strategic Working Groups of ESFRI addressing specific domains should be involved in the tailored development of the monitoring of pan-European RIs. Comment: 15 pages, 8 tables, 3 figures

Digital technologies, such as the Internet and Artificial Intelligence, are part of our daily lives, influencing broader aspects of our way of life, as well as the way we interact with the past. Having dramatically changed the ways in which knowledge is produced and consumed, the algorithmic age has also radically changed the relationship that the general public has with History. Fields of History such as Public and Oral History have particularly benefitted from the rise of digital culture. How does our digital culture affect the way we think, study, research and teach the past, as historical evidence spreads rapidly in the public sphere? How do digital technologies promote the study, writing and teaching of History? What should historians, students of history and pre-service history teachers be critically aware of, when swarmed with digitized or born-digital content, constantly growing on the Internet? And while these changes are now visible globally, how is the discipline of History situated within the digital transformation rapidly advancing in Greece? Finally, what are the consequences of these changes for History as a subject taught at Greek secondary schools? These are some of the issues raised in the text that follows, which is part of the course materials of the undergraduate course offered during winter semester 2020-2021 at the School University of Athens, School of Philosophy, Pedagogy, Psychology. Course Title: 'Pedagogics of History: Theory and Practice', Academic Institution: School of Philosophy-Pedagogy-Psychology, University of Athens. Comment: 47 pages, in Greek, 8 figures

The digital format opens up new possibilities for interaction with monographic publications. In particular, annotation tools make it possible to broaden the discussion on the content of a book, to suggest new ideas, to report errors or inaccuracies, and to conduct open peer reviews. However, this requires the support of the users who might not yet be familiar with the annotation of digital documents. This paper will give concrete examples and recommendations for exploiting the potential of annotation in academic research and teaching. After presenting the annotation tool of Hypothesis, the article focuses on its use in the context of HIRMEOS (High Integration of Research Monographs in the European Open Science Infrastructure), a project aimed to improve the Open Access digital monograph. The general line and the aims of a post-peer review experiment with the annotation tool, as well as its usage in didactic activities concerning monographic publications are presented and proposed as potential best practices for similar annotation activities.

We propose a morphologically informed model for named entity recognition, which is based on LSTM-CRF architecture and combines word embeddings, Bi-LSTM character embeddings, part-of-speech (POS) tags, and morphological information. While previous work has focused on learning from raw word input, using word and character embeddings only, we show that for morphologically rich languages, such as Bulgarian, access to POS information contributes more to the performance gains than the detailed morphological information. Thus, we show that named entity recognition needs only coarse-grained POS tags, but at the same time it can benefit from simultaneously using some POS information of different granularity. Our evaluation results over a standard dataset show sizable improvements over the state-of-the-art for Bulgarian NER. Comment: named entity recognition; Bulgarian NER; morphology; morpho-syntax

Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cross-lingual and cross-cultural communication are still omnipresent. Language Technologies (LTs) are a powerful means to break down these barriers. While the last decade has seen various initiatives that created a multitude of approaches and technologies tailored to Europe's specific needs, there is still an immense level of fragmentation. At the same time, AI has become an increasingly important concept in the European Information and Communication Technology area. For a few years now, AI, including many opportunities, synergies but also misconceptions, has been overshadowing every other topic. We present an overview of the European LT landscape, describing funding programmes, activities, actions and challenges in the different countries with regard to LT, including the current state of play in industry and the LT market. We present a brief overview of the main LT-related activities on the EU level in the last ten years and develop strategic guidance with regard to four key dimensions. Comment: Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020). To appear

FINALER ARTIKEL: https://www.oabooks.de/wp-content/uploads/2020/10/Dang_FDM_MontageAV2020.pdf; Forschungsdatenmanagement (FDM) – sowohl als zentraler Begriff als auch grundständige Praxis – gewinnt mehr und mehr auch in der Film- und Medienwissenschaft an Bedeutung. Ausgehend davon, dass FDM zunächst aus der eigenen Disziplin heraus begriffen werden muss, um sich in der aktuellen Auseinandersetzung positionieren und verständigen zu können, sucht der Beitrag eine Perspektive auf film- und medienwissenschaftliche Arbeitsweisen zu eröffnen, die methodische, epistemische, praktische und wissenschaftspolitische Aspekte des FDM in den Blick zu nehmen vermag. Das Ansinnen dieses Textes ist es, die gegenwärtige Omnipräsenz des Begriffs als Chance einer neuen Perspektivierung wahrzunehmen, durch welche die Film- und Medienwissenschaft in hohem Maße profitieren kann.

In this article, we propose a Category Theory approach to (syntactic) interoperability between linguistic tools. The resulting category consists of textual documents, including any linguistic annotations, NLP tools that analyze texts and add additional linguistic information, and format converters. Format converters are necessary to make the tools both able to read and to produce different output formats, which is the key to interoperability. The idea behind this document is the parallelism between the concepts of composition and associativity in Category Theory with the NLP pipelines. We show how pipelines of linguistic tools can be modeled into the conceptual framework of Category Theory and we successfully apply this method to two real-life examples. Comment: Paper submitted to Applied Category Theory 2020 and accepted for Virtual Poster Session

Reproducible research (Reproducible research is when data can be reanalysed taking the same steps and producing the same or similar result) is being implemented at different speeds in different disciplines, and Archaeology, as a discipline that sits at the intersection of the sciences and humanities, is at the start of this journey. Enabling reproducibility of your work by others is an important step in ensuring research quality. There are currently many barriers to moving towards reproducible research such as upskilling researchers in the practices, software and infrastructure needed to do reproducible research and also the need to address how we can, as a discipline, deal with issues like sensitive data. In this article, we seek to introduce reproducible research in an understandable manner so that archaeological researchers can learn where and how to start with this approach. We describe what reproducible archaeological research can look like and suggest three different computational skill levels of constructing reproducible research workflows (a research workflow is the different parts of a research lifecycle such as data collection, data analysis, data archiving, etc, and making all stages reproducible by using a history tracking system (version control) and transparent documation). Finally, in an extensive appendix, we address common questions about reproducible research to remove the stigma about these issues and suggest ways to overcome them.

The concept of literary genre is a highly complex one: not only are different genres frequently defined on several, but not necessarily the same levels of description, but consideration of genres as cognitive, social, or scholarly constructs with a rich history further complicate the matter. This contribution focuses on thematic aspects of genre with a quantitative approach, namely Topic Modeling. Topic Modeling has proven to be useful to discover thematic patterns and trends in large collections of texts, with a view to class or browse them on the basis of their dominant themes. It has rarely if ever, however, been applied to collections of dramatic texts. In this contribution, Topic Modeling is used to analyze a collection of French Drama of the Classical Age and the Enlightenment. The general aim of this contribution is to discover what semantic types of topics are found in this collection, whether different dramatic subgenres have distinctive dominant topics and plot-related topic patterns, and inversely, to what extent clustering methods based on topic scores per play produce groupings of texts which agree with more conventional genre distinctions. This contribution shows that interesting topic patterns can be detected which provide new insights into the thematic, subgenre-related structure of French drama as well as into the history of French drama of the Classical Age and the Enlightenment. Comment: 11 figures