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The authors also acknowledge the support and collaboration of many other colleagues in their respective institutes, research communities and IT Infrastructures, together with the funding received by these from many different sources. These include but are not limited to the following: (i) The Worldwide LHC Computing Grid (WLCG) project is a global collaboration of more than 170 computing centres in 43 countries, linking up national and international grid infrastructures. Funding is acknowledged from many national funding bodies and we acknowledge the support of several operational infrastructures including EGI, OSG and NDGF/NeIC. (ii) EGI acknowledges the funding and support received from the European Commission and the many National Grid Initiatives and other members. EOSC-hub receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 777536. (iii) The work leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 730941 (AARC2). (iv) Work on the development of ESGF's identity management system has been supported by The UK Natural Environment Research Council and funding from the European Union's Seventh Framework Programme for research, technological development and demonstration through projects IS-ENES (grant agreement no 228203) and IS-ENES2 (grant agreement no 312979). (v) Ludek Matyska and Michal Prochazka acknowledge funding from the RI ELIXIR CZ project funded by MEYS Czech Republic No. LM2015047. (vi) Scott Koranda acknowledges support provided by the United States National Science Foundation under Grant No. PHY-1700765. (vii) GÉANT Association on behalf of the GN4 Phase 2 project (GN4-2).The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 731122(GN4-2). (viii) ELIXIR acknowledges support from Research Infrastructure programme of Horizon 2020 grant No 676559 EXCELERATE. (ix) CORBEL life science cluster acknowledges support from Horizon 2020 research and innovation programme under grant agreement No 654248. (x) Mirjam van Daalen acknowledges that the research leading to this result has been supported by the project CALIPSOplus under the Grant Agreement 730872 from the EU Framework Programme for Research and Innovation HORIZON 2020. (xi) EISCAT is an international association supported by research organisations in China (CRIRP), Finland (SA), Japan (NIPR), Norway (NFR), Sweden (VR), and the United Kingdom (NERC). This white-paper expresses common requirements of Research Communities seeking to leverage Identity Federation for Authentication and Authorisation. Recommendations are made to Stakeholders to guide the future evolution of Federated Identity Management in a direction that better satisfies research use cases. The authors represent research communities, Research Services, Infrastructures, Identity Federations and Interfederations, with a joint motivation to ease collaboration for distributed researchers. The content has been edited collaboratively by the Federated Identity Management for Research (FIM4R) Community, with input sought at conferences and meetings in Europe, Asia and North America.

Cultural Heritage and Digital Humanities have become major application fields of Linked Data and Semantic Web technologies. This editorial introduces the special issue of the Semantic Web (SWJ) journal on Semantic Web for Cultural Heritage. In total 30 submissions for the call of papers were received, of which 11 were selected for publication. The papers cover a wide spectrum of modelled topics related to language, reading and writing, narratives, historical events and cultural artefacts, while describing reusable methodologies and tools for cultural data management. This issue indicates and demonstrates the high potential of Semantic Web technologies for applications in the Cultural Heritage domain.

This paper describes a corpus of about 3,000 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 two 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, Computational Stylistics, or Neurocognitive Poetics, e.g., as training and test corpus for stimulus development and control in empirical studies.

International audience; En guise de postface, il nous a semblé nécessaire de revenir sur le processus collaboratif de la fabrication de cet ouvrage et de vous confier la genèse de ce projet. Tout est parti d'un constat pragmatique, de nos situations quotidiennes de travail : le/la chercheur·e qui produit ou utilise des données a besoin de réponses concrètes aux questions auxquelles il/elle est confronté·e sur son terrain comme lors de tous ses travaux de recherche. Produire, exploiter, diffuser, partager ou éditer des sources numériques fait aujourd'hui partie de notre travail ordinaire. La rupture apportée par le développement du web et l'arrivée du format numérique ont largement facilité la diffusion et le partage des ressources (documentaires, textuelles, photographiques, sonores ou audiovisuelles...) dans le monde de la recherche et, au-delà, auprès des citoyens de plus en plus curieux et intéressés par les documents produits par les scientifiques.

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. named entity recognition; Bulgarian NER; morphology; morpho-syntax

The interdisciplinary field known as digital humanities (DH) is represented in various forms in the teaching and research practiced in iSchools. Building on the work of an iSchools organization committee charged with exploring digital humanities curricula, we present findings from a series of related studies exploring aspects of DH teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Through a survey of iSchool programs and an online DH course registry, we investigate the various education models for DH training found in iSchools, followed by a detailed look at DH courses and curricula, explored through analysis of course syllabi and course descriptions. We take a brief look at collaborative disciplines with which iSchools cooperate on DH research projects or in offering DH education. Next, we explore DH careers through an analysis of relevant job advertisements. Finally, we offer some observations about the management and administrative challenges and opportunities related to offering a new iSchool DH program. Our results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives.

This article reports on the technical development and testing of the basic components of a virtual environment platform that could be used for the cross-disciplinary study of complex urban realities, such as the historic city of Nicosia, Cyprus - the last divided capital of Europe. This platform captures data of virtual visitors' movements in space, and the article suggests that these data could help better understand the impact of planning scenarios and design interventions in open public spaces that used to be popular among the citizens of the historic city. The article presents how this platform uses interaction and immersion opportunities to engage citizens and stakeholders in the management of public open spaces that are associated with built heritage. Crowd simulation is discussed as a computational technique that when is combined with the presented virtual environment platform, and under the right conditions, would contribute to a digital practice for small-scale urban modelling. However, it is beyond the scope of this technical note to provide a full empirical testing and validation of the presented immersive virtual environment.

Highlights, scribbling, and marginal notes: Annotation is often a private practice that we only occasionally share with others, or even more rarely share publicly. Once considered fundamental to hypertext systems, the potential of annotating digital documents is often overlooked in today's technology. As data commonly leaves our devices when collaborating, further questions arise on digital ownership and privacy. In this thesis, I examine the question of how both ownership and privacy can be ensured in the context of Digital Humanities research, which increasingly leverages interoperable infrastructures and Linked Open Data. In an explorative study, I first investigate the aspects of real-time collaboration in research tools, followed by an examination of institutional services on Peer-to-Peer (P2P) networks. By establishing interoperability between such networks and the web, I then propose two approaches for bridging those networks and strengthening privacy, ownership, and private collaboration following the paradigm of local-first software. I argue that by balancing the autonomy of peers and the determinism of the web, gateways can translate across the separation of both networks while supporting peers by providing archiving and data availability. This enables researchers to perform private and collaborative annotation, while the underlying data can be embedded into existing workflows due to the bridge between both systems. Future work concerns the viability of this approach in scholarly environments and further research on the usability of distributed systems in the academic context.

This paper introduces the Global Medieval Sourcebook (GMS), an online repository of medieval texts and translations with an open network of contributors. Drawing on our experience developing and building this project in two phases over six years, we reflect on questions regarding editorial, curatorial, and translation practices, and on technical issues involved in the preparation, display, and preservation of texts for online publication. As an example of a scholar-led digital project, the trajectory of the GMS has broad relevance for scholars planning digital curation work of their own. In particular, it offers a salutary example of the infrastructural barriers to sustaining collaborative digital work and a possible model for preserving a concluded project.

This paper explores key issues in the development of open access to research data. The use of digital means for developing, storing and manipulating data is creating a focus on ‘data-driven science’. One aspect of this focus is the development of ‘open access’ to research data. Open access to research data refers to the way in which various types of data are openly available to public and private stakeholders, user communities and citizens. Open access to research data, however, involves more than simply providing easier and wider access to data for potential user groups. The development of open access requires attention to the ways data are considered in different areas of research. We identify how open access is being unevenly developed across the research environment and the consequences this has in terms of generating data gaps. Data gaps refer to the way data becomes detached from published conclusions. To address these issues, we examine four main areas in developing open access to research data: stakeholder roles and values; technological requirements for managing and sharing data; legal and ethical regulations and procedures; institutional roles and policy frameworks. We conclude that problems of variability and consistency across the open access ecosystem need to be addressed within and between these areas to ensure that risks surrounding a data gap are managed in open access. 11 authors. Missing: Sally Wyatt