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This volume documents the Proceedings of the 8th Workshop on Workshop on Linked Data in Linguistics, held on Friday teh 24th of June as part of the LREC 2022 conference (International Conference on Language Resources and Evaluation). Since its inception, the workshop series on Linked Data in Linguistics (LDL) established itself as the main venue for discussing how Linked Open Data (LOD) and semantic web technologies can be used for processing, analysing, publishing, and managing linguistic data. This includes the fields of natural language processing (NLP), language resources (LRs), lexicography and digital humanities (DH), and has been leading to the development of linguistic data science as a new area of study. The LDL workshop series has contributed greatly to the development of the Linguistic Linked Open Data (LLOD) cloud and the development of best practices for publishing and accessing language resources and providing language technology services on the web. Most notably, this includes community standards such as the NLP Interchange Format (NIF), the OntoLex-Lemon model of the W3C Community Group Ontology-Lexica, and numerous domain-specific adaptations and extensions that these models have had an influence on. In addition, there are an increasing number of national, European, and international research projects that build on LLOD technology. These will contribute to its further development and will help ensure the success of this workshop and a high attendance rate. The 10th anniversary edition of the LDL can count on the support of the COST action “NexusLinguarum: European Network for Web-centered Linguistic Data Science”, as well as two Horizon 2020 projects. Firstly, the Prêt-à-LLOD project, which is making linguistic linked open data ready-to-use, and, secondly, the ELEXIS project on building a lexicographic infrastructure.

Iako u Zborniku dominiraju radovi koji se bave naučnicama u prošlosti, kao i njihovim radom, saznanjima, nedovoljnom afirmisanosšću njihovog rada, poteškoćama sa kojima su se suočavale, zbornik zaokružuju radovi koji se bave savremenom situacijom, tj. položajem žena u akademskoj zajednici danas i svim teškoćama koje i same akterke katkada teško detektuju i prepoznaju. Patrijarhalni mehanizmi prožimaju društvo u kome živimo na različitim nivoima, a sami principi koji vladaju u akademskom svetu – u kojima sve više važe pravila liberalnog kapitalizma i ideje o „upotrebljivosti“ nauke i merljivosti rezultata – cementiraju i prikrivaju davno odomaćen diskriminatorski odnos prema ženama i prema naučničkom glasu i diskursu koji odudara od dominantne paradigme. Stoga su neophodni neprekidni napori da se ženski glas u nauci čuje, a položaj naučnica stalno unapređuje i popravlja. Зборник радова Етнографског института САНУ 34 / Collection of Papers of Institute of Ethnography SASA 34

Research funding organizations, particularly at international level, are increasingly promoting the\ud creation and maintenance of open access research infrastructures (RI). These resources have\ud assumed a pivotal role as support for the new open and networked science in their dimension of\ud technical and operational frameworks that allow scientists and stakeholders to collaborate and\ud share scientific data and results. In Social Sciences and Humanities (SSH), the creation and\ud exploitation of open data platforms is still attempting to catch up with longer-standing practices\ud in the “hard sciences” as the resistance to wider data sharing has not yet been completely\ud overcome. This paper aims to describe how a large project, financed by the European\ud Commission, managed the creation of a RI in the field of SSH, showing the steps undertaken to\ud comply with the GDPR regulations and prepare the data for useful sharing and reuse. In this\ud regard, the authors present the case study of the Horizon 2020 “CultureLabs” project, placing\ud emphasis on some specific practical factors that they believe are particularly important for\ud implementing open access principles in the establishment and maintenance of RIs in the new\ud course of science based on sharing and openness. In particular, the authors will focus on creation\ud of “useful” and GDPR-compliant data and the impact on research activities as a result of their\ud (re)utilisation; the control of the data management process; and the compliance with funders’\ud requirements (e.g. in terms of data security). The reflection on the interplay of these aspects,\ud operated through a case study, appears to be crucial in moving away from a merely theoretical\ud approach to addressing the issue of open access, and it hopes to serve as a guide or a warning for\ud those who create and administer open RIs.

This deliverable presents the outcome of the EOSC landscape and policy gap analysis in the countries covered by the project: Czech Republic, The Netherlands, Slovakia, Spain, Poland, Portugal and the United Kingdom. It formulates an initial set of recommendations for national and international stakeholders about the measures for alignment and harmonization of policies to facilitate the implementation of the EOSC. They will be validated and updated in the next phase, based on dedicated liaisons and engagement activities. EOSC-SYNERGY No. 857647. Peer reviewed

This book is a collection of seventeen papers which describe the impact that the ARIADNE project and its successor, ARIADNEplus (2019-2022) have had on the archaeological community, both in Europe and further afield. Each case study has been contributed by organisations involved in the ARIADNE Infrastructure who cover many countries from across Europe as well as Argentina and Japan. These papers were originally presented at the CAA Conference in Krakow, April 2019 and cover aspects such as data management, application of standards and guidelines, the use of CIDOC-CRM and Open Data to name but a few.

This book is a collection of seventeen papers which describe the impact that the ARIADNE project and its successor, ARIADNEplus (2019-2022) have had on the archaeological community, both in Europe and further afield. Each case study has been contributed by organisations involved in the ARIADNE Infrastructure who cover many countries from across Europe as well as Argentina and Japan. These papers were originally presented at the CAA Conference in Krakow, April 2019 and cover aspects such as data management, application of standards and guidelines, the use of CIDOC-CRM and Open Data to name but a few. Printed copies may be requested from Archaeolingua.

Explainable AI is an essential component of a "Human AI", i.e., an AI that expands human experience, instead of replacing it. It will be impossible to gain the trust of people in AI tools that make crucial decisions in an opaque way without explaining the rationale followed, especially in areas where we do not want to completely delegate decisions to machines.

The astonishing and cryptic effectiveness of Deep Neural Networks comes with the critical vulnerability to adversarial inputs - samples maliciously crafted to confuse and hinder machine learning models. Insights into the internal representations learned by deep models can help to explain their decisions and estimate their confidence, which can enable us to trace, characterise, and filter out adversarial attacks.

Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language. The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australia

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.