DOI: 10.3897/rio.9.e115466

Authors: Laurence Benichou, Donat Agosti, Willi Egloff, Elisa Hermann, Mariko Kageyama, Patricia Mergen, Constance Rinaldo, Jutta Buschbom

Abstract: The EU and other states have made legislative efforts to clarify data mining in copyrightable works, but the situation remains obscure and confusing, especially in a globalised field where international legislation can contribute to opacity. The present paper aims at asserting a common position of three communities representing biodiversity sciences and data specialists on this issue and to propose common and best practice guidelines so that they become universally accepted rules.As scientific data users, we take the standpoint that scientific data are not copyrightable and, furthermore, they can be accessed, shared and reused freely. Thus, once legal access has been gained to copyrighted publications, the data within those scholarly publications can be considered to be open data that is freely extractable. This set of recommendations has been reached specifically for scientific use and societal benefits.

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DOI: 10.3897/arphapreprints.e102613

Authors: Slavena Peneva, Kristina Hristova, Anna Sapundzhieva, Boris Barov, Pavel Stoev, Margarita Grudova, Iva Kostadinova

Abstract: This document presents BiCIKL’s recognizable visual identity, including the project logo, visual identity guide, brochure, poster, document, presentation templates and website design and functionality developed in the first three months. These materials will ensure that BiCIKL is communicated effectively and professionally with the aim to raise awareness and build a community from the start of the project.The modern and user-friendly public website (bicikl-project.eu) provides an easy-to-navigate, continuously updated platform allowing fast access to general information about BiCIKL and its activities, operating on several levels. It also prominently features the participating project partners and Research Infrastructures and their extensive service portfolio.

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DOI: 10.3897/arphapreprints.e102612

Authors: Lyubomir Penev, Mariya Dimitrova, Georgi Zhelezov, Teodor Georgiev

Abstract: To the best of our knowledge, OpenBiodiv is the first production-stage  semantic  system running on top  of  a  reasonably-sized biodiversity knowledge graph. It stores biodiversity data in  a semantic interlinked format and offers facilities for working with it (Senderov et Penev 2016, Senderov et al.   2018, Penev et al. 2019, Dimitrova et al. 2021). It is a dynamic system that continuously updates its database as new biodiversity information becomes available by several international biodiversity publishers. It also allows its users to ask complex queries via SPARQL (a query language for semantic graph databases) and a simplified semantic search interface.OpenBiodiv was created during two EU-funded Marie Sklodowska-Curie PhD projects: BIG4 (Grant Agreement No 642241) and IGNITE (Grant Agreement No 764840). During those projects, the backend Ontology-0, the first versions of RDF converters and the basic website functionalities have been created (see Dimitrova et al. 2021 for overview).After the start of the BiCIKL project, the entire workflow for processing and RDF conversion of full-text articles in XML and Plazi’s treatments in XML has been re-built using up-to-date technological solutions (such as Apache Kaka  and  Elasticsearch)  to  fully  automatise  and speed up the conversion process and to make it trackable and efficient. As a result, the entire graph content has been re-processed and indexed. New user applications described  in Milestone MS27 App specifications have been discussed and implemented.The present deliverable describes the newly built workflow and tools for data extraction, conversion and indexing and the user applications, created in the BiCIKL project.

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DOI: 10.3897/arphapreprints.e102609

Authors: Lyubomir Penev, Teodor Georgiev, Boris Barov, Pavel Stoev, Kristina Hristova

Abstract: The  main goal of the BiCIKL project is to improve, for the first time, seamless access, linking and usage tracking of data within a network of Research Infrastructures managing different data classes (literature, specimens, samples, occurrences, sequences, taxon names and Operational Taxonomic Units (OTU)), ultimately represented also in a biodiversity knowledge graph. To achieve this, the consortium members will operate with huge amount of data during and after the end of the project.As a Horizon 2020 project, BiCIKL conforms to the Open Research Data Pilot (ORDP)1 and   Article 29.3 of the H2020 Model Grant Agreement by default, hence the consortium aims to improve and maximise access, sharing, linking and reuse of FAIR Open Research Data (ORD), generated or managed by the project. A detailed Data Management Plan is a critical part of   the ORDP. The DMP described in the present document is developed in BiCIKL within the first  six months of the project and it will evolve as a “living document” during the lifetime of the project and beyond in order to present the status of the project's reflections on data management.The BiCIKL DMP outlines the handling of research data and provides the basis of the project consortium’s data management life cycle for the data collected, generated and processed by the participants in the project. The DMP also covers the methodologies and standards previously developed for data sharing and open access, curation  and  preservation.  The subject of the DMP is the management of research data. Personal data management  is covered by deliverable D9.1 Protection of Personal Data.The BiCIKL DMP was developed in close collaboration with all project partners and involved Research Infrastructures (RI) who provided information on their data management practices and policies in a questionnaire and planned generation, collection, and processing of data for the purposes of building a resilient data management strategy of the project which meets all criteria for open research.This DMP aims to adhere to the FAIR (Findable, Accessible, Interoperable, Reusable) data management criteria of Horizon 20202.

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