19 research outputs found

    Taxonomic information exchange and copyright: the Plazi approach

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    <p>Abstract</p> <p>Background</p> <p>A large part of our knowledge on the world's species is recorded in the corpus of biodiversity literature with well over hundred million pages, and is represented in natural history collections estimated at 2 – 3 billion specimens. But this body of knowledge is almost entirely in paper-print form and is not directly accessible through the Internet. For the digitization of this literature, new territories have to be chartered in the fields of technical, legal and social issues that presently impede its advance. The taxonomic literature seems especially destined for such a transformation.</p> <p>Discussion</p> <p>Plazi was founded as an association with the primary goal of transforming both the printed and, more recently, "born-digital" taxonomic literature into semantically enabled, enhanced documents. This includes the creation of a test body of literature, an XML schema modeling its logic content (TaxonX), the development of a mark-up editor (GoldenGATE) allowing also the enhancement of documents with links to external resources via Life Science Identifiers (LSID), a repository for publications and issuance of bibliographic identifiers, a dedicated server to serve the marked up content (the Plazi Search and Retrieval Server, SRS) and semantic tools to mine information. Plazi's workflow is designed to respect copyright protection and achieves extraction by observing exceptions and limitations existent in international copyright law.</p> <p>Conclusion</p> <p>The information found in Plazi's databases – taxonomic treatments as well as the metadata of the publications – are in the public domain and can therefore be used for further scientific research without any restriction, whether or not contained in copyrighted publications.</p

    Copyright and the Use of Images as Biodiversity Data [Forum paper]

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    Taxonomy is the discipline responsible for charting the world’s organismic diversity, understanding ancestor/descendant relationships, and organizing all species according to a unified taxonomic classification system. Taxonomists document the attributes (characters) of organisms, with emphasis on those can be used to distinguish species from each other. Character information is compiled in the scientific literature as text, tables, and images. The information is presented according to conventions that vary among taxonomic domains; such conventions facilitate comparison among similar species, even when descriptions are published by different authors. There is considerable uncertainty within the taxonomic community as to how to re-use images that were included in taxonomic publications, especially in regard to whether copyright applies. This article deals with the principles and application of copyright law, database protection, and protection against unfair competition, as applied to images. We conclude that copyright does not apply to most images in taxonomic literature because they are presented in a standardized way and lack the individuality that is required to qualify as ‘copyrightable works’. There are exceptions, such as wildlife photographs, drawings and artwork produced in a distinctive individual form and intended for other than comparative purposes (such as visual art). Further exceptions may apply to collections of images that qualify as a database in the sense of European database protection law. In a few European countries, there is legal protection for photographs that do not qualify as works in the usual sense of copyright. It follows that most images found in taxonomic literature can be re-used for research or many other purposes without seeking permission, regardless of any copyright declaration. In observance of ethical and scholarly standards, re-users are expected to cite the author and original source of any image that they use

    Scientific names of organisms : attribution, rights, and licensing

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    © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Research Notes 7 (2014): 79, doi:10.1186/1756-0500-7-79.As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed

    The Bari Manifesto : An interoperability framework for essential biodiversity variables

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    Essential Biodiversity Variables (EBV) are fundamental variables that can be used for assessing biodiversity change over time, for determining adherence to biodiversity policy, for monitoring progress towards sustainable development goals, and for tracking biodiversity responses to disturbances and management interventions. Data from observations or models that provide measured or estimated EBV values, which we refer to as EBV data products, can help to capture the above processes and trends and can serve as a coherent framework for documenting trends in biodiversity. Using primary biodiversity records and other raw data as sources to produce EBV data products depends on cooperation and interoperability among multiple stakeholders, including those collecting and mobilising data for EBVs and those producing, publishing and preserving EBV data products. Here, we encapsulate ten principles for the current best practice in EBV-focused biodiversity informatics as 'The Bari Manifesto', serving as implementation guidelines for data and research infrastructure providers to support the emerging EBV operational framework based on trans-national and cross-infrastructure scientific workflows. The principles provide guidance on how to contribute towards the production of EBV data products that are globally oriented, while remaining appropriate to the producer's own mission, vision and goals. These ten principles cover: data management planning; data structure; metadata; services; data quality; workflows; provenance; ontologies/vocabularies; data preservation; and accessibility. For each principle, desired outcomes and goals have been formulated. Some specific actions related to fulfilling the Bari Manifesto principles are highlighted in the context of each of four groups of organizations contributing to enabling data interoperability - data standards bodies, research data infrastructures, the pertinent research communities, and funders. The Bari Manifesto provides a roadmap enabling support for routine generation of EBV data products, and increases the likelihood of success for a global EBV framework.Peer reviewe

    Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

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    Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence-absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals

    Der Zugang zu Fachinformationen

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    The Plazi Workflow: The PDF prison break for biodiversity data

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    The Swiss NGO Plazi (http://plazi.org) has developed an automated workflow for liberating data, including images and text, from new taxonomic publications issued in PDF format. This stepwise process extracts, article metadata, illustrations and their captions, bibliographic references, scientific names, named geographic entities such as coordinates and country names, collection codes, and finally, taxonomic treatments. These extracted data are enhanced and published in TreatmentBank (http://plazi.org) and deposited in Biodiversity Literature Repository (https:/biolitrepo.org) respectively, in which a Digital Object Identifier (DataCite DOI) is minted for articles as well as their contained figures and taxon treatments, each linked to each other in their metadata. This input is complemented by the import of Journal Article Tag Suite/Taxpub XML based publications from Pensoft publishers (e.g. Zookeys, Journal of Hymenoptera Research; https://pensoft.net/browse_journals) that are semantically enhanced during their journal production workflow. Upon import, materials citation are discovered and parsed, and the taxonomic treatments added to TreatmentBank where a persistent identifier is minted. From TreatmentBank data from taxonomic treatments, including occurence data from cited specimens, are submitted to GBIF (http://gbif.org), or are accessible via API. Treatments and material citations from more than 26,200 articles have been registered. The articles can be found on GBIF using the Digital Object Identifier in the search field.  Plazi, together with Pensoft Publishers, has processed over 26,000 articles containing more than 284,000 taxonomic treatments, 190,000 images, 50,000 georeferenced materials citations, together comprising an estimated 100 million facts. Through the support of the Arcadia Fund (https://www.arcadiafund.org.uk/) Plazi's processing is expanding to cover a sufficient number of journals to liberate the data of over 50% of the new described animal species annually. This will complement an existing service provided to the MusĂ©um National d’Histoire Naturelle, Paris, to convert the European Journal of Taxonomy and their other journals (http://sciencepress.mnhn.fr/en/periodiques/adansonia/40/1) to JATS/TaxPub (https://www.ncbi.nlm.nih.gov/books/NBK47081), as well as an increasing portfolio of journals published in JATS/TaxPub by Pensoft Ltd

    Open exchange of scientific knowledge and European copyright: The case of biodiversity information

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    Background. The 7th Framework Programme for Research and Technological Development is helping the European to prepare for an integrative system for intelligent management of biodiversity knowledge. The infrastructure that is envisaged and that will be further developed within the Programme “Horizon 2020” aims to provide open and free access to taxonomic information to anyone with a requirement for biodiversity data, without the need for individual consent of other persons or institutions. Open and free access to information will foster the re-use and improve the quality of data, will accelerate research, and will promote new types of research. Progress towards the goal of free and open access to content is hampered by numerous technical, economic, sociological, legal, and other factors. The present article addresses barriers to the open exchange of biodiversity knowledge that arise from European laws, in particular European legislation on copyright and database protection rights.We present a legal point of view as to what will be needed to bring distributed information together and facilitate its re-use by data mining, integration into semantic knowledge systems, and similar techniques. We address exceptions and limitations of copyright or database protection within Europe, and we point to the importance of data use agreements. We illustrate how exceptions and limitations have been transformed into national legislations within some European states to create inconsistencies that impede access to biodiversity information.Conclusions. The legal situation within the EU is unsatisfactory because there are inconsistencies among states that hamper the deployment of an open biodiversity knowledge management system. Scientists within the EU who work with copyright protected works or with protected databases have to be aware of regulations that vary from country to country. This is a major stumbling block to international collaboration and is an impediment to the open exchange of biodiversity knowledge. Such differences should be removed by unifying exceptions and limitations for research purposes in a binding, Europe-wide regulation
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