Wikipedia as a gateway to biomedical research: The relative distribution and use of citations in the English Wikipedia

Authors: Lauren A. Maggio, John Willinsky, Ryan Steinberg, Daniel Mietchen, Joe Wass, Ting Dong

Abstract: Wikipedia is a gateway to knowledge. However, the extent to which this gateway ends at Wikipedia or continues via supporting citations is unknown. Wikipedia’s gateway functionality has implications for information design and education, notably in medicine. This study aims to establish benchmarks for the relative distribution and referral (click) rate of citations, as indicated by presence of a Digital Object Identifier (DOI), from Wikipedia, with a focus on medical citations. DOIs referred from the English Wikipedia in August 2016 were obtained from Crossref.org. Next, based on a DOI presence on a WikiProject Medicine page, all DOIs in Wikipedia were categorized as medical (WP:MED) or non-medical (non-WP:MED). Using this categorization, referred DOIs were classified as WP:MED, non-WP:MED, or BOTH, meaning the DOI may have been referred from either category. Data were analyzed using descriptive and inferential statistics. Out of 5.2 million Wikipedia pages, 4.42% (n=229,857) included at least one DOI. 68,870 were identified as WP:MED, with 22.14% (n=15,250) featuring one or more DOIs. WP:MED pages featured on average 8.88 DOI citations per page, whereas non-WP:MED pages had on average 4.28 DOI citations. For DOIs only on WP:MED pages, a DOI was referred every 2,283 pageviews and for non-WP-MED pages every 2,467 pageviews. DOIs from both pages accounted for 12% (n=58,475) of referrals, making determining a referral rate for both impossible. While these results cannot provide evidence of greater citation referral from WP:MED than non-WP:MED, they do provide benchmarks to assess strategies for changing referral patterns. These changes might include editors adopting new methods for designing and presenting citations or the introduction of teaching strategies that address the value of consulting citations as a tool for extending learning.

Citation: Maggio LA, Willinsky J, Steinberg R, Mietchen D, Wass J, and Dong T. 2017. Wikipedia as a gateway to biomedical research: The relative distribution and use of citations in the English Wikipedia. bioRxiv doi: 10.1101/165159

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Copyright and the Use of Images as Biodiversity Data

Authors: Willi Egloff, Donat Agosti, Puneet Kishor, David Patterson, Jeremy A. Miller

Abstract: 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 creativity 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.

Citation: Willi Egloff, Donat Agosti, Puneet Kishor, David Patterson, Jeremy A. Miller,  2017. “Copyright and the Use of Images as Biodiversity Data” 

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A Data Citation Roadmap for Scientific Publishers

Authors: Helena Cousijn, Amye Kenall, Emma Ganley, Melissa Harrison, David Kernohan, Fiona Murphy, Patrick Polischuk, Maryann Martone, Timothy Clark

Abstract: This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP), a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE program. The structure of the roadmap presented here follows the ‘life of a paper’ workflow and includes the categories Pre-submission, Submission, Production, and Publication. The roadmap is intended to be publisher-agnostic so that all publishers can use this as a starting point when implementing JDDCP-compliant data citation.

Citation: Helena Cousijn, Amye Kenall, Emma Ganley, Melissa Harrison, David Kernohan, Fiona Murphy, Patrick Polischuk, Maryann Martone, Timothy Clark. (2017). A Data Citation Roadmap for Scientific Publishers. bioRxiv 100784; doi: https://doi.org/10.1101/100784

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A Data Citation Roadmap for Scholarly Data Repositories

Authors: Martin Fennera, Merce Crosasb, Jeffrey S. Grethec, David Kennedy, Henning Hermjakobe, Phillippe Rocca-Serraf, Robin Berjong, Sebastian Karcherh, Maryann Martonei, Tim Clark

 

Abstract: This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles (Data Citation Synthesis Group, 2014), a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Early Adopters Expert Group, part of the Data Citation Implementation Pilot (DCIP) project (FORCE11, 2015), an initiative of FORCE11.org and the NIH BioCADDIE (2016) program. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories.

 

Citation: Fenner, M., Crosas, M., Grethe, J., Kennedy, D., Hermjakob, H., Rocca-Serra, P., … Clark, T. (2016). A Data Citation Roadmap for Scholarly Data Repositories. bioRxiv. https://doi.org/10.1101/097196

 

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