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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Citations for Software: Providing Identification, Access and Recognition for Research Software

Authors: Laura Soito, Lorraine J Hwang

 

Abstract: Software plays a significant role in modern academic research, yet lacks a similarly significant presence in the scholarly record. With increasing interest in promoting reproducible research, curating software as a scholarly resource not only promotes access to these tools, but also provides recognition for the intellectual efforts that go into their development. This work reviews existing standards for identifying, promoting discovery of, and providing credit for software development work. In addition, it shows how these guidelines have been integrated into existing tools and community cultures, and provides recommendations for future software curation efforts.

 

Citation: Soito, L, Hwang, L. (2016) Citations for Software: Providing Identification, Access and Recognition for Research Software International Journal of Digital Curation 11(2) doi:10.2218/ijdc.v11i2.390

 

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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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The open access advantage considering citation, article usage and social media attention

Author(s): Wang X., Liu C., Mao W., Fang Z.

Abstract: In this study, we compare the difference in the impact between open access (OA) and non-open access (non-OA) articles. 1761 Nature Communications articles published from 1 January 2012 to 31 August 2013 are selected as our research objects, including 587 OA articles and 1174 non-OA articles. Citation data and daily updated article-level metrics data are harvested directly from the platform of nature.com. Data is analyzed from the static versus temporal-dynamic perspectives. The OA citation advantage is confirmed, and the OA advantage is also applicable when extending the comparing from citation to article views and social media attention. More important, we find that OA papers not only have the great advantage of total downloads, but also have the feature of keeping sustained and steady downloads for a long time. For article downloads, non-OA papers only have a short period of attention, when the advantage of OA papers exists for a much longer time.

Citation: Wang X., Liu C., Mao W., Fang Z. (2015). The open access advantage considering citation, article usage and social media attention. Scientometrics. 103(2). doi:10.1007/s11192-015-1547-0 Archived at: arXiv:1503.05702 [cs.DL]

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