Abstract: Both the impact factor of the journal and immediate full-text availability in Pubmed Central (PMC) have featured in editorials before.1-3 In 2004, the editor of the Cardiovascular Journal of Africa (CVJA) lamented, like so many others, the injustice of not having an impact factor, its validity as a tool for measuring science output, and the negative effect of a low perceived impact in drawing attention from publications from developing countries.1,4
Since then, after a selection process, we have been indexed by the Web of Science® (WoS) and Thomson Reuters (Philadelphia, PA, USA), and have seen a growing impact factor. In the case of PMC, our acceptance to this database was announced in 2012,2 and now we are proud that it is active and full-text articles are available dating back to 2009. The journal opted for immediate full open access (OA), which means that full-text articles are available on publication date for anybody with access to the internet.
“Locate, identify, and cite research data with the leading global provider of DOIs for research data….DataCite is a leading global non-profit organisation that provides persistent identifiers (DOIs) for research data. Our goal is to help the research community locate, identify, and cite research data with confidence.
We work on several fronts to achieve this goal. We support the creation and allocation of DOIs and accompanying metadata. We provide services that support the enhanced search and discovery of research content. And we promote data citation and advocacy through our community-building efforts and responsive communication and outreach materials….”
Abstract: There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
“Scilit is a comprehensive, free database for scientists using a new method to collate data and indexing scientific material. Our crawlers extract the latest data from CrossRef and PubMed on a daily basis. This means that newly published articles are added to Scilit immediately….Publishers have the possibility to upload their data in order to improve the accuracy of the content on Scilit….”
At ScienceOpen, we offer a range of next-generation indexing services. This includes a package especially for institutes, to help them gain the maximum visibility and re-use of the articles their researchers publish.
“None of this is to deny that if you have strong primary research to report it is better to push it out in journals wherever feasible. But book chapters can have valuable exploratory, discursive, synoptic and review roles. And they can carry new findings too, especially in start-up fields and with good editors and editing. The old problems from the early digital phase, when for a while chapter texts became literally unfindable, and authors passively left things to publishers to promote their work, no longer apply with much of their previous force. However conservative your editors and publishers may be, you can get your chapter noticed, read and cited in the communities that matter to you.”
“With all the intense interest Unpaywall is getting (See coverage in academic sites like Nature,Science, Chronicle of Higher education, as well as more mainstream tech sites like Techcruch, Gimzo), you might be surprised to know that Unpaywall isn’t in fact the first tool that promises to help users unlock paywalls by finding free versions.
“Scientific results are communicated visually in the literature through diagrams, visualizations, and photographs. These information-dense objects have been largely ignored in bibliometrics and scientometrics studies when compared to citations and text. In this project, we use techniques from computer vision and machine learning to classify more than 8 million figures from PubMed into 5 figure types and study the resulting patterns of visual information as they relate to impact. We find that the distribution of figures and figure types in the literature has remained relatively constant over time, but can vary widely across field and topic. We find a significant correlation between scientific impact and the use of visual information, where higher impact papers tend to include more diagrams, and to a lesser extent more plots and photographs. To explore these results and other ways of extracting this visual information, we have built a visual browser to illustrate the concept and explore design alternatives for supporting viziometric analysis and organizing visual information. We use these results to articulate a new research agenda – viziometrics – to study the organization and presentation of visual information in the scientific literature….”