Is Sci-Hub Increasing Visibility of Indian Research Papers? An Analytical Evaluation

Abstract:  Sci-Hub, founded by Alexandra Elbakyan in 2011 in Kazakhstan has, over the years, emerged as a very popular source for researchers to download scientific papers. It is believed that Sci-Hub contains more than 76 million academic articles. However, recently three foreign academic publishers (Elsevier, Wiley and American Chemical Society) have filed a lawsuit against Sci-Hub and LibGen before the Delhi High Court and prayed for complete blocking these websites in India. It is in this context, that this paper attempts to find out how many Indian research papers are available in Sci-Hub and who downloads them. The citation advantage of Indian research papers available on Sci-Hub is analysed, with results confirming that such an advantage do exist. 

Research Square, Kudos Partner to Expand Research Communication Services for Authors

“Leading research communication platforms Research Square and Kudos have partnered to help preprint authors accelerate and maximize exposure of their newly shared research. A new package of communication products and services, launched today, will create and disseminate web profile pages for authors’ new research.  …”

Day-to-day discovery of preprint–publication links | SpringerLink

Abstract:  Preprints promote the open and fast communication of non-peer reviewed work. Once a preprint is published in a peer-reviewed venue, the preprint server updates its web page: a prominent hyperlink leading to the newly published work is added. Linking preprints to publications is of utmost importance as it provides readers with the latest version of a now certified work. Yet leading preprint servers fail to identify all existing preprint–publication links. This limitation calls for a more thorough approach to this critical information retrieval task: overlooking published evidence translates into partial and even inaccurate systematic reviews on health-related issues, for instance. We designed an algorithm leveraging the Crossref public and free source of bibliographic metadata to comb the literature for preprint–publication links. We tested it on a reference preprint set identified and curated for a living systematic review on interventions for preventing and treating COVID-19 performed by international collaboration: the COVID-NMA initiative (covid-nma.com). The reference set comprised 343 preprints, 121 of which appeared as a publication in a peer-reviewed journal. While the preprint servers identified 39.7% of the preprint–publication links, our linker identified 90.9% of the expected links with no clues taken from the preprint servers. The accuracy of the proposed linker is 91.5% on this reference set, with 90.9% sensitivity and 91.9% specificity. This is a 16.26% increase in accuracy compared to that of preprint servers. We release this software as supplementary material to foster its integration into preprint servers’ workflows and enhance a daily preprint–publication chase that is useful to all readers, including systematic reviewers. This preprint–publication linker currently provides day-to-day updates to the biomedical experts of the COVID-NMA initiative.

 

Next Steps for Microsoft Academic – Expanding into New Horizons | Microsoft Research

TLDR:

Microsoft Academic Website: No longer accessible after Dec. 31, 2020,
Microsoft Academic Graph: No longer providing updated data or access to old releases after Dec. 31, 2021; however, existing copies can still be used under license.

Microsoft Academic has been on a mission to explore new ways to empower researchers and research organizations to achieve more. The research project is characterized by two sets of technologies: one that reads all the Bing-indexed web pages and organizes the most up-to-date academic knowledge into a knowledge base called Microsoft Academic Graph (MAG), and the other that performs semantic reasoning and inference to serve that knowledge through the Microsoft Academic search website and API. We are proud that these data and web services have been found useful in numerous research projects around the world, and excited to see more community-driven, public efforts emerge.

One question that we are asked frequently, though, is how the technologies powering Microsoft Academic can be used by institutions outside of academia to make organizational knowledge more discoverable and accessible. Over the years, we have openly shared some of the building blocks, such as the language and network similarity packages, and the core search engine MAKES.  With the continued progress in data access, we believe now is the right time to fully explore opportunities to extend this technology to new industries and transition to community approaches for academic research.

Microsoft Research will continue to support the automated AI agents powering Microsoft Academic services through the end of calendar year 2021. During this time, we encourage existing Microsoft Academic users to begin transitioning to other equivalent services. Below are just a few of the many great options available to the community.

Aminer
CrossRef
Dimensions
lens.org
OpenCitations
Scopus
Semantic Scholar

Thank you very much for the years of support and encouragement. We are immensely grateful to have learned and grown from your feedback over the years. As we are passing the torch to the community-driven efforts, we invite you to join us in continuously contributing ideas and suggestions to nurture, embrace, and grow these platforms.

 

Assessment, Usability, and Sociocultural Impacts of DataONE | International Journal of Digital Curation

Abstract:  DataONE, funded from 2009-2019 by the U.S. National Science Foundation, is an early example of a large-scale project that built both a cyberinfrastructure and culture of data discovery, sharing, and reuse. DataONE used a Working Group model, where a diverse group of participants collaborated on targeted research and development activities to achieve broader project goals. This article summarizes the work carried out by two of DataONE’s working groups: Usability & Assessment (2009-2019) and Sociocultural Issues (2009-2014). The activities of these working groups provide a unique longitudinal look at how scientists, librarians, and other key stakeholders engaged in convergence research to identify and analyze practices around research data management through the development of boundary objects, an iterative assessment program, and reflection. Members of the working groups disseminated their findings widely in papers, presentations, and datasets, reaching international audiences through publications in 25 different journals and presentations to over 5,000 people at interdisciplinary venues. The working groups helped inform the DataONE cyberinfrastructure and influenced the evolving data management landscape. By studying working groups over time, the paper also presents lessons learned about the working group model for global large-scale projects that bring together participants from multiple disciplines and communities in convergence research.

 

Day-to-day discovery of preprint–publication links | SpringerLink

Abstract:  Preprints promote the open and fast communication of non-peer reviewed work. Once a preprint is published in a peer-reviewed venue, the preprint server updates its web page: a prominent hyperlink leading to the newly published work is added. Linking preprints to publications is of utmost importance as it provides readers with the latest version of a now certified work. Yet leading preprint servers fail to identify all existing preprint–publication links. This limitation calls for a more thorough approach to this critical information retrieval task: overlooking published evidence translates into partial and even inaccurate systematic reviews on health-related issues, for instance. We designed an algorithm leveraging the Crossref public and free source of bibliographic metadata to comb the literature for preprint–publication links. We tested it on a reference preprint set identified and curated for a living systematic review on interventions for preventing and treating COVID-19 performed by international collaboration: the COVID-NMA initiative (covid-nma.com). The reference set comprised 343 preprints, 121 of which appeared as a publication in a peer-reviewed journal. While the preprint servers identified 39.7% of the preprint–publication links, our linker identified 90.9% of the expected links with no clues taken from the preprint servers. The accuracy of the proposed linker is 91.5% on this reference set, with 90.9% sensitivity and 91.9% specificity. This is a 16.26% increase in accuracy compared to that of preprint servers. We release this software as supplementary material to foster its integration into preprint servers’ workflows and enhance a daily preprint–publication chase that is useful to all readers, including systematic reviewers. This preprint–publication linker currently provides day-to-day updates to the biomedical experts of the COVID-NMA initiative.

 

Crowdsourcing Scholarly Discourse Annotations | 26th International Conference on Intelligent User Interfaces

Abstract:  The number of scholarly publications grows steadily every year and it becomes harder to find, assess and compare scholarly knowledge effectively. Scholarly knowledge graphs have the potential to address these challenges. However, creating such graphs remains a complex task. We propose a method to crowdsource structured scholarly knowledge from paper authors with a web-based user interface supported by artificial intelligence. The interface enables authors to select key sentences for annotation. It integrates multiple machine learning algorithms to assist authors during the annotation, including class recommendation and key sentence highlighting. We envision that the interface is integrated in paper submission processes for which we define three main task requirements: The task has to be . We evaluated the interface with a user study in which participants were assigned the task to annotate one of their own articles. With the resulting data, we determined whether the participants were successfully able to perform the task. Furthermore, we evaluated the interface’s usability and the participant’s attitude towards the interface with a survey. The results suggest that sentence annotation is a feasible task for researchers and that they do not object to annotate their articles during the submission process.

 

Google Scholar, Web of Science, and Scopus: Which is best for me? | Impact of Social Sciences

“Being able to find, assess and place new research within a field of knowledge, is integral to any research project. For social scientists this process is increasingly likely to take place on Google Scholar, closely followed by traditional scholarly databases. In this post, Alberto Martín-Martín, Enrique Orduna-Malea , Mike Thelwall, Emilio Delgado-López-Cózar, analyse the relative coverage of the three main research databases, Google Scholar, Web of Science and Scopus, finding significant divergences in the social sciences and humanities and suggest that researchers face a trade-off when using different databases: between more comprehensive, but disorderly systems and orderly, but limited systems….”