The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis | SpringerLink

Abstract:  Traditionally, Web of Science and Scopus have been the two most widely used databases for bibliometric analyses. However, during the last few years some new scholarly databases, such as Dimensions, have come up. Several previous studies have compared different databases, either through a direct comparison of article coverage or by comparing the citations across the databases. This article aims to present a comparative analysis of the journal coverage of the three databases (Web of Science, Scopus and Dimensions), with the objective to describe, understand and visualize the differences in them. The most recent master journal lists of the three databases is used for analysis. The results indicate that the databases have significantly different journal coverage, with the Web of Science being most selective and Dimensions being the most exhaustive. About 99.11% and 96.61% of the journals indexed in Web of Science are also indexed in Scopus and Dimensions, respectively. Scopus has 96.42% of its indexed journals also covered by Dimensions. Dimensions database has the most exhaustive journal coverage, with 82.22% more journals than Web of Science and 48.17% more journals than Scopus. This article also analysed the research outputs for 20 selected countries for the 2010–2018 period, as indexed in the three databases, and identified database-induced variations in research output volume, rank, global share and subject area composition for different countries. It is found that there are clearly visible variations in the research output from different countries in the three databases, along with differential coverage of different subject areas by the three databases. The analytical study provides an informative and practically useful picture of the journal coverage of Web of Science, Scopus and Dimensions databases.

 

Open Access surpasses subscription publication globally for the first time | Dimensions

“In the vein of keeping things moving, the Dimensions team has introduced many new features over the last few years. Most recently, they have updated the Open Access classifications in Dimensions and introduced some additional fields that some of you may find helpful.

The Open Access data in Dimensions is sourced from our colleagues at Unpaywall.  When we first launched Dimensions, Unpaywall was almost as new as we were, but in the meanwhile, both Unpaywall and Dimensions have moved on. The new release of Dimensions now tracks the Unpaywall OA classifications.  This means that the filters in Dimensions should be more consistent and easier to understand – we now have: Green, Bronze, Gold, Hybrid, All OA and Closed.  Of course, all the Open Access filters are available in the free version of Dimensions as well.

While we have seen the percentage of OA increasing rapidly in recent years, especially in countries like China, Germany and the UK, it was not until 2020 that more outputs were published through Open Access channels than traditional subscription channels globally….”

How PLOS uses Dimensions to validate next generation Open Access agreements | Dimensions

“While there are few, if any, organizations that can claim to have perfect data, the goal should undoubtedly be to strive for a level that is as good as possible. “Data underpins and supports the discussions, the agreements and of course the metrics for success following an agreement,” says Sara. She continues, “at PLOS, we combine data from our own internal sources together with external data sources like Dimensions – which give us the crucial, broader view of the market place outside of PLOS alone.”

How does Dimensions support PLOS? “PLOS relies on Dimensions for baseline data about institutions and their funding sources for agreement discussions but also for internal business analytics,” notes Sara. She adds,  Dimensions Analytics is particularly easy to use for non-analysts like myself who want to get in, get a specific question answered (like who is the most frequent funder of a  specific country or institution), and get out quickly.” PLOS understands that subject matter experts need to dedicate their time to more significant impact analysis tasks.  Accessing a database like Dimensions Analytics that already provides analytical views – layered on top of the data itself – means that many questions can be answered by the PLOS team at all levels. …”

How PLOS uses Dimensions to validate next generation Open Access agreements | Dimensions

“While there are few, if any, organizations that can claim to have perfect data, the goal should undoubtedly be to strive for a level that is as good as possible. “Data underpins and supports the discussions, the agreements and of course the metrics for success following an agreement,” says Sara. She continues, “at PLOS, we combine data from our own internal sources together with external data sources like Dimensions – which give us the crucial, broader view of the market place outside of PLOS alone.”

How does Dimensions support PLOS? “PLOS relies on Dimensions for baseline data about institutions and their funding sources for agreement discussions but also for internal business analytics,” notes Sara. She adds,  Dimensions Analytics is particularly easy to use for non-analysts like myself who want to get in, get a specific question answered (like who is the most frequent funder of a  specific country or institution), and get out quickly.” PLOS understands that subject matter experts need to dedicate their time to more significant impact analysis tasks.  Accessing a database like Dimensions Analytics that already provides analytical views – layered on top of the data itself – means that many questions can be answered by the PLOS team at all levels. …”

Open Access and Altmetrics in the pandemic age: Forescast analysis on COVID-19 literature | bioRxiv

Abstract:  We present an analysis on the uptake of open access on COVID-19 related literature as well as the social media attention they gather when compared with non OA papers. We use a dataset of publications curated by Dimensions and analyze articles and preprints. Our sample includes 11,686 publications of which 67.5% are openly accessible. OA publications tend to receive the largest share of social media attention as measured by the Altmetric Attention Score. 37.6% of OA publications are bronze, which means toll journals are providing free access. MedRxiv contributes to 36.3% of documents in repositories but papers in BiorXiv exhibit on average higher AAS. We predict the growth of COVID-19 literature in the following 30 days estimating ARIMA models for the overall publications set, OA vs. non OA and by location of the document (repository vs. journal). We estimate that COVID-19 publications will double in the next 20 days, but non OA publications will grow at a higher rate than OA publications. We conclude by discussing the implications of such findings on the dissemination and communication of research findings to mitigate the coronavirus outbreak.

 

Research Square Partners with Dimensions to Provide Citation Data on Preprints | Research Square

” Research Square, the company behind the world’s fastest-growing preprint platform, is partnering with Dimensions to provide early citation data on preprints. The Dimensions Badge will now display on all Research Square preprints that have been cited and will provide 4 different types of data: the total citations, most recent citations, Field Citation Ratio (FCR), and Relative Citation Ratio (RCR)….”

Huge Covid-19 output prompting ‘sea change’ in access to research | Times Higher Education (THE)

“The Covid-19 crisis is leading to a “sea change” in the way that researchers are collating and analysing research in a bid to keep up with the “phenomenal” growth in scholarship on the topic, experts have suggested.

According to one search portal for coronavirus research, as of 3 April more than 6,000 papers, including preprints, have been published on the topic and related areas since the beginning of the year….

He added that the fact that many publishers were making Covid-19 research open access also meant that scholars could get around the overwhelming nature of dealing with such a vast amount of information by using sophisticated search techniques such as text mining….”