We have launched a fresh look and feel to the PubMed Central (PMC) website, which marks the first step of an ongoing modernization effort. The updated website will allow us to make continuous enhancements to PMC based on your feedback.
What Has Changed?
Now when you visit PMC’s homepage, you will see:
A redesigned and reorganized homepage
Easy-to-navigate help documentation
A similar look and feel between features in PMC and PubMed
On March 21, we will be launching an updated PMC website with a modern design. You can try the updated version on PMC Labs now, and it will become the default design of the PMC website following launch. Be sure to check the banner at the top of the PMC website for updates on an exact cutover date.
This update represents the first phase of an overall PMC modernization that will help us update PMC in a quicker and more responsive fashion. New features and functionality will be deployed on an ongoing basis.
In June, we announced the arrival of PMC Labs, where you can test drive the work underway to create a more modern PMC website. Since then, we’ve continued to talk to users, gather input, and make ongoing adjustments based on your feedback.
We hope that the planned updates will create an easier navigation and reading experience, while keeping all the features you use most within PMC. If you haven’t had a chance to try out the changes, there’s still time to give input using the green feedback button in the lower right-hand corner of the site.
To enhance machine access to biomedical literature and drive impactful analyses and reuse, the National Library of Medicine (NLM) is pleased to announce the availability of the PubMed Central (PMC) Article Datasets on Amazon Web Services (AWS) Registry of Open Data as part of AWS’s Open Data Sponsorship Program (ODP). These datasets collectively span 4 million of PMC’s 7 million (total) full-text scientific articles.
We’re updating PubMed Central (PMC) to a give you a more modern and easier to use site and we want your feedback. The first phase of this work is now on PMC Labs for you to explore and provide feedback.
In the first phase we have focused on modernizing PMC’s platform to create a more stable and easy-to-update environment. This also includes some initial changes to the homepage (Figure 1), site organization, and article pages (Figure 2). Many of the updates you see on the Labs site create a similar look and feel for PMC and PubMed, reorganizing documentation to highlight the most accessed and important content first and consolidating redundant features to provide a smoother experience. Please visit PMC Labs to try out the PMC updates and provide feedback using the buttons on the lower right-hand side of the Labs pages (Figure 1). We will update the current PMC website with new features once we gather your input on the Labs site.
One important way the National Library of Medicine (NLM) is responding to the ongoing public health emergency is through the COVID-19 Initiative. This public-private cooperation between NLM and more than 50 scholarly publishers and societies allows you to access over 100,000 articles on COVID-19, SARS-CoV-2 and other coronaviruses through PubMed Central (PMC). This collection includes recently published discoveries, a history of coronavirus reports for comparison, international (globally comprehensive) content, and captures the breadth of research, analysis, and commentary. We make these articles available in human- and machine-readable formats to support public accessibility and analysis by researchers.
You can search this public health emergency collection in PMC or download the collection through the PMC Open Access Subset. The collection spans:
More than half a century of research, including articles from the 1960s through the present (more than 60% of the articles included thus far were published in 2020 (Figure 1, top panel);
Several languages, including content in English (~95%), German, French, and Spanish;
Many publication types, more than half of them research or review articles (Figure 1, bottom panel).
Figure 1. The Public Health Emergency Collection articles by decade of publication (top panel) and by publication type (bottom panel).
People have viewed or downloaded articles in this PMC collection more than 80 million times since March reflecting the great demand for such an open and centralized collection. Artificial intelligence organizations, such as the Allen Institute for AI — builders of the COVID-19 Research Dataset (CORD-19), have also used the collection to develop new text and data mining techniques that can help answer high-priority scientific questions related to COVID-19.
NLM is preparing to launch a pilot project to test the viability of making preprints resulting from NIH-funded research available via PubMed Central (PMC). The primary goal of the NIH Preprint Pilot will be to explore approaches to increasing the discoverability of early NIH research results. The pilot will begin the week of June 8, 2020 and will run for a minimum of 12 months. Lessons learned during that time will inform future NLM efforts with preprints.
In its role as the repository for peer-reviewed manuscripts supported by NIH, PMC already makes available more than one million published papers resulting from NIH-supported research. Building on NIH guidance (NOT-OD-17-050) to investigators that encouraged the use of interim research products, such as preprints, to speed the dissemination and enhance the rigor of their work, NLM hopes this pilot will inform possible future steps to further accelerate discovery and access of papers that are developed with NIH funds and encourage the open and fast dissemination of NIH research results, when appropriate.
Are you interested in mining literature about COVID-19 and the novel SARS-Cov-2 virus? You may want to check out the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a collection of more than 13,000 full text articles that focus on COVID-19 and coronaviruses and that were assembled from PMC, the WHO, bioRxiv, and medRxiv. To produce this dataset, the National Library of Medicine partnered with colleagues from the Allen Institute for AI, the Chan Zuckerberg Initiative (CZI), Georgetown University’s Center for Security and Emerging Technology (CSET), Kaggle, Microsoft, and the White House Office of Science and Technology Policy (OSTP).
CORD-19 is available from the Allen Institute and will be updated weekly as new articles become available. The article data are formatted in JSON, making the collection ideal for computational methods such as data mining, machine learning, and natural language processing. We hope this collection serves as a call to action for the community to improve our understanding of coronaviruses and the human diseases they cause. Have a look and let us know what you think!