On June 9, 2020, NLM launched 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. Following standard NLM practice, a citation for each preprint record in PMC will also be available in PubMed to further increase the discoverability of this content. The pilot will run for a minimum of 12 months. Lessons learned during that time will inform future NLM efforts with preprints.
Newly created filters will also provide users with the option to exclude preprint records from search results. In PMC, you can use a search filter to find preprint records: preprint[filter]. In PubMed, you can query by publication type: preprint[pt]. To exclude preprint records from your search results, you can use the Boolean "NOT" in either database, e.g., covid 19 NOT preprint[filter] in PMC and covid 19 NOT preprint[pt] in PubMed.
Dataset Description
In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 138,000 scholarly articles, including over 69,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses. This freely available dataset is provided to the global research community to apply recent advances in natural language processing and other AI techniques to generate new insights in support of the ongoing fight against this infectious disease. There is a growing urgency for these approaches because of the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up.
Call to Action
We are issuing a call to action to the world's artificial intelligence experts to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions. The CORD-19 dataset represents the most extensive machine-readable coronavirus literature collection available for data mining to date. This allows the worldwide AI research community the opportunity to apply text and data mining approaches to find answers to questions within, and connect insights across, this content in support of the ongoing COVID-19 response efforts worldwide. There is a growing urgency for these approaches because of the rapid increase in coronavirus literature, making it difficult for the medical community to keep up.
A list of our initial key questions can be found under the Tasks section of this dataset. These key scientific questions are drawn from the NASEM’s SCIED (National Academies of Sciences, Engineering, and Medicine’s Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats) research topics and the World Health Organization’s R&D Blueprint for COVID-19.
Many of these questions are suitable for text mining, and we encourage researchers to develop text mining tools to provide insights on these questions.
We are maintaining a summary of the community's contributions. For guidance on how to make your contributions useful, we're maintaining a forum thread with the feedback we're getting from the medical and health policy communities.
Accessing the Dataset
We have made this dataset available on Kaggle. Watch out for periodic updates.
The dataset is also hosted on AI2's Semantic Scholar. And you can search the dataset using AI2's new COVID-19 explorer.
The licenses for each dataset can be found in the all _ sources _ metadata csv file.
This dataset was created by the Allen Institute for AI in partnership with the Chan Zuckerberg Initiative, Georgetown University’s Center for Security and Emerging Technology, Microsoft Research, IBM, and the National Library of Medicine - National Institutes of Health, in coordination with The White House Office of Science and Technology Policy.
Due to the current health emergency in the U.S. and the sudden shift of classes to the online environment, ProQuest has made all their eBooks available without user limits to all participating universities through June 30.
This adds hundreds of thousands of titles to those already available in the library's catalog. Search here for e-books not found in the Library's catalog as the released titles will not show up in the catalog or Galileo.
Open ICPSR's COVID-19 Data Repository is a repository for data examining the social, behavioral, public health, and economic impact of the novel coronavirus global pandemic. This is a free self-publishing option for any researcher who wants to share data related to COVID-19. The data will be available to any interested user for secondary analysis.
For best practices in preparing data for sharing, ICPSR also has a handy Guide to Social Science Data Preparation.
COVID-19 repository deposits are most useful if they include all data, annotated program code, command files, and documentation necessary to understand the data collection and/or replicate research findings.
The Cochrane Library has created two Special Collection.
1. Coronavirus (COVID-19): infection control and prevention measures This Special Collection has been created in response to the COVID-19 pandemic and is regularly updated. It aims to ensure immediate access to systematic reviews most directly relevant to the prevention of infection. It includes reviews that are relevant to the WHO interim guidance, as well as other potentially relevant reviews from three Cochrane Networks: Cochrane Public Health and Health Systems; Cochrane Musculoskeletal, Oral, Skin and Sensory; and Cochrane Acute and Emergency Care, and also draws on the knowledge of Cochrane groups in affected regions. Many reviews in this collection have associated Cochrane Clinical Answers (CCAs), with links provided.
2.Coronavirus (COVID-19): evidence relevant to critical care This Special Collection has been created in response to the COVID-19 pandemic, and is regularly updated. It aims to ensure immediate access to systematic reviews most directly relevant to the management of people hospitalized with severe acute respiratory infections. It includes reviews that are relevant to the WHO interim guidance, those identified as relevant by Cochrane Acute and Emergency Care, and also draws on the knowledge of Cochrane groups in affected regions.
In response to the recent Coronavirus outbreak, the Greenblatt Library recommends the following information and resource pages.
Project MUSE is pleased to support its participating publishers in making scholarly content temporarily available for free on our platform until September 30.
Among the publishers currently opting to make content free on Project MUSE are Johns Hopkins University Press (all books and journals), Ohio State University Press (all books and journals), University of Nebraska Press (all books and journals), University of North Carolina Press (all books), Temple University Press (all books), and Vanderbilt University Press (selected books). We will continually update the list of publishers offering free access to content at https://about.muse.jhu.edu/resources/freeresourcescovid19/.
Content that is freely available on the Project MUSE platform during the COVID-19 crisis will display a distinctive “Free” icon, different from the “OA” icon used for fully open access content on MUSE, or the familiar green checkmark that users associate with content held by their library. MUSE search results (muse.jhu.edu/search), by default, include any content to which a user has access, so will offer the researcher any relevant free, OA, or entitled articles and books. There are over 2000 open access books and a small number of fully OA journals on the MUSE platform. More information in MUSE OA content is available at https://about.muse.jhu.edu/muse/open-access-overview/.