“Inspired by the ancient Library of Alexandria, OpenAlex indexes the world of scholarly research, including works, citations, authors, journals, and institutions. OpenAlex data is completely free and open to all via a web interface, API, and database snapshot. Join us to learn how to use the OpenAlex API for your scholcomm research needs. OpenAlex was created by OurResearch, a nonprofit that makes open scholarly infrastructure including Unpaywall (an index of the world’s Open Access research literature) and Unsub (a tool to help librarians eliminate toll-access journal subscriptions). …”
“Use of our Academic Graph API has accelerated since our upgrade release in 2021. Many users would like to fetch data for a large number of papers according to their own criteria, but making individual API calls for each paper is slow and expensive. We have encouraged users to use our full-corpus S2AG (Semantic Scholar Academic Graph) dataset, but this has previously not always been possible because of discrepancies between the dataset and the API. Our new datasets give users access to the full range of data exposed in our API for the entirety of our corpus….”
“We’ve got a ton of great API improvements to report! If you’re an API user, there’s a good chance there’s something in here you’re gonna love.
You can now search both titles and abstracts. We’ve also implemented stemming, so a search for “frogs” now automatically gets your results mentioning “frog,” too. Thanks to these changes, searches for works now deliver around 10x more results. This can all be accessed using the new search query parameter.
New entity filters
We’ve added support for tons of new filters, which are documented here. You can now:
get all of a work’s outgoing citations (ie, its references section) with a single query.
search within each work’s raw affiliation data to find an arbitrary string (eg a specific department within an organization)
filter on whether or not an entity has a canonical external ID (works: has_doi, authors: has_orcid, etc) ….”
The aims of the study were to identify publicly available patient safety report databases and to determine whether these databases support safety analyst and data scientist use to identify patterns and trends.
An Internet search was conducted to identify publicly available patient safety databases that contained patient safety reports. Each database was analyzed to identify features that enable patient safety analyst and data scientist use of these databases.
Seven databases (6 hosted by federal agencies, 1 hosted by a nonprofit organization) containing more than 28.3 million safety reports were identified. Some, but not all, databases contained features to support patient safety analyst use: 57.1% provided the ability to sort/compare/filter data, 42.9% provided data visualization, and 85.7% enabled free-text search. None of the databases provided regular updates or monitoring and only one database suggested solutions to patient safety reports. Analysis of features to support data scientist use showed that only 42.9% provided an application programing interface, most (85.7%) provided batch downloading, all provided documentation about the database, and 71.4% provided a data dictionary. All databases provided open access. Only 28.6% provided a data diagram.
Patient safety databases should be improved to support patient safety analyst use by, at a minimum, allowing for data to be sorted/compared/filtered, providing data visualization, and enabling free-text search. Databases should also enable data scientist use by, at a minimum, providing an application programing interface, batch downloading, and a data dictionary.
“A fully-featured, mature, and 100% open source DMS [data management system].”
“This short course provides training materials about how to create a set of publication data, gather additional information about the data through an API (Application Programming Interface), clean the data, and analyze the data in various ways. The API that we’ll use is from Unpaywall and helps gather information related to the open access (OA) status of the item. This short course was created for the Scholarly Communication Notebook. If open access is new to you, we recommend checking out Peter Suber’s book Open Access. It’s concise and well written. Although things have changed since it was published in 2012, it’s a great place to start….”
“CORE has just released a major update to its search engine, including a sleek new user interface and upgraded search functionality driven by the new CORE API V3.0.
CORE Search is the engine that researchers, librarians, scholars, and others turn to for open access research papers from around the world and for staying up to date on the latest scientific literature….”
“This time there is a release from our friends at the Open Access Helper. This is a tool that helps everyone discover a legal Open Access version of research outputs around the web.
What is new with this version is the application’s ability to bring to researchers proactive notifications on their iPad and iPhone whenever they are browsing articles behind a paywall.
We are really excited about this release because it is integrating our brand new CORE API (v3). …”
“Many institutions have reported that participation rates of article deposit in their IR are low regardless of their various efforts in outreach and engagement. Even when the deposit is mandated, the participation rate can still be quite low.
Once this hurdle was overcome, there is another challenge faced by the IR administrators, ensuring that the version submitted by the researcher is the appropriate version. If it is not, IR administrators would need to take additional steps to correspond with the researcher to obtain the appropriate version. Thus, increasing their administrative work load.
Therefore, some institutions had taken the pro-active initiative to complete the deposit on behalf of their researchers. This certainly is not a small undertaking. However, there are openly available R packages (https://ropensci.org/) that can be used to automate some of the processes. In this page, I will summarize the steps to do that….”
“On Thursday 13th January 2022, Petr Knoth, Head of CORE and Matteo Cancellieri, Lead Developer, gave a webinar describing the new CORE APIv3 features. There were 72 attendees. In the first part, we introduced new features in the API, and the second part provided live coding examples followed by answering questions from the audience.
The CORE APIv3 has already been released into production, and we encourage existing and new users of CORE to move to it. At a glance, the new APIv3 offers:
An extended model of the CORE resources to link different versions of a paper. ?
Support for medium-size datasets collection.?
Improved analytical tools?.
User management made easier?.
A gallery to kick start your journey with the API….”
“Earlier this year, Ginny posted an exciting update on Crossref’s progress with adopting ROR, the Research Organization Registry for affiliations, announcing that we’d started the collection of ROR identifiers in our metadata input schema.
The capacity to accept ROR IDs to help reliably identify institutions is really important but the real value comes from their open availability alongside the other metadata registered with us, such as for publications like journal articles, book chapters, preprints, and for other objects such as grants. So today’s news is that ROR IDs are now connected in Crossref metadata and openly available via our APIs….
Now that this metadata is available, it helps confer the downstream benefits of ROR for different (and interconnected) groups:
It makes it easier for institutions to find and measure their research output by the articles their researchers have published, or perhaps make it easier to track the grants they’ve received.
Funders need to be able to discover and track the research and researchers they have supported.
Academic librarians need to easily find all of the publications associated with their campus.
Journals need to know where authors are affiliated so they can determine eligibility for institutionally sponsored publishing agreements.
Editors can use more accurate information on author and reviewer institutions during the peer review process, which can help avoid potential conflicts of interest….”
“OpenAlex launched this week! (January 3rd 2022 for those reading from the future)
We’re now pulling in new content on our own. Until now, we’ve been getting new works, authors, and other entities from MAG. Now that MAG is gone, we’re gathering all of our own data from the big wide internet.
The new REST API is launched! This is a much faster and easier way to access the OpenAlex database than downloading and installing the snapshot. It’s completely open and free–you don’t even need a user account or token.
We’ve now got oodles of new documentation here: https://docs.openalex.org/
Slight change of plan:
The MAG Format snapshot is now hosted for free, thanks to the AWS Open Data program. This will cover the data transfer fees (which turned out to be $70!) so you don’t have to. Here are the new instructions on how to download the MAG format snapshot to your machine.
We are extending the beta period for OpenAlex; we’ll emerge from beta in February. This is mostly in response to discovering issues with the coverage and structure of existing data sources including MAG. Extending the beta reflects the fact that the data will improve significantly between now and February.
Huge exciting news:
OpenAlex was built to offer a drop-in replacement for MAG. We’re doing that. But today, we’re also unveiling some moves toward a more innovative future for Openalex:
We’ve now built around a simple new five-entity model: works, authors, venues (journals and repositories), institutions, and concepts. Everything in OpenAlex is one of these entities, or a connection between them. Each type of entity has its own API endpoint.
We’ve got a new Standard Format for the snapshot, one that’s closely tied to both the five-entity model the API. In the future, this will become the only supported format. The MAG format is now deprecated and will go away on July 1, 2022. …”
“OpenAlex is a fully open catalog of the global research system. It’s named after the ancient Library of Alexandria.
The OpenAlex dataset describes scholarly entities and how those entities are connected to each other. There are five types of entities:
Works are papers, books, datasets, etc; they cite other works
Authors are people who create works
Venues are journals and repositories that host works
Institutions are universities and other orgs that are affiliated with works (via authors)
Concepts tag Works with a topic
Together, these make a huge web (or more technically, heterogeneous directed graph) of of hundreds of millions of entities and over a billion connections between them all….”
Abstract: The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.
“We’re delighted to announce a new partnership between CORE and Cypris, a leading AI-driven, market intelligence platform that connects research & development (R&D) teams with innovation data and trends in their field.
The partnership will provide Cypris with unlimited access to over 210 million open access articles to further enhance their platform and regularly add live market data to provide R&D teams with the most up-to-date research in their fields of interest….”