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.
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.
“On the ScienceOpen platform, the search engine that powers our discovery database is unique in that it is front and center on each new search—without any barricades, inviting all users to tinker with and explore content with it. Excitingly, the ScienceOpen technical team has recently upgraded the search functionalities on the site to be even more advanced and user-friendly! …”
“Ten months into the NIH Preprint Pilot, more than 2,100 preprints reporting NIH-supported research on COVID-19 are now discoverable in PubMed Central (PMC) and PubMed. Through early April 2021, these records have been viewed more than 1 million times in each of these databases (1.4 million in PMC; 1 million in PubMed). Of the preprints included in the pilot, ~60% are currently discoverable only as a preprint version, having not yet been linked to a published article. All articles are clearly identified as preprints. Preprints may be selected or excluded in searches by using the preprint filter.
The pilot launched in June 2020 with preprint records from medRxiv, bioRxiv, arXiv, ChemRxiv, Research Square, and SSRN. Phase 1 has focused on improving the discoverability of preprints relating to the ongoing public health emergency and accelerating dissemination of NIH-supported research on the SARS-CoV-2 virus and COVID-19. This narrowly scoped first phase has allowed the National Library of Medicine (NLM) to streamline curation and ingest workflows for NIH-supported preprints and refine the details of implementation with a set of articles for which there has been high demand for accelerated access and discovery. Since launching the pilot, NLM has made display of preprint records in PubMed search results more transparent. We have also automated checks for new preprint versions and preprint withdrawals, and reduced the steps required to report preprints as products of awards in My Bibliography….”
“An efficient strategy for searching for adverse events in scientific literature should find as many relevant events as possible and maintain screening effort within reasonable levels.
Naturally, finding more adverse events is directly related to the question of where to search. Past studies suggest results do improve when searching multiple established proprietary global literature databases. We decided to investigate databases that favor open models of scholarly publications, now gaining traction in the academic world. Can they be a cost-effective way to more adverse events results from the literature?
In this post, we investigate the use of alternative scientific literature sources to complement searching for adverse events on a mainstream index (PubMed). In particular we explored:
The Directory of Open Access Journals (DOAJ) indexes academic literature with an open access license from publishers worldwide. It currently hosts over 5 million records.
Crossref: a community organization dedicated to supporting scholarly communication by generating metadata and providing services for content discoverability. The Crossref metadata spans over 120 million records, with a growing proportion being published as open abstracts….”
“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….”
“The archive’s catalog currently holds more than 120 million digital records, as well as “archival metadata and other types of records, including electronic databases.” However, the system has “an unsophisticated search” function, according to a request for information.
While NARA employees add metadata tags to digital records, “There is a delta between what NARA has been able to describe and the specific information that users want from our records,” the RFI states, asking, “Can AI fill the gap?”
During an informational day held in early April, NARA executives outlined some of the challenge, including a single search returning a flood of results from the same source—making it difficult to sift through to find multiple sources—and difficulty distinguishing between records with similar names, such as a search for “Truman” the president versus “Truman” the aircraft carrier.
The current search function also is not able to return accurate results if the search term input is not exactly the same as it exists in the metadata.
The RFI is seeking feedback on automated solutions that can analyze how users search the digital archives and associate those search terms with the appropriate record….”
“Europe PMC (https://europepmc.org/?) is an open science platform that enables access to a worldwide collection of life science publications. Watch this video and see how Europe PMC helps the scientific community to complete their everyday tasks. Read more on the blog post: https://bit.ly/2QnZqNu?. …”
“For scientists to pull out detailed information like that, however, they first have to know that a particular specimen even exists. In 2011, the National Science Foundation started handing out grants as part of a ten-year push to bring old-fashioned collections into the Internet age. One of the goals was to put specimen records online and into a searchable portal called iDigBio….
Now, as that program winds down, he and other experts are pondering what needs to happen over the next decade so that biological collections can continue to become more accessible. That’s why the NSF recently asked for some advice from an expert panel convened by the National Academies of Sciences, Engineering, and Medicine.
One of its recommendations was simple: create a national registry of all collections, so experts know who’s got plants, microbes, or animals of interest.
The U.S. is thought to possess about 1,800 natural history collections, which is about a third of those that exist worldwide. In addition, the country has at least 2,800 “living stock” collections, such as microbe collections, which continually maintain living organisms for research….”
“In the early 2000s, my role at Google was running web indexing: the system that crawls the web, making pages and content discoverable and accessible through search. Nowadays, there’s an assumption that looking for something via Google searches everything, but that wasn’t the case in the early days. Part of my role was to expand the index by reaching out to many different types of organizations – government, business, publishers – to make sure their web sites were included in the index.
A key group among these was scholarly publishers hosting journals and conferences. Having grown up on a university campus, scholarly articles had been all around and I wanted to make sure that they were as easy to find as everything else.
As a part of this, I reached out to HighWire to explore the possibility of indexing the hosted journals. I remember our first call in the Fall of 2002 with John Sack, Todd McGee and several others. A few quick calls, a couple of meetings in person and we were off….”