CHORUS and DataCite sign MOU to advance linking and discoverability – CHORUS

“CHORUS and DataCite have signed a two-year Memorandum of Understanding (MOU) to coordinate efforts to adopt identifiers and standards to manage access to and reporting of research outputs.

Authoritative connections between researchers and their works, funding sources, and affiliations, are essential for delivering public access to scholarly content. As not-for-profit organizations engaged in supporting discoverability in scholarly communications, both DataCite and CHORUS have an important contribution to make creating and supporting these links.

The organizations commit to dialog and cooperation on the following topics:

Supporting simple and non-ambiguous links between datasets, researchers and their funding
Displaying links between CHORUS content and DataCite DOIs in the CHORUS dashboards and reports
Building awareness of DataCite services among funding agency researchers and administrators
Encouraging the use of persistent identifiers for researchers and organizations to support public access to research works …”

OCLC supports libraries, researchers, educators and students with open access content through WorldCat

“OCLC is supporting libraries, researchers, educators and students with high-quality open access content that is discoverable and freely accessible through WorldCat Discovery and….

OCLC is making open content more discoverable and accessible through expanding collections and user-friendly discovery services….”

The next generation discovery citation indexes — a review of the landscape in 2020 (I) | by Aaron Tay | Academic librarians and open access | Oct, 2020 | Medium

“In terms of cross disciplinary citation indexes that are used for discovery, everyone knows of the two incumbants — Web of Science and Scopus(2004). Joined by the large web scale Google Scholar (2004), these three reigned as the “Big 3” of citation indexes for roughly a decade more or less unchallenged.

However 10 years later, around 2015 and in the years after, a new generation of citation indexes started to emerge to challenge the big 3 in a variety of ways .

As of time of writing in 2020, some of these new challengers have had a couple of years of development. How do things look now?

First off, using newer techniques and paradigms, we have for-profit companies like Digital Science launching Dimensions (2018) which strike me as challengers to Scopus and Web of Science in the arena of citation/bibliometric assessment, just as Scopus itself was a challenge to the older Web of Science back in 2004.

On the other end of the spectrum we have the rise of more “open” citation indexes . In particular, a very important player in this area is the relaunched Microsoft Academic(2016) which not only uses web crawling style technologies like Google Scholar to scour the web, applies the latest in Natural Language Processing (NLP) /“semantic” technologies and makes the dataset dubbed Microsoft Academic Graph (MAG) available with open licenses.

Semantic Scholar(2015) is yet another project with Microsoft ties ( funded by the Allen Institute for AI) that play in the same area and releases data with open licenses. One of the more “Semantic” features of this search engine is that it types citations into whether the cite is for citing of background, methods or results using machine learning.

While scite (2018) a new citation index by a startup does not provide open data, it’s selling point is the use of NLP to type citation relationships into “Supporting”, “Disputing” and “Neutral” cites which is yet another way of contextualizing research by describin citation relationships.

Besides the two above mentioned well funded think tanks projects, we also see more grassroot like movements like 2017’s I4OC (Intiative for open Citations) — an amazingly successful push to get publishers to deposit and make references open in Crossref as well as efforts by (a founding member of I4OC) to extract citations from open access papers from PMC to produce the OpenCitations Corpus (OCC), which have served to further increase the pool of Scholarly meta-data and citations that are available in the public domain/CCO….”

Jisc – JSTOR Open Community Collections | About JSTOR

“Jisc and JSTOR are collaborating to support discovery, use, and impact of open digital collections for the benefit of the research and teaching community and collection owners. Jisc functions as the UK node for engagement with and take-up of the programme by UK universities with JSTOR providing the service delivery platform….”


GDD Network – AHRC Network for a global dataset of digitised texts

“What is the GDD Network?

Digital scholarship relies on access to digital sources but finding these sources, whether a large corpus for digital scholarship or a single text for in-depth study, is often difficult.

All around the world, libraries, archives and search providers are digitising collections to make them available. While this is making millions of texts available online, there is still no single place where you can search all of them at once.

The difficulty of discovering digitised texts, including but extending beyond the millions of items digitised by national libraries and mass digitisation programmes, often means that these efforts do not have the impact they could and should.

The Global Digitised Dataset Network (GDD Network) is a research collaboration investigating the feasibility of creating a global catalogue of digitised texts, which would enable people to search and find texts, and access them for reading, digital scholarship, collections analysis, and more….”

DataCite Commons – Discovering PIDs and the PID Graph

“DataCite recently launched DataCite Commons, a new discovery service which allows you to conduct simple searches across different types of PIDs giving a comprehensive overview of the connections between entities. DataCite Commons has been released as a minimum viable product and will be developed in the future. This webinar will present the new service and provide the background to it, including the user driven requirements gathering and give an opportunity for feedback on how much it meets your needs and what else you would like it to do….”

Artificial Intelligence for Data Discovery and Reuse (AIDR) Symposium 2020

“AIDR (Artificial Intelligence for Data Discovery and Reuse) aims to find innovative solutions to accelerate the dissemination and reuse of scientific data in the data revolution. The explosion in the volume of scientific data has made it increasingly challenging to find data scattered across various platforms. At the same time, increasing numbers of new data formats, greater data complexity, lack of consistent data standards across disciplines, metadata or links between data and publications makes it even more challenging to evaluate data quality, reproduce results, and reuse data for new discoveries. Last year, supported by the NSF scientific data reuse initiative, the inaugural AIDR 2019 attracted AI/ML researchers, data professionals, and scientists from biomedicine, technology industry, high performance computing, astronomy, seismology, library and information science, archaeology, and more, to share innovative AI tools, algorithms and applications to make data more discoverable and reusable, and to discuss mutual challenges in data sharing and reuse.

This year, we are following up with a one-day, virtual AIDR Symposium, that provides a place for the community to continue having these conversations and work together to build a healthy data ecosystem. The program will feature invited speakers and panel discussions from a variety of disciplines, including a focused session on COVID-19 data. Audience are highly encouraged to join the conversation by submitting a poster, joining the panel discussions and social hours, chatting on Slack, and participating in collaborative note-taking.”