“The purpose of this survey is to ascertain the support for such a standard and to identify blockers to implementation. The focus of this work is on interoperability and standards that enable and further open exchange of information, knowledge and data across systems and technologies …”
“The U.S. Government Publishing Office (GPO) has once again made history by becoming the only organization to maintain the highest global standard of excellence for digital repositories. GPO successfully completed its second yearly surveillance audit that is required to maintain its ISO 16363 Trustworthy Digital Repository certification for govinfo, the one-stop site for authentic information published by the Government. GPO achieved the certification by meeting official criteria for trustworthy digital repositories as defined by experts in the field….”
Abstract: Modern microscopes used for biological imaging often present themselves as black boxes whose precise operating principle remains unknown, and whose optical resolution and price seem to be in inverse proportion to each other. With UC2 (You. See. Too.) we present a low-cost, 3D-printed, open-source, modular microscopy toolbox and demonstrate its versatility by realizing a complete microscope development cycle from concept to experimental phase. The self-contained incubator-enclosed brightfield microscope monitors monocyte to macrophage cell differentiation for seven days at cellular resolution level (e.g. 2??m). Furthermore, by including very few additional components, the geometry is transferred into a 400 Euro light sheet fluorescence microscope for volumetric observations of a transgenic Zebrafish expressing green fluorescent protein (GFP). With this, we aim to establish an open standard in optics to facilitate interfacing with various complementary platforms. By making the content and comprehensive documentation publicly available, the systems presented here lend themselves to easy and straightforward replications, modifications, and extensions.
“At the end of 2012, just three months after we launched the ORCID registry, we were thrilled to be able to share that nearly 50,000 researchers had already registered for an iD. Ten months after that, we celebrated the ORCID record growing to nearly 250,000 (with 80 Members!) All told, it took us just a little over two years to grow to 1,000,000 iDs, and nine months after that, in 2015, we hit 1.5 million iDs.
Since 2015 we’ve been steadily growing and exceeding even our own high expectations:
In 2015, the record grew by 788,650 records,
In 2016, by 1,068,295,
In 2017, 1,388,796,
In 2018, it grew by 1,585,851,
In 2019, by 2,006,672, and
In 2020 (so far), it’s grown by 2,293,631!
And just last week ORCID hit another major milestone: 10 million registered ORCID iDs! …”
“The National Information Standards Organization (NISO) announced today that their Voting Members have approved a new work item to update the 2008 Recommended Practice, NISO RP-8-2008, Journal Article Versions (JAV): Recommendations of the NISO/ALPSP JAV Technical Working Group. A NISO Working Group is being set up, and work is expected to begin in early 2021.
Publication practices have changed rapidly since the publication of the original recommendations. For example, preprints have become much more important as a publication type in many disciplines, and publishers are increasingly experimenting with new ways to publish, update, and keep research alive. All of these versions of an article are important and citable, making the concept of a single ‘version of record’ less relevant. These additional processes to support public availability make the consistent assignment of DOIs to one or more versions challenging.
The NISO JAV working group will define a set of terms for each of the different versions of content that are published, as well as a recommendation for whether separate DOIs should be assigned to them. They will address questions such as: Should there be a single DOI for an article, regardless of version? Different DOIs for each version? How are the identifiers connected and used? How do we define a version? As with all NISO output, the group’s draft recommendations will be shared for public comment before publication….”
“1) Voted YES on Approval of Proposed New Work Item: Update NISO RP-8-2008, Journal Article Versions (JAV)
Do you approve of a Proposed New Work Item: Update NISO RP-8-2008, Journal Article Versions (JAV)?
This ballot is to approve a proposed new work item to Update NISO RP-8-2008, Journal Article Versions (JAV) [https://www.niso.org/publications/niso-rp-8-2008-jav] to take into account publication practices that have been adopted over the past 12 years, especially the increasing circulation of preprints and the application of DOIs across the landscape….”
“Service providers could benefit from:
Sharing lessons learnt. This might involve developing communities of practice and guidance; pooling resources and working with initiatives such as Invest in Open Infrastructure (IOI) and JROST.
Following good governance practices. This allows the community to trust that the infrastructure or service will be steered by the needs of the community and stay true to the values of research.
Going open source and adopting open standards. “Despite a strong uptake of open source and open standards by many, challenges remain for some in sharing good governance, open content and applying open standards,” wrote the authors.
Diversifying fund-raising efforts, upskilling to embrace a range of business revenue models. This allows the organisation to spread financial risk….”
“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 …”
“A stakeholder group was therefore formed earlier this year, with representatives from all disciplines and sectors — funders, HEIs, infrastructure providers, libraries, publishers, researchers, research managers, and more. At an initial meeting of this group in April, participants discussed the five persistent identifiers (PIDs) that have been deemed high priority for improving access to UK research. These are ORCID iDs for people, Crossref and DataCite DOIs for outputs, Crossref grant DOIs, ROR identifiers for organisations, and RAiDs for projects. This was followed by five focus group meetings during May and June, each focused on one of the priority PIDs….”
“A “nutrition label” for datasets.
The Data Nutrition Project aims to create a standard label for interrogating datasets for measures that will ultimately drive the creation of better, more inclusive algorithms.
Our current prototype includes a highly-generalizable interactive data diagnostic label that allows for exploring any number of domain-specific aspects in datasets. Similar to a nutrition label on food, our Dataset Nutrition Label aims to highlight the key ingredients in a dataset such as meta-data and populations, as well as unique or anomalous features regarding distributions, missing data, and comparisons to other ‘ground truth’ datasets. We are currently testing our label on several datasets, with an eye towards open sourcing this effort and gathering community feedback.
The design utilizes a ‘modular’ framework that can be leveraged to add or remove areas of investigation based on the domain of the dataset. For example, Dataset Nutrition Labels for data about people may include modules about the representation of race and gender, while Nutrition Labels for data about trees may not require that module.
To learn more, check out our live prototype built on the Dollars for Docs dataset from ProPublica. A first draft of our paper can be found here….”