4Science, share your knowledge: research data and digital libraries

“Our mission is to support universities, research and cultural institutes in managing the different phases of a digital project.

To successfully fulfill this mission 4Science chose DSpace, the most widely used repository software in the world.

As a DSpace Registered Service Provider and thanks to our Team of experts, that includes 2 DSpace Committers, we provide any kind of support to your repository.

4Science is constantly working with the DSpace Community on improving the platform, developing new functionalities and add-on modules and implementing compliancy with international standards.

Thanks to our natural inclination towards innovation and our deep understanding of the Research Data & Information and the Cultural Heritage domains, we developed two out-of-the-box configurations of DSpace that meet the requirements of these two areas….”

Sharing and organizing research products as R packages | SpringerLink

Abstract:  A consensus on the importance of open data and reproducible code is emerging. How should data and code be shared to maximize the key desiderata of reproducibility, permanence, and accessibility? Research assets should be stored persistently in formats that are not software restrictive, and documented so that others can reproduce and extend the required computations. The sharing method should be easy to adopt by already busy researchers. We suggest the R package standard as a solution for creating, curating, and communicating research assets. The R package standard, with extensions discussed herein, provides a format for assets and metadata that satisfies the above desiderata, facilitates reproducibility, open access, and sharing of materials through online platforms like GitHub and Open Science Framework. We discuss a stack of R resources that help users create reproducible collections of research assets, from experiments to manuscripts, in the RStudio interface. We created an R package, vertical, to help researchers incorporate these tools into their workflows, and discuss its functionality at length in an online supplement. Together, these tools may increase the reproducibility and openness of psychological science.

 

Being Fair about the Design of FAIR Data Standards | Zenodo

Abstract:  Since 2014 the FAIR data movement has been rapidly altering the landscape of data sharing and re-use. Support for the FAIR movement has seen the evolution of disciplinary-specific standards to foster data that are “finable, accessible, interoperable and reusable.” While these exciting developments should not be minimised, it is important to interrogate how these standards are set. Key questions to ask include how representation in standard setting communities is addressed; what infrastructures and resources these emergent standards are reliant on; and how standards dictate specific interpretations of “value” and “valuable data.” Asking such questions introduces a needed reflexivity into FAIR discussions, as standard setters interrogate what data practices commit present—and future—researchers to.

Celebrating the Five Year Anniversary of the UK ORCID Consortium – Jisc scholarly communications

“August 2020 sees the 5-year anniversary of the UK ORCID consortium. The evolution of ORCID and the UK Consortium can be viewed as a change programme. If we look back and reflect, what have been the drivers for change and what improvements can we celebrate?…

The range and complexity of outputs that ORCID identifiers are associated with has expanded as well, as new systems and ways of capturing information emerge – especially as we move to a data rich, information-centric open science model of scholarship. As such, the power of interconnected PIDs with the personal identifier of ORCID ID embedded, gives deeply intertwined and more useful information. These potential benefits can be realised as the various systems and identifiers mature and adoption improves. Examples of associations with unique persistent person identities are: works (e.g. works identified with a DOI); organisations (identified, for example with a ROR id); affiliations and workflows which can be examined via the events captured in PID Graphs. A project identifier such as RAiD allows you to associate people, data, works and funding with a long term effort, track the impact of efforts over the long term, and focus on the narrative, rather than a particular researcher or funding stream. This evolving landscape of interconnection allows us to build better, more effective scholarly machines, to do open research on a better, more cohesive and collaborative scale….”

Data Sharing in a Time of Pandemic: Patterns

“The resulting recommendations and guidelines on data sharing,

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 published in final form on Jun 30, 2020, are a thorough and comprehensive overview of how to share data (and research software) from multiple disciplines to inform response to a pandemic, along with guidelines and recommendations on data sharing under the present COVID-19 circumstances. It is a long document (more than 140 pages) but is very thorough and well structured….”

FAIRsFAIR

“FAIRsFAIR – Fostering Fair Data Practices in Europe – aims to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle. Emphasis is on fostering FAIR data culture and the uptake of good practices in making data FAIR. FAIRsFAIR will play a key role in the development of global standards for FAIR certification of repositories and the data within them contributing to those policies and practices that will turn the EOSC programme into a functioning infrastructure.

In the end, FAIRsFAIR will provide a platform for using and implementing the FAIR principles in the day to day work of European research data providers and repositories. FAIRsFAIR will also deliver essential FAIR dimensions of the Rules of Participation (RoP) and regulatory compliance for participation in the EOSC. The EOSC governance structure will use these FAIR aligned RoPs to establish whether components of the infrastructure function in a FAIR manner….”

Persistent identifiers and Open Access in the UK: The way forward

“By providing information on the use of persistent identifiers (PIDs) in the research ecosystem, you agree that you have asked us to process it as described in our standard privacy notice at https://www.jisc.ac.uk/website/privacy-notice. You may instruct us to stop processing it at any time by emailing help@jisc.ac.uk. Until then, we’ll use it to inform work being carried out by Jisc to support the UK’s compliance with Plan S. …”

Persistent identifiers and open access in the UK: the way forward | Jisc

“Today, more than ever, a resilient and efficient research infrastructure is critically important. Persistent identifiers (PIDs) are an essential element of global research data infrastructures and have become central to building and maintaining reliable and robust links between people, communities and infrastructures.

Professor Adam Tickell’s 2018 independent advice to the UK government on open access to research publications, included a recommendation for Jisc to “lead on selecting and promoting a range of unique identifiers … in collaboration with sector leaders with relevant partner organisations”.

During this online event, we will share progress made towards implementing this recommendation and establishing a persistent identifier roadmap for open access – and open research more broadly – in in the UK. We will highlight the role PIDs can play in improving open access workflows, in the context of Plan S requirements and the recently published UKRI OA review.

You will hear from practitioners, as well as from the Jisc team working on the project. And we want to hear from you too, so there will be plenty of time for Q&A….”

The DataCite MDC Stack

“In May, the Make Data Count team announced that we have received additional funding from the Alfred P. Sloan Foundation for work on the Make Data Count (MDC) initiative. This will enable DataCite to do additional work in two important areas:

Implement a bibliometrics dashboard that enables bibliometricians – funded by a separate Sloan grant – to do quantitative studies around data usage and citation behaviors.

Increase adoption of standardized data usage across repositories by developing a log processing service that offloads much of the hard work from repositories.

In this blog post, we want to provide more technical details about the upcoming work on the bibliometrics dashboard; the log processing service will be the topic of a future blog post. The bibliometrics dashboard will be based on several important infrastructure pieces that DataCite has built over the past few years, and that are again briefly described below….”

Montreal Statement | Sustainability in the Digital Age

“OPEN AND TRANSPARENT ACCESS TO DATA AND KNOWLEDGE CRITICAL TO ACHIEVING ENVIRONMENTAL SUSTAINABILITY AND SOCIAL EQUITY

Colossal quantities of data are produced and made accessible as a result of the digital age. Nevertheless, much of the data most valuable for building a climate-safe and equitable world are either not available for public use or are simply not being collected. As AI is increasingly turning collected data into usable knowledge, steps that could ensure open access to this critical data and knowledge include:

The creation and support of multi-stakeholder, consensus-based processes to identify priority data needed in the public domain. This includes understanding:

What data, critical for environmental sustainability and social equity, already exists in private or public domains? Who is harvesting and providing such data, and who has access to them?

What critical data is missing and how can they be obtained?

What are the environmental and social costs of data collection, storage, and use?…

This entails developing standards—such as providing for data transparency, traceability, ownership, and anonymity—to ensure that data for public use is of the highest quality, and is widely accessible and usable….”

 

Montreal Statement | Sustainability in the Digital Age

“OPEN AND TRANSPARENT ACCESS TO DATA AND KNOWLEDGE CRITICAL TO ACHIEVING ENVIRONMENTAL SUSTAINABILITY AND SOCIAL EQUITY

Colossal quantities of data are produced and made accessible as a result of the digital age. Nevertheless, much of the data most valuable for building a climate-safe and equitable world are either not available for public use or are simply not being collected. As AI is increasingly turning collected data into usable knowledge, steps that could ensure open access to this critical data and knowledge include:

The creation and support of multi-stakeholder, consensus-based processes to identify priority data needed in the public domain. This includes understanding:

What data, critical for environmental sustainability and social equity, already exists in private or public domains? Who is harvesting and providing such data, and who has access to them?

What critical data is missing and how can they be obtained?

What are the environmental and social costs of data collection, storage, and use?…

This entails developing standards—such as providing for data transparency, traceability, ownership, and anonymity—to ensure that data for public use is of the highest quality, and is widely accessible and usable….”

 

Welcome — The Turing Way

“The Turing Way is an open source community-driven guide to reproducible, ethical, inclusive and collaborative data science.

Our goal is to provide all the information that data scientists in academia, industry, government and in the third sector need at the start of their projects to ensure that they are easy to reproduce and reuse at the end.

The book started as a guide for reproducibility, covering version control, testing, and continuous integration. But technical skills are just one aspect of making data science research “open for all”.

In February 2020, The Turing Way expanded to a series of books covering reproducible research, project design, communication, collaboration, and ethical research.”