How to access Pew Research Center survey data | Pew Research Center

“Pew Research Center regularly makes the full datasets behind our survey reports available to the public for free. In this post, we’ll explain exactly how you can download these datasets and begin to analyze our survey findings yourself.

We typically do not publish datasets at the same time as we publish reports, and the lag time varies by study. That’s because it takes some time for us to complete all of our own reporting for a given study and to prepare the data for public release. We “clean” our survey datasets in this way to make them easier to use and to remove any information that could be used to identify individual poll respondents. Protecting confidentiality also means we never release some datasets of rare populations (for instance, surveys of scientists or foreign policy experts)….”

‘New journals concept’ from CUP’s Research Directions | The Bookseller

“Cambridge University Press is launching an initiative it describes as a “new concept” for the journal, bringing researchers from different fields together to explore fundamental questions which cut across traditional disciplines.

Research Directions is the brainchild of Fiona Hutton, CUP executive publisher and its head of STM Open Access publishing. A former research scientist, Hutton wants to provide alternatives to traditional journal formats and bring communities together to frame research to problems that no one discipline would be able to tackle alone, said the publisher.

CUP said the approach would “speed discovery by fostering collaboration and knowledge sharing between subject communities” as well as provide “opportunities to publish research from areas not well served by traditional, discipline-specific journals”. 

The first titles under the Research Directions banner will be published in 2022, with an initial set of questions to answer, informed by feedback from hundreds of researchers. The publishing model will “mirror the research lifecycle”, with the results, analysis and impact reviews all published as separate, Open Access, peer-reviewed and citable outputs on CUP’s Cambridge Core platform….”

Transform to Open Science (TOPS) | Science Mission Directorate

“From 2022 to 2027, TOPS will accelerate the engagement of the scientific community in open science practices through events and activities aimed at:

Lowering barriers to entry for historically excluded communities
Better understanding how people use NASA data and code to take advantage of our big data collections
Increasing opportunities for collaboration while promoting scientific innovation, transparency, and reproducibility….”

Open Science and Data Policy Developments: Virtual SciDataCon 2021 Strand – CODATA, The Committee on Data for Science and Technology

“Virtual SciDataCon 2021 is organised around a number of thematic strands.  This is the third of a series of announcements presenting these strands to the global data community. Please note that registration is free, but participants must register for each session they wish to attend.

The  COVID-19 pandemic has demonstrated some of the benefits of Open Science practices, while highlighting persistent shortcomings in current science system. The deepening climate crisis underlines the need for targeted data gathering and action oriented research. In the policy sphere, 2021 started with the adoption of the ‘Recommendation of the OECD Council concerning Access to Research Data from Public Funding’.  November should see the adoption of a Recommendation on Open Science by the UNESCO General Conference: a major achievement which it is hoped will have a mobilising effect on Members States world-wide. The UNESCO Recommendation defines shared values and principles for Open Science, and identifies concrete measures on Open Science, with proposals to bring citizens closer to science and commitments to facilitate the production and dissemination of scientific knowledge around the world.

On Tuesday 19 October, SciDataCon will host a strand of session exploring these and other important Open Science and data policy developments.  Two sessions relate to the implementation of the OECD Recommendation. The third will include an update on the UNESCO Recommendation and other developments….”

Metrics for Data Repositories and Knowledgebases: Working Group Report | Data Science at NIH

“The National Institutes of Health (NIH) Data Resources Lifecycle and Metrics Working Group and Metrics for Repositories (MetRe) subgroup have released “Metrics for Data Repositories and Knowledgebases: A Working Group Report”. This report presents the findings of an exploration of the current landscape of biomedical data repository metrics. The work was carried out in two phases consisting of a small pilot (phase 1) and a public survey (phase 2).

Below is an excerpt from the report:

“This report includes input from representatives of 13 NIH repositories from Phase 1 and 92 repository managers in Phase 2. The metrics these respondents reported using are divided into several broad categories, including (from most to least commonly collected) User Behavior Characteristics, Scientific Contribution/Impact, and Repository Operations, and the respondents from the two groups reported similar patterns in the metrics they collect. The majority of respondents (77%) also indicated a willingness to share their metrics data – an encouraging finding given that such metrics can be helpful to NIH in better understanding how datasets and repositories are used.” …”

The OpenNeuro resource for sharing of neuroscience data | eLife

Abstract:  The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlight the importance of the Brain Imaging Data Structure (BIDS) standard for enabling effective curation, sharing, and reuse of data. The archive presently shares more than 600 datasets including data from more than 20,000 participants, comprising multiple species and measurement modalities and a broad range of phenotypes. The impact of the shared data is evident in a growing number of published reuses, currently totalling more than 150 publications. We conclude by describing plans for future development and integration with other ongoing open science efforts.

 

Responsible Research Network, Finland | DORA

“Finland is among the first countries to have developed national recommendations on responsible research evaluation. In 2020, a task force formed by the Federation of Finnish Learned Societies published the “Good Practice in Researcher Evaluation: Recommendation for Responsible Evaluation of a Researcher in Finland.”1 A major driver for the national recommendation was the need to make conscious decisions in evaluation processes. Although many national entities were involved in developing the Recommendation, the approach is considered “bottom-up” and there was broad and enthusiastic buy-in among Finnish academic stakeholders….

A national task force was founded based on shared concerns identified by learned societies, research funders, policy organizations, publishers, national open science coordination, and the national research integrity board. While many national entities were involved in the Recommendation’s creation, the approach is considered “bottom-up”; in Finland there is a historic culture of autonomy for academic stakeholders….

In addition, the Recommendation timing coincided with the uptake of FAIR (findable, accessible, interoperable, and reusable) data and open science initiatives in Finland. These initiatives incentivize and reward researchers for producing open and FAIR data, and align with the Recommendation. In the coming years, the focus will be on building the capacity to move evaluation practices beyond quantitative publication metrics and in closer alignment with the goals of the Recommendation….”

What a difference a data repository makes: Six ways depositing data maximizes the impact of your science – The Official PLOS Blog

“1. You can’t lose data that’s in a public data repository…

2. Public data repositories support understanding, reanalysis and reuse…

3. Public data repositories facilitate discovery…

4. Public data repositories reflect the true value of data…

5. Public data demonstrates rigor…

6. Research with data in public data repositories attracts more citations…”

 

International Survey on Data Sharing and Re-use in Traumatic Stress Research

“The Global Collaboration on Traumatic Stress, a coalition of 11 scientific societies in the field of traumatic stress, is conducting a survey to better understand traumatic stress researchers’ opinions and experiences regarding data sharing and data re-use.

If you are a traumatic stress researcher at any career stage (including trainees) we invite you to share your opinions and experiences by participating in this survey. …”

A Survey of Researchers’ Needs and Priorities for Data Sharing

Abstract:  One of the ways in which the publisher PLOS supports open science is via a stringent data availability policy established in 2014. Despite this policy, and more data sharing policies being introduced by other organizations, best practices for data sharing are adopted by a minority of researchers in their publications. Problems with effective research data sharing persist and these problems have been quantified by previous research as a lack of time, resources, incentives, and/or skills to share data.

In this study we built on this research by investigating the importance of tasks associated with data sharing, and researchers’ satisfaction with their ability to complete these tasks. By investigating these factors we aimed to better understand opportunities for new or improved solutions for sharing data.

In May-June 2020 we surveyed researchers from Europe and North America to rate tasks associated with data sharing on (i) their importance and (ii) their satisfaction with their ability to complete them. We received 617 completed responses. We calculated mean importance and satisfaction scores to highlight potential opportunities for new solutions to and compare different cohorts.

Tasks relating to research impact, funder compliance, and credit had the highest importance scores. 52% of respondents reuse research data but the average satisfaction score for obtaining data for reuse was relatively low. Tasks associated with sharing data were rated somewhat important and respondents were reasonably well satisfied in their ability to accomplish them. Notably, this included tasks associated with best data sharing practice, such as use of data repositories. However, the most common method for sharing data was in fact via supplemental files with articles, which is not considered to be best practice.

We presume that researchers are unlikely to seek new solutions to a problem or task that they are satisfied in their ability to accomplish, even if many do not attempt this task. This implies there are few opportunities for new solutions or tools to meet these researcher needs. Publishers can likely meet these needs for data sharing by working to seamlessly integrate existing solutions that reduce the effort or behaviour change involved in some tasks, and focusing on advocacy and education around the benefits of sharing data.

There may however be opportunities – unmet researcher needs – in relation to better supporting data reuse, which could be met in part by strengthening data sharing policies of journals and publishers, and improving the discoverability of data associated with published articles.

Data Steward Research Data Management (RDM) | Technische Universiteit Eindhoven

“We are looking for a research data management specialist (data steward) with an enterprising and customer-oriented attitude, who will shape RDM support to the university’s researchers. You will support researchers in addressing internal and external requirements with regards to RDM, applying FAIR principles to research data, and so contribute to reuse and reproducibility of research. Your work will cover a broad scope of topics, which vary from assistance in RDM planning, advice on storage, archiving and publication of research data, handling privacy-sensitive data, policy making, to providing and developing training in RDM skills. You will serve as first line of support for privacy-related matters, working closely with the Privacy team and performing the first assessment of the privacy compliance in research projects….”

Data sharing policies: share well and you shall be rewarded | Synthetic Biology | Oxford Academic

Abstract:  Sharing research data is an integral part of the scientific publishing process. By sharing data, authors enable their readers to use their results in a way that the textual description of the results does not allow by itself. In order to achieve this objective, data should be shared in a way that makes it as easy as possible for readers to import them in computer software where they can be viewed, manipulated and analyzed. Many authors and reviewers seem to misunderstand the purpose of the data sharing policies developed by journals. Rather than being an administrative burden that authors should comply with to get published, the objective of these policies is to help authors maximize the impact of their work by allowing other members of the scientific community to build upon it. Authors and reviewers need to understand the purpose of data sharing policies to assist editors and publishers in their efforts to ensure that every article published complies with them.

Equitable data sharing in epidemics and pandemics | BMC Medical Ethics | Full Text

Abstract:  Background

Rapid data sharing can maximize the utility of data. In epidemics and pandemics like Zika, Ebola, and COVID-19, the case for such practices seems especially urgent and warranted. Yet rapidly sharing data widely has previously generated significant concerns related to equity. The continued lack of understanding and guidance on equitable data sharing raises the following questions: Should data sharing in epidemics and pandemics primarily advance utility, or should it advance equity as well? If so, what norms comprise equitable data sharing in epidemics and pandemics? Do these norms address the equity-related concerns raised by researchers, data providers, and other stakeholders? What tensions must be balanced between equity and other values?

Methods

To explore these questions, we undertook a systematic scoping review of the literature on data sharing in epidemics and pandemics and thematically analyzed identified literature for its discussion of ethical values, norms, concerns, and tensions, with a particular (but not exclusive) emphasis on equity. We wanted to both understand how equity in data sharing is being conceptualized and draw out other important values and norms for data sharing in epidemics and pandemics.

Results

We found that values of utility, equity, solidarity, and reciprocity were described, and we report their associated norms, including researcher recognition; rapid, real-time sharing; capacity development; and fair benefits to data generators, data providers, and source countries. The value of utility and its associated norms were discussed substantially more than others. Tensions between utility norms (e.g., rapid, real-time sharing) and equity norms (e.g., researcher recognition, equitable access) were raised.

Conclusions

This study found support for equity being advanced by data sharing in epidemics and pandemics. However, norms for equitable data sharing in epidemics and pandemics require further development, particularly in relation to power sharing and participatory approaches prioritizing inclusion. Addressing structural inequities in the wider global health landscape is also needed to achieve equitable data sharing in epidemics and pandemics.