The volume of data stored in research institutions is growing, and the rate at which it is growing is accelerating. Spending and effort and resources are being duplicated needlessly, and so this opinion piece argues for the establishment of a national infrastructure for research data management.
Open science should be boosted in 2020 as the number of journals with research data policies increases as a result of collective action by publishers, who are being encouraged to adopt a new common framework for journal data policies.
Science is built on trust. Trust that your experiments will work. Trust in your collaborators to pull their weight. But most importantly, trust that the data we so painstakingly collect are accurate and as representative of the real world as they can be. And so when I realized that I could no longer trust the data that I had reported in some of my papers, I did what I think is the only correct course of action. I retracted them.
European Science Cloud Will Uncover 'Hidden Treasure'
The European Open Science Cloud, an enormous repository of research results that is due to go live later this year, will add new value to vast stores of unused data, Ursula von der Leyen, European Commission president pledged on Wednesday.
What Researchers Think About the Culture They Work In: Quantitative Dataset
Here we present an anonymized version of the dataset that we collected in the quantitative phase of Wellcome's research on research culture. Additionally, we present a document detailing how the data was transformed to protect anonymity. We also present a flowchart that indicates how participants were guided to answer questions in the survey.
Towards a Community-endorsed Data Stewardship Profession
Data stewardship encompasses all of the various tasks and responsibilities that relate to research data management throughout the entire research lifecycle. It has been discussed at the 14th RDA Plenary in Helsinki by research, industry and policy experts.
Data Sharing at Scale: A Heuristic for Affirming Data Cultures
Addressing the most pressing contemporary social, environmental, and technological challenges will require integrating insights and sharing data across disciplines, geographies, and cultures. Strengthening international data sharing networks will not only demand advancing technical, legal, and logistical infrastructure for publishing data in open, accessible formats; it will also require recognizing, respecting, and learning to work across diverse data cultures. This essay introduces a heuristic for pursuing richer characterizations of the “data cultures” at play in international, interdisciplinary data sharing.
Engaging Researchers with Data Management: The Cookbook
Effective Research Data Management (RDM) is a key component of research integrity and reproducible research, and its importance is increasingly emphasised by funding bodies, governments, and research institutions around the world. However, many researchers are unfamiliar with RDM best practices, and research support staff are faced with the difficult task of delivering support to researchers across different disciplines and career stages. What strategies can institutions use to solve these problems? Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM.
$100M Health Initiative Aims to Democratize Data Science
Together with partners, the Rockefeller Foundation is working to improve access to data science tools for frontline health workers to prevent 6 million maternal and child deaths in 10 countries by 2030.
RDA and COAR Collaborate to Progress Research Data Management Internationally
The Research Data Alliance (RDA) and the Confederation of Open Access Repositories (COAR) are pleased to announce an agreement to work together to strengthen and expand capacities for research data management within the international data repository community.
Establishing, Developing, and Sustaining a Community of Data Champions
While research data support units now exist in many universities, these are typically not able to provide discipline-specific expertise or resources. This article focuses on the Data Champion Programme at the University of Cambridge, which empowers discipline-specific expertise already embedded within each unit to advocate for good RDM and to deliver support locally.
Figure Errors, Sloppy Science, and Fraud: Keeping Eyes on Your Data
Recent reports suggest that there has been an increase in the number of retractions and corrections of published articles due to post-publication detection of problematic data. Moreover, fraudulent data and sloppy science have long-term effects on the scientific literature and subsequent projects based on false and unreproducible claims. The JCI introduced several data screening checks for manuscripts prior to acceptance in an attempt to reduce the number of post-publication corrections and retractions, with the ultimate goal of increasing confidence in the published papers.
Ten Principles for Machine-Actionable Data Management Plans
Data management plans can have thematic, machine-actionable richness with added value for all stakeholders: researchers, funders, repository managers, research administrators, data librarians, and others.