Big Qual - Why We Should Be Thinking Big About Qualitative Data for Research, Teaching and Policy
When social scientists think about big data, they often think in terms of quantitative number crunching. However, the growing availability of ‘big’ qualitative datasets presents new opportunities for qualitative research.
As open access Plan S draws closer editors start to re-evaluate the business case of academic publishing, and their role in it. A major investigation reveals that editors at academic journals can make up to five figure salaries.
Nature Human Behaviour and the Behavioural and Social Sciences Community invite researchers across all career stages and disciplines to share their thoughts on publishing while training for a PhD. A broad selection of submissions will be published as World Views in Nature Human Behaviour or will be posted on the Behavioural and Social Sciences community page. Send us a short presubmission enquiry now!
Module 1 of the Open Science MOOC: Open Principles
This is Module 1 of the Open Science MOOC. This course is totally SELF-PACED, meaning it can be completed whenever you want and in your own time. Rationale: To innovate in a field frequently implies moving against prevailing trends and cultural inertia. Open Science is no different. No matter how convinced you are, you will come across resistance from peers and colleagues, and the best defence is strong personal conviction that what you are doing may not be perfect now, but is the right decision in the long run. This module will introduce the guiding principles of the 'open movement', the different actors involved, and the impact that they are having. Learning outcomes You will be able to describe the ethical, legal, social, economic, and research impact arguments for and against Open Science. After deciding which platforms/tools/services are most useful for themselves and their community, you will develop a personal profile for showcasing your research profile and outputs. After reflecting on the status of Open Science within your research group or lab, you will devise concrete ways to locally improve open practices. Using the guidelines published by their research laboratories, departments, or institutes, you will identify the policies for career progression and assessment, publishing and open access, data sharing, and intellectual property. Resources: Open Principles There are two tasks that are optional as part of this module: Defining how Open Science affects you. Developing your digital researcher profile. These tasks are OPTIONAL. You do NOT need to complete them in order to finish this module. They are, however, strongly recommended still. To complete this module, the only thing you need to do is complete the quiz! Once you have done that, you get this cool certificate to proudly display (the real one is bigger and nicer). Citation: We strongly encourage maximal sharing, re-use, and remixing of all content available for this module. It is also openly-licensed (CC0 or CC-BY at source) and copyright free as such. To cite this work, please use: Jon Tennant; Bruce Caron; Jo Havemann; Samuel Guay; Julien Colomb; Eva Lantsoght; Erzsébet Tóth-Czifra; Katharina Kriegel; Justin Sègbédji Ahinon; Cooper Smout & Gareth O'Neill. (2019, March 16). OpenScienceMOOC/Module-1-Open-Principles 2.0.0 (Version 2.0.0). Zenodo. http://doi.org/10.5281/zenodo.2595951 Other live modules: Module 5: Open Research Software and Open Source
Introducing Five Essential Factors, our latest white paper. Over the past two years, we've heard from more than 11,000 researchers about their views on data sharing, what they do in practice and the challenges they face. Building on that understanding, today we have released a whitepaper which proposes five key factors to make data management and sharing "business as usual" for all researchers.
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.
An HIV Treatment Cost Taxpayers Millions. The Government Patented It. But a Pharma Giant Is Making Billions.
The extraordinary standoff between the CDC and a drug company over patent rights raises a big question for the Trump administration: How aggressively should the government attempt to enforce its patents against an industry partner?
Implementing Publisher Policies that Inform, Support and Encourage Authors to Share Data
Open research data is one of the key areas in the expanding open scholarship movement. Scholarly journals and publishers find themselves at the heart of the shift towards openness. In this article we present two case studies which examine the experiences of Taylor & Francis and Springer Nature rolling out data-sharing policies.