Has there been meaningful movement toward open science practices within the social sciences in recent years? Discussions about changes in practices such as posting data and pre-registering analyses have been marked by controversy—including controversy over the extent to which change has taken place. This study, based on the State of Social Science (3S) Survey, provides the first comprehensive assessment of awareness of, attitudes towards, perceived norms regarding, and adoption of open science practices within a broadly representative sample of scholars from four major social science disciplines: economics, political science, psychology, and sociology. We observe a steep increase in adoption: as of 2017, over 80% of scholars had used at least one such practice, rising from one quarter a decade earlier. Attitudes toward research transparency are on average similar between older and younger scholars, but the paceof change differs by field and methodology. According with theories of normal science and scientific change, the timing of increases in adoption coincides with technological innovations and institutional policies. Patterns are consistent with most scholars underestimating the trend toward open science in their discipline.

“Open Science” has become a buzzword in academic circles. However, exactly what it means, why you should care about it, and – most importantly – how it can be put into practice is often not very clear to researchers. In this session of the SSDL, we will provide a brief tour d'horizon of Open Science in which we touch on all of these issues and by which we hope to equip you with a basic understanding of Open Science and a practical tool kit to help you make your research more open to other researchers and the larger interested public. Throughout the presentation, we will focus on giving you an overview of tools and services that can help you open up your research workflow and your publications, all the way from enhancing the reproducibility of your research and making it more collaborative to finding outlets which make the results of your work accessible to everyone. Absolutely no prior experience with open science is required to participate in this talk which should lead into an open conversation among us as a community about the best practices we can and should follow for a more open social science.

You can become a more visible, effective and impactful researcher by sharing your research data and publications openly. In this course, you will learn the objectives, main concepts, and benefits of Open Science principles along with practices for open data management and open data sharing.

Since research increasingly relies on software which is used to model and simulate, and to deal with the ever growing volume of research data, the course will also introduce FAIR software practices.

You'll learn to establish links between publications, data, software and methods, how to attach a persistent identifier and metadata to your results, and methods for clarifying usage rights. You will also discover ways to apply these principles to your daily research and adapt existing routines. Finally, you'll uncover potential barriers to sharing research and discuss possible solutions.

This course will help you grasp the key principles of Open Science, with answers to questions like:

How can researchers effectively store, manage, and share research data?
What kinds of open access publishing are most effective?
How can researchers increase the visibility and impact of their research?
How can the use of social media contribute to the visibility and impact of research?
How can researchers be acknowledged for the research software they write?
You will apply the topics of the course to a variety of case studies on Open Science adoption, which you will then discuss among fellow students. You will also be presented with a hands-on guide to publishing your research with open access. This will help you to apply Open Science principles in your daily work. It will enable you to implement and benefit from the Open Science policies that are currently being developed by governments and research institutions.

This course is aimed at professionals. Those who will see the most benefit include academic researchers at different levels: PhD students, postdoctoral researchers, and professors; researchers working for governments; researchers working for commercial enterprises; MSc and BSc students interested to learn about the principles of Open Science.

The development of this course is supported by the VRE4EIC project with funding from the European Union's Horizon 2020 Research and Innovation Programme.

There is a vast body of helpful tools that can be used in order to foster Open Science practices. For reasons of clarity, this toolbox aims at providing only a selection of links to these resources and tools. Our goal is to give a short overview on possibilities of how to enhance your Open Science practices without consuming too much of your time.

Open Science, the movement to make scientific products and processes accessible to and reusable by all, is about culture and knowledge as much as it is about technologies and services. Convincing researchers of the benefits of changing their practices, and equipping them with the skills and knowledge needed to do so, is hence an important task.This book offers guidance and resources for Open Science instructors and trainers, as well as anyone interested in improving levels of transparency and participation in research practices. Supporting and connecting an emerging Open Science community that wishes to pass on its knowledge, the handbook suggests training activities that can be adapted to various settings and target audiences. The book equips trainers with methods, instructions, exemplary training outlines and inspiration for their own Open Science trainings. It provides Open Science advocates across the globe with practical know-how to deliver Open Science principles to researchers and support staff. What works, what doesn’t? How can you make the most of limited resources? Here you will find a wealth of resources to help you build your own training events.

Open Science is a collection of actions designed to make scientific processes more transparent and results more accessible. Its goal is to build a more replicable and robust science; it does so using new technologies, altering incentives, and changing attitudes. The current movement towards open science was spurred, in part, by a recent “series of unfortunate events” within psychology and other sciences. These events include the large number of studies that have failed to replicate and the prevalence of common research and publication procedures that could explain why. Many journals and funding agencies now encourage, require, or reward some open science practices, including pre-registration, providing full materials, posting data, distinguishing between exploratory and confirmatory analyses, and running replication studies. Individuals can practice and encourage open science in their many roles as researchers, authors, reviewers, editors, teachers, and members of hiring, tenure, promotion, and awards committees. A plethora of resources are available to help scientists, and science, achieve these goals.

Note: This webinar was presented in Spanish. The slides presented during this webinar can be found here:https://osf.io/6qnse/ The slides presented during this seminar can be found here: https://osf.io/6qnse/ Este seminario web se centrará en el estado de la ciencia abierta en América Latina, desde los esfuerzos de los investigadores individuales para abrir sus flujos de trabajo, herramientas para ayudar a los investigadores a ser abiertos y nuevas redes e iniciativas prometedoras en ciencia abierta. Ricardo Hartley (@ametodico) es profesor de metodología de la investigación de la Universidad Central de Chile, investigador en biología de la reproducción y en comunicación - valoración del conocimiento. Organizador de las OpenCon Santiago 2016 y 2017 y embajador COS. Erin McKiernan es profesora del Departamento de Física, Programa de Física Biomédica de la Universidad Nacional Autónoma de México. También es la fundadora del Why Open Research? proyecto, un sitio educativo para que los investigadores aprendan cómo compartir su trabajo, financiado en parte por la Fundación Shuttleworth. Fernan Federici Noe es profesor asistente e investigador de la Universidad Católica de Chile y fellow internacional del OpenPlant Synthetic Biology Center, University of Cambridge. Fernan es miembro del Global For Open Science Hardware (GOSH) y TECNOx (www.tecnox.org).

This lesson series is for the Openscapes Champions program, an open data science mentorship program for science teams.

Openscapes Champions is a professional development and leadership opportunity for teams to reimagine data analysis & stewardship as a collaborative effort, develop modern skills that are of immediate value to them, and cultivate collaborative and inclusive research communities. Cohorts are ~7 research teams (~35 total participants including team leads and members) that convene remotely to explore open data science tooling and practices together. This is a remote-by-design program since its launch in 2019.

The Series is written (and always improving) to be used as a reference, to teach, or as self-paced learning.

Openscapes is co-directed by Julia Stewart Lowndes and Erin Robinson. It is operated by the National Center for Ecological Analysis & Synthesis (NCEAS) and was incubated by a Mozilla Fellowship awarded to Lowndes in 2018.

The movement towards open science is a consequence of seemingly pervasive failures to replicate previous research. This transition comes with great benefits but also significant challenges that are likely to affect those who carry out the research, usually early career researchers (ECRs). Here, we describe key benefits, including reputational gains, increased chances of publication, and a broader increase in the reliability of research. The increased chances of publication are supported by exploratory analyses indicating null findings are substantially more likely to be published via open registered reports in comparison to more conventional methods. These benefits are balanced by challenges that we have encountered and that involve increased costs in terms of flexibility, time, and issues with the current incentive structure, all of which seem to affect ECRs acutely. Although there are major obstacles to the early adoption of open science, overall open science practices should benefit both the ECR and improve the quality of research. We review 3 benefits and 3 challenges and provide suggestions from the perspective of ECRs for moving towards open science practices, which we believe scientists and institutions at all levels would do well to consider.

Opensciency is core open science curriculum material, drafted to introduce those beginning their open science journey to important definitions, tools, and resources; and provide for participants at all levels recommended practices. The material is made available under a CC-BY 4.0 International license and is structured into five modules:

- Ethos of Open Science
- Open Tools and Resources
- Open Data
- Open Software
- Open Results

In this webinar, we demonstrate the OSF tools available for contributors, labs, centers, and institutions that support stronger collaborations. The demo includes useful practices like: contributor management, the OSF wiki as an electronic lab notebook, using OSF to manage online courses and syllabi, and more. Finally, we look at how OSF Institutions can provide discovery and intelligence gathering infrastructure so that you can focus on conducting and supporting exceptional research. The Center for Open Science’s ongoing mission is to provide community and technical resources to support your commitments to rigorous, transparent research practices. Visit cos.io/institutions to learn more.

The research publications on Our World in Data are dedicated to a large range of global problems in health, education, violence, political power, human rights, war, poverty, inequality, energy, hunger, and humanity’s impact on the environment. On the homepage we list all the global problems and important long-term changes that we have researched.

Thanks to the work of thousands of researchers around the world who dedicate their lives to it, we often have a good understanding of how it is possible to make progress against the large problems we are facing. The world has the resources to do much better and reduce the suffering in the world.

We believe that a key reason why we fail to achieve the progress we are capable of is that we do not make enough use of this existing research and data: the important knowledge is often stored in inaccessible databases, locked away behind paywalls and buried under jargon in academic papers.

The goal of our work is to make the knowledge on the big problems accessible and understandable. As we say on our homepage, Our World in Data’s mission is to publish the “research and data to make progress against the world’s largest problems”.

Licenses: All visualizations, data, and articles produced by Our World in Data are open access under the Creative Commons BY license. You have permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited. All the software and code that we write is open source and made available via GitHub under the permissive MIT license. All other material, including data produced by third parties and made available by Our World in Data, is subject to the license terms from the original third-party authors.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Uncovering the links between microbiome profiles and host conditions is critical to understanding the roles microbes play in human health. However, analysis of microbiome profiles with traditional testing frameworks is made difficult by the high-dimensionality and sparsity of the data. Often this is addressed by incorporating information from closely related microbes. This phylogenetic information is added under the assumption that operational taxonomic units (OTUs) from related taxa will tend to behave similarly, but the complexity of microbe interactions can make this assumption invalid. The recently developed tool, Phylogeny-guided microbiome OTU-Specific association Test (POST), addresses this issue. POST determines how much, if any, information to borrow from neighboring OTUs based on phylogenetic distance and outcome-OTU association. This tool is a local collapsing test built under the kernel machine framework to accommodate complex OTU effects..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Vision is the primary sense of many animals and much is known about how vision is processed in the mammalian nervous system. One distinct property of the primary visual cortex is a highly organized pattern of sensitivity to location and orientation of objects in the visual field. But how did we learn this? An important tool is the ability to design experiments to map out the structure and response of a system such as vision. In this activity, students learn about the visual system and then conduct a model experiment to map the visual field response of a Panoptes robot. (In Greek mythology, Argus Panoptes was the "all-seeing" watchman giant with 100 eyes.) A simple activity modification enables a true black box experiment, in which students do not directly observe how the visual system is configured, and must match the input to the output in order to reconstruct the unseen system inside the box.

Training Modules developed for Ocean Sciences Meeting 2020 and recorded for sharing at European Geosciences Union 2020 General Assembly.

Over the past ten years, researchers, institutional leaders and policymakers have begun to speak more and more about infrastructure. As more voices join the conversation, however, it can sometimes become more difficult, rather than less, to understand what exactly research infrastructure is and does. In particular in the humanities, and the digital humanities, the term is used to cover a lot of different projects, resources and approaches.

To address this gap, the PARTHENOS cluster of humanities research infrastructure projects has devised this series of training modules and resources for researchers, educators, managers, and policy makers who want to learn more about research infrastructures and the issues and methods around them.

The modules, which released on a rolling basis from late 2016, cover a wide range of awareness levels, requirements and topic areas within the landscape of research infrastructure. Parthenos provides training modules for independent learners and for instructors looking to incorporate this material into existing courses.

In this lesson, students will compare weather and climate, explain patterns over time and make observations by creating a rain gauge.

NGSS: 3-ESS2-1

Time: 55 minutes

Materials: laminated patterns in nature photos (photos included), thermometer for the class, duct tape, data sheet, rulers, sharpies, scissors, empty soda bottles for rain gauages, pebbles

Journals are exploring new approaches to peer review in order to reduce bias, increase transparency and respond to author preferences. Funders are also getting involved. If you start reading about the subject of peer review, it won't be long before you encounter articles with titles like Can we trust peer review?, Is peer review just a crapshoot? and It's time to overhaul the secretive peer review process. Read some more and you will learn that despite its many shortcomings – it is slow, it is biased, and it lets flawed papers get published while rejecting work that goes on to win Nobel Prizes – the practice of having your work reviewed by your peers before it is published is still regarded as the 'gold standard' of scientific research. Carry on reading and you will discover that peer review as currently practiced is a relatively new phenomenon and that, ironically, there have been remarkably few peer-reviewed studies of peer review.

This activity fits in a unit with the purpose, “Students will interpret visual information in order to make informed consumer decisions.” It is designed to get them thinking deeply about how we represent data visually, introducing the ideas of a coordinate plane (quadrant 1 only) in a very informal way – without numbers.