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Open Science Tweets

Introduction

What is Open Science?

"Open Science is the practice of science in such a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods. In a nutshell, Open Science is transparent and accessible knowledge that is shared and developed through collaborative networks" (Vicente-Sáez and Martínez-Fuentes, 2018, The Open Science Training Handbook.)

Open Science encompasses the following (Open Science of FOSTER):

Open Access
Open Data
Open Reproducible Research
Open Science Evaluation
Open Science Policies
Open Science Tools

Why Open Science?

Unlike traditional models of science that produce articles locked behind a journal paywall, Open Science (also known as Open Scholarship) is about opening up the tools, processes, and products of science to make research more reproducible and equitable.

The European Union has adopted Open Science as the official framework for research in higher education (EU Open Science Policy). It is believed that Open Science will lead to research that is:

More reliable: Responsible, reproducible research
More efficient: Collaborate, co-design, co-create
More accessible: Open access to publications; FAIR data
More relevant to society: Public engagement

How to engage in Open Science?

NTU fully endorses the principles of open access and expects faculty, staff and higher degree students by research to make their research publications and theses open access (Open Access Policy). In addition, the University requires final research data to be made available at the institutional data repository, DR-NTU (Data), and/or an external open access data repository (Research Data Policy).

Moreover, there are various other channels or tools with which the research community can engage in Open Science at various stages of the research lifecycle.

Kramer, Bianca, & Bosman, Jeroen. (2018, January). Rainbow of open science practices. Zenodo. http://doi.org/10.5281/zenodo.1147025

Video

Open Science: Michael Nielsen at TEDxWaterloo

Listen to Michael Nielsen, one of the pioneers of quantum computation, on his take on open science collaboration - why some flourished and others fizzled out, as well as his aspirations for the open science community.

Learning resources on Open Science

FOSTER Open Science Training Courses
These courses answer some of the most common questions you might have about putting open science into practice. A badge will be rewarded upon completion.
Open Science MOOC
This MOOC (Massive Open Online Course) is designed to help equip students and researchers with the skills they need to excel in a modern research environment.
Open Science Training Handbook
The Open Science Training Handbook is a CC0 resource written to support the practical teaching of open science principles.

Tools and platforms

Code collaboration and project management

Visual Studio Code
Visual Studio Code is an integrated development environment by Microsoft for Windows, Linux and macOS. Features include support for debugging, syntax highlighting, intelligent code completion, snippets, code refactoring, and embedded Git.
GitHub
GitHub is a great place for storing, distributing, collaborating, and version-controlling code.
Open Science Framework (OSF)
OSF enables collaborative research and writing, keeping files, data, and protocols in the cloud. Control which parts of your project are public or private, connect to other tools to share data, archive data, track project changes.

Collaborative writing and publishing

Tools for developing reproducible research documents with R
The current ecosystem of tools for developing reproducible research documents with R is small, but growing and changing. These tools are further combined to create dynamic workflows, allowing unprecedented organization of scientific work. See this website for a listing of such free tools.
Manubot
Manubot is a workflow and set of tools for the next generation of scholarly publishing. Write your manuscript in markdown, track it with git, automatically convert it to .html, .pdf, or .docx, and deploy it to your destination of choice.
NTU Library Guide on Digital Tools and Methods
Visit this LibGuide to learn about tools for data visualisation, GIS, online publishing and presentation offered by NTU Library.

Learning resources on reproducible research

Reproducible Reporting with RMarkdown
This workshop covers using R and dynamic document generation with RMarkdown and RStudio to weave together reporting text with executable R code to automatically generate reports in the form of PDF, Word, or HTML documents. (CC BY-NC-SA 4.0)
R for Reproducible Scientific Analysis
The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis.