7 Steps towards Reproducible Research
This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.
We will also examine how Reproducible Research builds business continuity...
Keywords: reproducibility, Reproducibility, reproducible workflows
Resource type: full-course, tutorial
7 Steps towards Reproducible Research
https://amandamiotto.github.io/ReproducibleResearch/
https://dresa.org.au/materials/7-steps-towards-reproducible-research
This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.
We will also examine how Reproducible Research builds business continuity into your research group, how the culture in your institute ecosystem can affect Reproducibility and how you can identify and address risks to your knowledge.
The workshop can be used as self-paced or as an instructor
Amanda Miotto - a.miotto@griffith.edu.au
Amanda Miotto
reproducibility, Reproducibility, reproducible workflows
phd
support
ARDC FAIR Data 101 self-guided
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the...
Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
ARDC FAIR Data 101 self-guided
https://zenodo.org/records/5094034
https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub.
contact@ardc.edu.au
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Martinez, Paula A. (orcid: 0000-0002-8990-1985)
Simons, Natasha (orcid: 0000-0003-0635-1998)
Russell, Keith (orcid: 0000-0001-5390-2719)
McCafferty, Siobhann (orcid: 0000-0002-2491-0995)
Ferrers, Richard (orcid: 0000-0002-2923-9889)
McEachern, Steve (orcid: 0000-0001-7848-4912)
Barlow, Melanie (orcid: 0000-0002-3956-5784)
Brady, Catherine (orcid: 0000-0002-7919-7592)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Quiroga, Maria del Mar (orcid: 0000-0002-8943-2808)
training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
Create a website resume
Written for the Qld Research Bazaar conference 2021, this self paced lesson breaks down how to use Github pages to make a resume, with a simple and basic template to start off with. It discusses how to use Markdown and minimum HTML to customize the template, and offers explanations on how the...
Keywords: personal development, website
Resource type: tutorial, guide
Create a website resume
https://amandamiotto.github.io/ResumeLesson/HowIMadeThis
https://dresa.org.au/materials/create-a-website-resume
Written for the Qld Research Bazaar conference 2021, this self paced lesson breaks down how to use Github pages to make a resume, with a simple and basic template to start off with. It discusses how to use Markdown and minimum HTML to customize the template, and offers explanations on how the components work together.
a.miotto@griffith.edu.au
Amanda Miotto
personal development, website
10 Reproducible Research things - Building Business Continuity
The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are...
Keywords: reproducibility, data management
Resource type: tutorial, video
10 Reproducible Research things - Building Business Continuity
https://guereslib.github.io/ten-reproducible-research-things/
https://dresa.org.au/materials/9-reproducible-research-things-building-business-continuity
The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are replicable due to lack of information on the process. Therefore, reproducibility in research is extremely important.
Researchers genuinely want to make their research more reproducible, but sometimes don’t know where to start and often don’t have the available time to investigate or establish methods on how reproducible research can speed up every day work. We aim for the philosophy “Be better than you were yesterday”. Reproducibility is a process, and we highlight there is no expectation to go from beginner to expert in a single workshop. Instead, we offer some steps you can take towards the reproducibility path following our Steps to Reproducible Research self paced program.
Video:
https://www.youtube.com/watch?v=bANTr9RvnGg
Tutorial:
https://guereslib.github.io/ten-reproducible-research-things/
a.miotto@griffith.edu.au; s.stapleton@griffith.edu.au; i.jennings@griffith.edu.au;
Amanda Miotto
Julie Toohey
Sharron Stapleton
Isaac Jennings
reproducibility, data management
masters
phd
ecr
researcher
support
Data Storytelling
Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert...
Keywords: data storytelling, data visualisation
Data Storytelling
https://griffithunilibrary.github.io/data-storytelling/
https://dresa.org.au/materials/data-storytelling
Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert your insights and discovery from data into stories to share with non-experts with a language they understand. But how?
This tutorial helps you construct stories that incite an emotional response and create meaning and understanding for the audience by applying data storytelling techniques.
m.yamaguchi@griffith.edu.au
a.miotto@griffith.edu.au
Masami Yamaguchi
Amanda Miotto
Brett Parker
data storytelling, data visualisation
support
masters
phd
researcher