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
How can software containers help your research?
This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility.
Software Containers in research are a solution that addresses the challenge of a...
Keywords: containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material
How can software containers help your research?
https://zenodo.org/records/5091260
https://dresa.org.au/materials/how-can-software-containers-help-your-research-ca0f9d41-d83b-463b-a548-402c6c642fbf
This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility.
Software Containers in research are a solution that addresses the challenge of a replicable computational environment and supports reproducibility of research results. Understanding the concept of software containers enables researchers to better communicate their research needs with their colleagues and other researchers using and developing containers.
Watch the video here: https://www.youtube.com/watch?v=HelrQnm3v4g
If you want to share this video please use this:
Australian Research Data Commons, 2021. How can software containers help your research?. [video] Available at: https://www.youtube.com/watch?v=HelrQnm3v4g DOI: http://doi.org/10.5281/zenodo.5091260 [Accessed dd Month YYYY].
contact@ardc.edu.au
Australian Research Data Commons
Martinez, Paula Andrea (type: ProjectLeader)
Sam Muirhead (type: Producer)
The ARDC Communications Team (type: Editor)
The ARDC Skills and Workforce Development Team (type: ProjectMember)
The ARDC eResearch Infrastructure & Services (type: ProjectMember)
The ARDC Nectar Cloud Services team (type: ProjectMember)
containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material
CheckEM User Guide
CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for...
Keywords: stereo-video, fish, annotation
CheckEM User Guide
https://globalarchivemanual.github.io/CheckEM/articles/manuals/CheckEM_user_guide.html
https://dresa.org.au/materials/checkem-user-guide
CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for common inaccuracies made whilst annotating stereo imagery. CheckEM creates interactive plots and tables in a graphical interface, and provides summarised data and a report of potential errors to download.
brooke.gibbons@uwa.edu.au
Brooke Gibbons
stereo-video, fish, annotation
EventMeasure Annotation Guide
EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length
Keywords: fish, stereo-video, annotation
EventMeasure Annotation Guide
https://globalarchivemanual.github.io/CheckEM/articles/manuals/EventMeasure_annotation_guide.html
https://dresa.org.au/materials/eventmeasure-annotation-guide
EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length
tim.langlois@uwa.edu.au
Brooke Gibbons
Tim Langlois
Claude Spencer
fish, stereo-video, annotation
Stereo-video workflows for fish and benthic ecologists
Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range...
Keywords: stereo-video, fish, sharks, habitats
Resource type: tutorial
Stereo-video workflows for fish and benthic ecologists
https://globalarchivemanual.github.io/CheckEM/index.html
https://dresa.org.au/materials/stereo-video-workflows-for-fish-and-benthic-ecologists
Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way.
tim.langlois@uwa.edu.au
Tim Langlois
Brooke Gibbons
Claude Spencer
stereo-video, fish, sharks, habitats
Beyond Basics: Conditionals and Visualisation in Excel
After cleaning your dataset, you may need to apply some conditional analysis to glean greater insights from your data. You may also want to enhance your charts for inclusion into a manuscript, thesis or report by adding some statistical elements. This course will cover conditional syntax, nested...
Beyond Basics: Conditionals and Visualisation in Excel
https://intersect.org.au/training/course/excel201
https://dresa.org.au/materials/beyond-basics-conditionals-and-visualisation-in-excel
After cleaning your dataset, you may need to apply some conditional analysis to glean greater insights from your data. You may also want to enhance your charts for inclusion into a manuscript, thesis or report by adding some statistical elements. This course will cover conditional syntax, nested functions, statistical charting and outlier identification. Armed with the tips and tricks from our introductory Excel for Researchers course, you will be able to tap into even more of Excel’s diverse functionality and apply it to your research project.
- Cell syntax and conditional formatting
- IF functions
- Pivot Table summaries
- Nesting multiple AND/IF/OR calculations
- Combining nested calculations with conditional formatting to bring out important elements of the dataset
- MINIFS function
- Box plot creation and outlier identification
- Trendline and error bar chart enhancements
Familiarity with the content of Excel for Researchers, specifically:
- the general Office/Excel interface (menus, ribbons/toolbars, etc.)
- workbooks and worksheets
- absolute and relative references, e.g. $A$1, A1.
- simple ranges, e.g. A1:B5
training@intersect.org.au
Intersect Australia
Excel
Excel for Researchers
Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there’s too much of it. Frequently, it has errors. We’ll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise,...
Excel for Researchers
https://intersect.org.au/training/course/excel101
https://dresa.org.au/materials/excel-for-researchers
Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there’s too much of it. Frequently, it has errors. We’ll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.
While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data.
‘Clean up’ messy research data
Organise, format and name your data
Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING)
Perform calculations on your data using functions (MAX, MIN, AVERAGE)
Extract significant findings from your data (PIVOT TABLE, VLOOKUP)
Manipulate your data (convert data format, work with DATES and TIMES)
Create graphs and charts to visualise your data (CHARTS)
Handy tips to speed up your work
In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software.
training@intersect.org.au
Intersect Australia
Excel
Getting Started with Excel
We rarely receive the research data in an appropriate form. Often data is messy. Sometimes it is incomplete. And sometimes there’s too much of it. Frequently, it has errors.
This webinar targets beginners and presents a quick demonstration of using the most widespread data wrangling tool,...
Getting Started with Excel
https://intersect.org.au/training/course/excel001
https://dresa.org.au/materials/getting-started-with-excel
We rarely receive the research data in an appropriate form. Often data is messy. Sometimes it is incomplete. And sometimes there’s too much of it. Frequently, it has errors.
This webinar targets beginners and presents a quick demonstration of using the most widespread data wrangling tool, Microsoft Excel, to sort, filter, copy, protect, transform, aggregate, summarise, and visualise research data.
Introduction to Microsoft Excel user interface
Interpret data using sorting, filtering, and conditional formatting
Summarise data using functions
Analyse data using pivot tables
Manipulate and visualise data
Handy tips to speed up your work
The webinar has no prerequisites.
training@intersect.org.au
Intersect Australia
Excel
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