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
Cleaning Biodiversity Data in R
This book is a practical guide for cleaning geo-referenced biodiversity data using R. It focuses specifically on the processes and challenges you’ll face with biodiversity data. As such, this book isn’t a general guide to data cleaning but a targeted resource for those working with or interested...
Keywords: R, Data cleaning, Biodiversity data, Rstats, Ecology, Reproducibility, Beginner R coding, data wrangling, Coding
Cleaning Biodiversity Data in R
https://cleaning-data-r.ala.org.au/
https://dresa.org.au/materials/cleaning-biodiversity-data-in-r
This book is a practical guide for cleaning geo-referenced biodiversity data using R. It focuses specifically on the processes and challenges you’ll face with biodiversity data. As such, this book isn’t a general guide to data cleaning but a targeted resource for those working with or interested in ecology, evolution, and geo-referenced biodiversity data.
Atlas of Living Australia support@ala.org.au
Atlas of Living Australia
R, Data cleaning, Biodiversity data, Rstats, Ecology, Reproducibility, Beginner R coding, data wrangling, Coding
ALA Labs
ALA Labs provides resources and articles from the Atlas of Living Australia's Science and Decision Support team. On the website, you can find:
- Posts: Code, articles, analyses and visualisations that will hopefully help you in your own work
- Research: Highlighted summaries of scientific...
Keywords: Ecology, R, Python, Rstats, Biodiversity data, Open science, Reproducibility, Coding, Data cleaning, Data visualisation, Species Distribution Modelling, Beginner R coding
ALA Labs
https://labs.ala.org.au/
https://dresa.org.au/materials/ala-labs
ALA Labs provides resources and articles from the Atlas of Living Australia's Science and Decision Support team. On the website, you can find:
- Posts: Code, articles, analyses and visualisations that will hopefully help you in your own work
- Research: Highlighted summaries of scientific research that has used data from the Atlas of Living Australia
- Software: R & Python packages that the Science & Decision Support team manage
- Books: Long-form resources with best-practice data wrangling and visualisation
- Gallery: Showcasing external work that uses tools from ALA Labs
Atlas of Living Australia support@ala.org.au
Ecology, R, Python, Rstats, Biodiversity data, Open science, Reproducibility, Coding, Data cleaning, Data visualisation, Species Distribution Modelling, Beginner R coding
Wildlife Insights training videos
A series of videos that provide tutorials on use of the Wildlife Insights camera trap data platform, and how to manage camera trap data in the platform
Keywords: wildlife, Camera traps, Monitoring, monitoring data management, Ecology
Wildlife Insights training videos
https://www.youtube.com/channel/UC4VjisiJLOowtbcY6P4-GNQ
https://dresa.org.au/materials/wildlife-insights-training-videos
A series of videos that provide tutorials on use of the Wildlife Insights camera trap data platform, and how to manage camera trap data in the platform
https://groups.google.com/u/0/g/wildlifeinsights?pli=1
wildlife, Camera traps, Monitoring, monitoring data management, Ecology
EcoCommons written support material, species distribution models explained and platform guides
These written descriptions on how to use the EcoCommons platform, the descriptions of the variety of species distribution models (SDM) available and the how to design and run and SDM have proven very popular with students whose instructors are using EcoCommons to teach basic SDM. They also...
Keywords: Species Distribution Modelling, Ecology, EcoCommons
EcoCommons written support material, species distribution models explained and platform guides
https://support.ecocommons.org.au/support/home
https://dresa.org.au/materials/ecocommons-written-support-material-species-distribution-models-explained-and-platform-guides
These written descriptions on how to use the EcoCommons platform, the descriptions of the variety of species distribution models (SDM) available and the how to design and run and SDM have proven very popular with students whose instructors are using EcoCommons to teach basic SDM. They also provide useful references for anyone using the platform.
https://www.ecocommons.org.au/contact/
Species Distribution Modelling, Ecology, EcoCommons
ugrad
masters
mbr
phd
EcoCommons use case estimating % of suitable habitat impacted by bushfires & utility of HCAS
We compare a variety of ways of estimating the percentage of suitable habitat impacted by the massive bushfires in eastern Australia (2019-2020), by comparing different SDM modelling algorithms, and inclusion of the Habitat Condition Assessment System (HCAS) derived variable.
Models were run...
Keywords: Species Distribution Modelling, HCAS, Fire, Ecology, EcoCommons
EcoCommons use case estimating % of suitable habitat impacted by bushfires & utility of HCAS
https://www.ecocommons.org.au/how-australian-mega-fires-impacted-the-superb-lyrebird-and-greater-sooty-owl/
https://dresa.org.au/materials/ecocommons-use-case-estimating-of-suitable-habitat-impacted-by-bushfires-utility-of-hcas
We compare a variety of ways of estimating the percentage of suitable habitat impacted by the massive bushfires in eastern Australia (2019-2020), by comparing different SDM modelling algorithms, and inclusion of the Habitat Condition Assessment System (HCAS) derived variable.
Models were run using the EcoCommons point-and-click SDM tools, and overlayed with a burnt area map https://researchdata.edu.au/google-earth-engine-map-geebam/1441550 to estimate % of suitable habitat that was impacted. HCAS data available: https://doi.org/10.25919/5j5j-4p06
https://www.ecocommons.org.au/contact/
Species Distribution Modelling, HCAS, Fire, Ecology, EcoCommons
EcoCommons & Open EcoAcoustics SDM use case
- Examples of code and the associated text summaries describe how open ecoacoustics https://openecoacoustics.org/ data can generate better SDM predictions. By using long-term monitoring data from https://acousticobservatory.org/ which allows analysts to infer absence locations, which does a much...
Keywords: Species Distribution Modelling, Ecoacoustics, Ecology, Owls, Mapping uncertainty
EcoCommons & Open EcoAcoustics SDM use case
https://www.ecocommons.org.au/acoustic-sdm-use-case/
https://dresa.org.au/materials/ecocommons-open-ecoacoustics-sdm-use-case
1. Examples of code and the associated text summaries describe how open ecoacoustics https://openecoacoustics.org/ data can generate better SDM predictions. By using long-term monitoring data from https://acousticobservatory.org/ which allows analysts to infer absence locations, which does a much better job at predicting distributions than presence only methods, and which facilitate use of call frequency as a response variable rather than presence absence.
The code and data used to generate these examples:
https://github.com/andrew-1234/sdm-usecase-master
2. Shows one way to overlay areas with the least geographically and environmentally representative sampling in addition to the predicted probability of occurrence generated by an SDM. This shows how to spatially represent areas where additional acoustic sampling would increase representative sampling most.
The code used in this example:
https://github.com/EcoCommons-Australia/educational_material/tree/main/SDMs_in_R/Scripts/adding_uncertainty_to_the_map
https://www.ecocommons.org.au/contact/
Species Distribution Modelling, Ecoacoustics, Ecology, Owls, Mapping uncertainty
ugrad
masters
mbr
phd
EcoCommons Marine use case
This is a toy example with many of the steps required for a robust example not included. This does show how to pull together marine data from IMOS / AODN and summarise those environmental predictors and occurrence data by month. Then we show how you can pull together one model with predictors...
Keywords: Species Distribution Modelling, SDM temporal predictions, Ecology, Marine seasonal distributions, R statistical software
EcoCommons Marine use case
https://www.ecocommons.org.au/marine-use-case/
https://dresa.org.au/materials/ecocommons-marine-use-case
This is a toy example with many of the steps required for a robust example not included. This does show how to pull together marine data from IMOS / AODN and summarise those environmental predictors and occurrence data by month. Then we show how you can pull together one model with predictors that are both temporally (monthly) and spatially (Australian waters) explicit.
Again, a robust example would need calibration and validation steps, but this example does show how SDMs can be developed across time.
The data and code needed to run these examples is here:
https://github.com/EcoCommons-Australia/educational_material/tree/main/Marine_use_case
https://www.ecocommons.org.au/contact/
Species Distribution Modelling, SDM temporal predictions, Ecology, Marine seasonal distributions, R statistical software
ugrad
masters
mbr
phd
ecr
Species Distribution Modelling in R
This set of scripts and videos provide an introduction to running SDMs in R and include some steps to consider that go beyond what's available in the EcoCommons SDM point-and-click tools.
Five videos include: 1. An introduction to SDM in R, 2. occurrence data, 3. environmental data, 4. fitting...
Keywords: Species Distribution Modelling, Ecology, R software, EcoCommons
Species Distribution Modelling in R
https://www.ecocommons.org.au/educational-material4-mastering-species-distribution-modelling-in-r/
https://dresa.org.au/materials/species-distribution-modelling-in-r
This set of scripts and videos provide an introduction to running SDMs in R and include some steps to consider that go beyond what's available in the EcoCommons SDM point-and-click tools.
Five videos include: 1. An introduction to SDM in R, 2. occurrence data, 3. environmental data, 4. fitting your model, 5. model evaluation
Scripts and files are available here:
https://github.com/EcoCommons-Australia/educational_material/tree/main/SDMs_in_R/Scripts
Scripts for all four modules are here: https://www.ecocommons.org.au/wp-content/uploads/EcoCommons_steps_1_to_4.html
https://www.ecocommons.org.au/contact/
https://orcid.org/0000-0002-1359-5133
Species Distribution Modelling, Ecology, R software, EcoCommons
ugrad
mbr
phd
Discovering Species Distribution Modelling with BCCVL
A set of 10 videos that provide an excellent introduction to species distribution modelling. These modules include: 1. Introduction to SDM, 2. Ecological theory of SDM, 3. Data for SDMs, 4. Design an SDM, 5. Presence only models, 6. Statistical models, 7. Machine learning models, 8. Model...
Keywords: Species Distribution Modelling, Ecology, EcoCommons, Beginer ecological modelling, Climate projections
Discovering Species Distribution Modelling with BCCVL
https://www.ecocommons.org.au/educational-material2-discovering-species-distribution-with-bccvl/
https://dresa.org.au/materials/discovering-species-distribution-modelling-with-bccvl
A set of 10 videos that provide an excellent introduction to species distribution modelling. These modules include: 1. Introduction to SDM, 2. Ecological theory of SDM, 3. Data for SDMs, 4. Design an SDM, 5. Presence only models, 6. Statistical models, 7. Machine learning models, 8. Model evaluation, 9. SDMs and climate change projections, 10. Case studies in BCCVL
https://www.ecocommons.org.au/contact/
BCCVL
Species Distribution Modelling, Ecology, EcoCommons, Beginer ecological modelling, Climate projections
ugrad
mbr
EcoCommons Modelling Made Easy
These ten videos walk users through some of the point-and-click functionality available on the EcoCommons platform including: 1. Navigating the EcoCommons platform, 2. Exploring environmental and climate grids available on the platform, 3. Importing your own data, 4. How to run a Species...
Keywords: Species Distribution Modelling, Climate projections , EcoCommons, Ecology
Resource type: video
EcoCommons Modelling Made Easy
https://www.ecocommons.org.au/educational-material-1-ecocommons-modelling-made-easy/
https://dresa.org.au/materials/ecocommons-modelling-made-easy
These ten videos walk users through some of the point-and-click functionality available on the EcoCommons platform including: 1. Navigating the EcoCommons platform, 2. Exploring environmental and climate grids available on the platform, 3. Importing your own data, 4. How to run a Species Distribution Model (SDM), 5. Predicting how distributions will change under climate change, 6. Running simple (averaged) ensemble models of SDMs, 7. An introduction to toy species trait problems that highlight how variation in species traits can be predicted spatially, 8. An introduction to Biosecurity Risk Mapping, 9. How to run SDMs for multiple species, 10. A multiple species SDM use case
support@ecocommons.org.au
Species Distribution Modelling, Climate projections , EcoCommons, Ecology
ugrad
mbr
phd
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
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