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
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
Introduction to text mining and analysis
In this self-paced workshop you will learn steps to:
- Build data sets: find where and how to gather textual data for your corpus or data set.
- Prepare data for analysis: explore useful processes and tools to prepare and clean textual data for analysis
- Analyse data: identify different...
Keywords: textual training materials
Resource type: tutorial
Introduction to text mining and analysis
https://griffithunilibrary.github.io/intro-text-mining-analysis/
https://dresa.org.au/materials/introduction-to-text-mining-and-analysis
In this self-paced workshop you will learn steps to:
- Build data sets: find where and how to gather textual data for your corpus or data set.
- Prepare data for analysis: explore useful processes and tools to prepare and clean textual data for analysis
- Analyse data: identify different types of analysis used to interrogate content and uncover new insights
s.stapleton@griffith.edu.au; y.banens@griffith.edu.au;
Yuri Banens
Sharron Stapleton
Ben McRae
textual training materials
mbr
phd
ecr
researcher
support
VOSON Lab Code Blog
The VOSON Lab Code Blog is a space to share methods, tips, examples and code. Blog posts provide techniques to construct and analyse networks from various API and other online data sources, using the VOSON open-source software and other R based packages.
Keywords: visualisation, Data analysis, data collections, R software, Social network analysis, social media data, Computational Social Science, quantitative, Text Analytics
Resource type: tutorial, other
VOSON Lab Code Blog
https://vosonlab.github.io/
https://dresa.org.au/materials/voson-lab-code-blog
The VOSON Lab Code Blog is a space to share methods, tips, examples and code. Blog posts provide techniques to construct and analyse networks from various API and other online data sources, using the VOSON open-source software and other R based packages.
robert.ackland@anu.edu.au
visualisation, Data analysis, data collections, R software, Social network analysis, social media data, Computational Social Science, quantitative, Text Analytics
researcher
support
phd
masters
Introduction to R
An introduction to R, for people with zero coding experience.
To be taught as a hands on workshop, typically as two half-days.
Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and...
Keywords: R
Resource type: tutorial
Introduction to R
https://monashdatafluency.github.io/r-intro-2/
https://dresa.org.au/materials/introduction-to-r
An introduction to R, for people with zero coding experience.
To be taught as a hands on workshop, typically as two half-days.
Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given.
Paul Harrison paul.harrison@monash.edu
Paul Harrison
R
phd
ecr
researcher
Getting Started with Deep Learning
This lecture provides a high level overview of how you could get started with developing deep learning applications. It introduces deep learning in a nutshell and then provides advice relating to the concepts and skill sets you would need to know and have in order to build a deep learning...
Keywords: Deep learning, Machine learning
Resource type: presentation
Getting Started with Deep Learning
https://doi.org/10.26180/15032688
https://dresa.org.au/materials/getting-started-with-deep-learning
This lecture provides a high level overview of how you could get started with developing deep learning applications. It introduces deep learning in a nutshell and then provides advice relating to the concepts and skill sets you would need to know and have in order to build a deep learning application. The lecture also provides pointers to various resources you could use to gain a stronger foothold in deep learning.
This lecture is targeted at researchers who may be complete beginners in machine learning, deep learning, or even with programming, but who would like to get into the space to build AI systems hands-on.
datascienceplatform@monash.edu
Titus Tang
Deep learning, Machine learning
