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...

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...

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...

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...

These two videos walk through the "R for Ecologists" module offered by the Data Carpentries https://datacarpentry.org/R-ecology-lesson/

The first video: Manipulating Data covers:
Opening R, setting your working directory, reading and downloading csv files, selecting and filtering data, using...

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...

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...

Resources include:
* Facilitator notes
*PowerPoint presentation
This is an introduction to the Five Safes framework and has been developed for anyone with no or little knowledge of the framework can develop their own workshop.

The main objective of this project was to provide education on the use of data translated to the OMOP common data model. We aimed to showcase how the Atlas interface tool could be used to generate evidence for a highly relevant and significant research question. The clinical question that was...

This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases.

This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine.

Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data...

A hands-on workshop covering the basics of the Unix command line interface.

Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing...

In this train-the-trainer workshop, we will be exploring and discussing methods for active data management.

Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data,...

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.

A workshop to expand the skill-set of someone who has basic familiarity with R. Covers programming constructs such as functions and for-loops, and working with data frames using the dplyr and tidyr packages. Explains the importance of a "tidy" data representation, and goes through common steps...

A workshop on linear models in R. Learning to use linear models provides a foundation for modelling, estimation, prediction, and statistical testing in R. Many commonly used statistical tests can be performed using linear models. Ideas introduced using linear models are applicable to many of the...

This workshop will introduce you to Jupyter Notebooks, a digital tool that has exploded in popularity in recent years for those working with data.

You will learn what they are, what they do and why you might like to use them. It is an introductory set of lessons for those who are brand new,...

A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface.

This workshop is a ‘train-the-trainer’ session that covers topics such as jargon busting, network literacy and data movement solutions. The workshop will also provide a peek at some collaborative research tools such as Jupyter Notebooks and CloudStor. You will learn about networks, integrated...

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...

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...

A series of eight videos (each between 5 and 10 minutes long) following the content of the Software Carpentry workshop "The Unix Shell".

Sessions 1, 2 and 3 provide instructions on the minimal level of Linux/Unix commands recommended for new...

A short video outlining the basics on how to use FileZilla to establish a secure file transfer protocol (sftp) connection to HPC to use a drag and drop interface to transfer files between the HPC and a desktop computer.

A series of three short videos introducing how to use PuTTY to connect from a Windows PC to a secure HPC (high performance computing) cluster.

1 - The very basics on how to establish a connection to HPC.
2 - How to add more specific options for the connection to HPC.
3 - How to save the...

This video shows how you can use the web app version of the Trove Newspaper & Gazette Harvester to download large quantities of digitised newspaper articles from Trove. Just give it a search from the Trove web interface, and the harvester will...

This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify.
The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata,...

This workshop is designed to be instructor led and consists of two parts.
Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset.
Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for...

This workshop explores how data visualisation techniques could be utilised to better understand data and to communicate research efforts and outcomes. The workshop covers a broad range of techniques from simple and static 2D graphics to advanced 3D visualisations in order to provide a broad...

Modern deep neural networks require large amounts of labelled data to train. Obtaining the required labelled data is often an expensive and time consuming process. Semi-supervised deep learning involves the use of various creative techniques to train deep neural networks on partially labelled...