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Secondary use of clinical trials data in health research: A Practical Guide

This document presents a theoretical framework for the use of clinical trials and other health data for secondary research purposes, which was derived from research papers, consultation with stakeholders and the research community.  Four overall scenarios for data reuse were identified; scenario...

Keywords: Secondary Data Use, Clinical Trials, Training Material, HeSANDA, Health Data Australia, HDA

Secondary use of clinical trials data in health research: A Practical Guide https://dresa.org.au/materials/secondary-use-of-clinical-trials-data-in-health-research-a-practical-guide This document presents a theoretical framework for the use of clinical trials and other health data for secondary research purposes, which was derived from research papers, consultation with stakeholders and the research community.  Four overall scenarios for data reuse were identified; scenario 1: evidence synthesis, scenario 2: secondary analyses, scenario 3: reproducibility, replication and validation, and scenario 4: education and methods development. contact@ardc.edu.au Secondary Data Use, Clinical Trials, Training Material, HeSANDA, Health Data Australia, HDA
Geophysical Research Data Processing and Modelling for 2030 Computation

The Cross-NCRIS National Data Assets program co-funded the ‘Geophysics 2030: Building a National High-Resolution Geophysics Reference Collection for 2030 Computation’ (Geophysics2030) project. At completion, Geophysics2030 i) trialled publishing vertically integrated geophysical datasets, making...

Keywords: Geophysics, Applied mathematics, Physical sciences, Computer and information sciences

Resource type: presentation

Geophysical Research Data Processing and Modelling for 2030 Computation https://dresa.org.au/materials/geophysical-research-data-processing-and-modelling-for-2030-computation The Cross-NCRIS National Data Assets program co-funded the ‘Geophysics 2030: Building a National High-Resolution Geophysics Reference Collection for 2030 Computation’ (Geophysics2030) project. At completion, Geophysics2030 i) trialled publishing vertically integrated geophysical datasets, making both raw datasets and successive levels of derivative data products available online in a new international self-describing data standard (first published in 2022); ii) co-located these datasets/data products with HPC computing resources required to process datasets at scale; and iii) developed new community software and environments allowing researchers to exploit the new data sets at high-resolution on a continental-scale. This ARDC, AuScope, NCI and TERN-funded project created new high-performance dataset and introduced a new, world-leading community platform that allows researchers to combine high-performance computing, high-resolution datasets, and flexible software workflows. The world-leading innovation was evidenced by new projects in collaboration with leading international researchers, including Jared Peacock, the United States Geological Survey-based leader of the new standards for Magnetotelluric (MT) data and Karl Kappler, DIAS Geophysics, who leads the development of ‘Aurora’, a National Science Foundation (USA) funded open-source software package for processing MT data using the new MTH5 standards. This Community Connect project, in partnership with NCI and AuScope, proposed to develop, deliver, and distribute a 2-day ‘Geophysical Research Data Processing and Modelling for 2030 Computation’ workshop in 2023. The training packages will consist of two parts, i) the utilisation of NCI for Geophysics processing and modelling, and ii) developing workflows for coupling Geophysical software, compute environments and datasets. Through previous engagement with the Geophysics community, we knew users of the 2030 Geophysics Collection were experts in their fields of geophysics data acquisition, processing and modelling. The community had high levels of computer literacy and deep technical skills in geophysics and research expertise. The workshop was targeted to support this advanced community and facilitate the usage of large co-located datasets and high-performance computing at the NCI HPC/cloud platform. rebecca@auscope.org.au Geophysics, Applied mathematics, Physical sciences, Computer and information sciences
Sharing a Trove List as a CollectionBuilder exhibition

You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. CollectionBuilder creates online exhibitions using static web...

Keywords: Trove, Trove List, CollectionBuilder, collection, GLAM Workbench, exhibition, HASS

Resource type: tutorial

Sharing a Trove List as a CollectionBuilder exhibition https://dresa.org.au/materials/sharing-a-trove-list-as-a-collectionbuilder-exhibition You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. [CollectionBuilder](https://collectionbuilder.github.io/) creates online exhibitions using static web technologies. But how do you get your List data from Trove into CollectionBuilder? This tutorial from the Trove Data Guide walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, Trove List, CollectionBuilder, collection, GLAM Workbench, exhibition, HASS
Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps

Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP,...

Keywords: Trove, maps, Gazetteer of Historical Australian Placenames (GHAP), GLAM Workbench, geospatial, HASS

Resource type: tutorial

Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps https://dresa.org.au/materials/create-a-layer-in-the-gazetteer-of-historical-australian-placenames-using-metadata-from-trove-s-digitised-maps Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP, but how do you get the data from Trove in a format that can be uploaded as a layer? This tutorial from the Trove Data Guide walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, maps, Gazetteer of Historical Australian Placenames (GHAP), GLAM Workbench, geospatial, HASS
Comparing manuscript collections from Trove in Mirador

You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The Mirador viewer can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get...

Keywords: Trove, images, manuscripts, GLAM Workbench, IIIF, HASS, Mirador

Resource type: tutorial

Comparing manuscript collections from Trove in Mirador https://dresa.org.au/materials/comparing-manuscript-collections-in-mirador You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The [Mirador viewer](https://projectmirador.org/) can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get manuscript collections from Trove to Mirador? This tutorial from the Trove Data Guide walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, images, manuscripts, GLAM Workbench, IIIF, HASS, Mirador
Working with a Trove collection in Tropy

You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. Tropy is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into...

Keywords: Trove, images, Tropy, IIIF, GLAM Workbench, HASS

Resource type: tutorial

Working with a Trove collection in Tropy https://dresa.org.au/materials/working-with-a-trove-collection-in-tropy You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. [Tropy](https://tropy.org/) is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into Tropy? This tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab Trove, images, Tropy, IIIF, GLAM Workbench, HASS
Analysing keywords in Trove’s digitised newspapers

You want to explore differences in language use across a collection of digitised newspaper articles. The Australian Text Analytics Platform provides a Keywords Analysis tool that helps you...

Keywords: text analysis, Australian Text Analytics Platform (ATAP), Trove, GLAM Workbench, Trove Newspaper and Gazette Harvester, newspapers, HASS

Resource type: tutorial

Analysing keywords in Trove’s digitised newspapers https://dresa.org.au/materials/analysing-keywords-in-trove-s-digitised-newspapers You want to explore differences in language use across a collection of digitised newspaper articles. The [Australian Text Analytics Platform](https://www.atap.edu.au/) provides a [Keywords Analysis tool](https://github.com/Australian-Text-Analytics-Platform/keywords-analysis) that helps you examine whether particular words are over or under-represented across collections of text. But how do get data from Trove’s newspapers to the keyword analysis tool? This tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step. Tim Sherratt (tim@timsherratt.au) ARDC Community Data Lab text analysis, Australian Text Analytics Platform (ATAP), Trove, GLAM Workbench, Trove Newspaper and Gazette Harvester, newspapers, HASS
WEBINAR: A practical guide to AI tools for life scientists

This record includes training materials associated with the Australian BioCommons webinar ‘A practical guide to AI tools for life scientists’. This webinar took place on 8 May 2024.
Event description
The widespread availability and application of AI tools like ChatGPT have fundamentally...

Keywords: Bioinformatics, Machine Learning, Artificial Intelligence, ChatGPT

WEBINAR: A practical guide to AI tools for life scientists https://dresa.org.au/materials/webinar-a-practical-guide-to-ai-tools-for-life-scientists This record includes training materials associated with the Australian BioCommons webinar ‘A practical guide to AI tools for life scientists’. This webinar took place on 8 May 2024. Event description The widespread availability and application of AI tools like ChatGPT have fundamentally transformed our approach to work, creativity, learning, and communication. In the realm of scientific research, the impact of AI extends far beyond mere promises, already catalysing significant advances and discoveries. This talk will explore how AI is reshaping scientific exploration and innovation. We explore how AI can accelerate research processes, from data analysis and code writing to hypothesis development. We will present some of the available and emerging AI and how we might effectively leverage these tools while acknowledging their limitations. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Speaker: Dr Michael Kuiper, Principal Research Scientist in Computational Biology and acting Group Leader of the Computational Modelling (CM) group at Data61 of CSIRO.  Host: Dr Patrick Capon, Australian BioCommons Training materials Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Kuiper_May2024_b_version: A PDF copy of the slides presented during the webinar. Q_and_A_AI-life-scientists: PDF copy of questions and answers from the webinar Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/NbYvq3OLEfo   Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning, Artificial Intelligence, ChatGPT
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://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
HeSANDA & Health Data Australia FAQ

This document provides answers to common questions about the Health Studies Australian National Data Asset (HeSANDA), and the Health Data Australia (HDA), including the usage of the health data platform, sharing, contributing and accessing clinital trails data, governance, and potential risks. 

Keywords: HeSANDA, Frequently asked Questions, Health Data Australia, training material

HeSANDA & Health Data Australia FAQ https://dresa.org.au/materials/hesanda-health-data-australia-faq This document provides answers to common questions about the Health Studies Australian National Data Asset (HeSANDA), and the Health Data Australia (HDA), including the usage of the health data platform, sharing, contributing and accessing clinital trails data, governance, and potential risks.  contact@ardc.edu.au Australian Research Data Commons (type: Editor) Australian Clinical Trials Alliance (type: Editor) Melbourne Academic Centre for Health (type: Editor) Mental Health Node (type: Editor) The Queensland Node (type: Editor) Sydney Health Partners Node (type: Editor) Western Australia Node (type: Editor) Monash University and Monash Partners Node (type: Editor) Health Translation South Australia (type: Editor) National Cancer Cooperative Trials Groups (type: Editor) Northern Australia Node (type: Editor) HeSANDA, Frequently asked Questions, Health Data Australia, training material
WEBINAR: MetaboLights: the home for metabolomics experiments and derived information

This record includes training materials associated with the Australian BioCommons webinar ‘MetaboLights: the home for metabolomics experiments and derived information’. This webinar took place on 9 April 2024.
Event description
MetaboLights is an open-access database for metabolomics studies,...

Keywords: Bioinformatics, Metabolomics, Metabolites, Data sharing

WEBINAR: MetaboLights: the home for metabolomics experiments and derived information https://dresa.org.au/materials/webinar-metabolights-the-home-for-metabolomics-experiments-and-derived-information This record includes training materials associated with the Australian BioCommons webinar ‘MetaboLights: the home for metabolomics experiments and derived information’. This webinar took place on 9 April 2024. Event description MetaboLights is an open-access database for metabolomics studies, their raw experimental data and associated metadata. It is cross-species, cross-technique and covers metabolite structures and their reference spectra as well as their biological roles and locations where available. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information. This webinar will provide an introduction to MetaboLights and how it can be used as: A repository, enabling the metabolomics community to share findings, data and protocols from metabolomics studies. A compound library of curated knowledge about metabolite structures, their reference spectra, as well as their biological roles, locations, concentrations, and raw data from metabolic experiments.  The webinar will provide details about data availability, standards and re-use, as well as guidance on submitting your own metabolomics data. Speaker: Dr Thomas Payne, Scientific Database Curator - MetaboLights, EMBL-EBI Host: Dr Patrick Capon, Australian BioCommons Training materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. 2024_MetaboLights_Webinar_TP: A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/aCALHhqxOiM   Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Metabolomics, Metabolites, Data sharing
WEBINAR: MaveDB: discovery and interpretation of high-throughput functional assay data

This record includes training materials associated with the Australian BioCommons webinar ‘MaveDB: discovery and interpretation of high-throughput functional assay data’. This webinar took place on 26 March 2024.
Event description
Multiplexed assays of variant effect (MAVEs) are a family of...

Keywords: Bioinformatics, Genetic variation, Functional annotation, Clinical genetics

WEBINAR: MaveDB: discovery and interpretation of high-throughput functional assay data https://dresa.org.au/materials/webinar-mavedb-discovery-and-interpretation-of-high-throughput-functional-assay-data This record includes training materials associated with the Australian BioCommons webinar ‘MaveDB: discovery and interpretation of high-throughput functional assay data’. This webinar took place on 26 March 2024. Event description Multiplexed assays of variant effect (MAVEs) are a family of experimental techniques that measure all single amino acid or single nucleotide changes in a gene or other functional element. MaveDB is an international community database that enables discovery and reuse of data from these experiments. It provides a platform for integrating large-scale measurements of sequence variant impact with applications that can be used to interpret the data for basic and clinical research. In this webinar we consider:  What are MAVEs and how are the experiments performed? How much MAVE data is available in MaveDB and how is it organised? Who can submit datasets to MaveDB? What are some of the clinical applications for MAVEs and how is the data being used to understand patient variants?   Speaker: Dr Alan Rubin, Senior Research Officer, WEHI  Host: Dr Melissa Burke, Australian BioCommons   Materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. MAVEDB_slides: A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/BXGQ2IuDnGE   Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Genetic variation, Functional annotation, Clinical genetics
WEBINAR: Scaling up bioinformatics with ABLeS, the Australian BioCommons Leadership Share

This record includes training materials associated with the Australian BioCommons webinar ‘Scaling up bioinformatics with ABLeS, the Australian BioCommons Leadership Share’. This webinar took place on 12 March 2024.
Event description
The Australian BioCommons Leadership Share (ABLeS) supports...

Keywords: Bioinformatics, Computational biology, Computational infrastructure

WEBINAR: Scaling up bioinformatics with ABLeS, the Australian BioCommons Leadership Share https://dresa.org.au/materials/webinar-scaling-up-bioinformatics-with-ables-the-australian-biocommons-leadership-share This record includes training materials associated with the Australian BioCommons webinar ‘Scaling up bioinformatics with ABLeS, the Australian BioCommons Leadership Share’. This webinar took place on 12 March 2024. Event description The Australian BioCommons Leadership Share (ABLeS) supports access to, and efficient use of, national computational systems for big-data bioinformatics. Designed for established life sciences projects, groups, institutes and consortia, ABLeS can be used to facilitate software optimisation and scaling, implementation of optimised software for production analyses, and creation of reference data. This webinar highlights how ABLeS is being used by life science communities across Australia to access and leverage bioinformatics at scale. We’ll explain the structure of the ABLeS program and how your life science community can get involved, as well as providing a breakdown of the program expectations and the support available from the BioCommons and our partners. Community members making use of ABLeS will share their perspective on the program, and the research outcomes that have resulted. ABLeS is supported by the Australian BioCommons in partnership with Bioplatforms Australia, the National Computational Infrastructure, and the Pawsey Supercomputing Centre. Speakers: Australian BioCommons: Dr Steven Manos Dr Johan Gustafsson Dr Ziad Al Bkhetan   ABLeS users: Dr Hardip Patel, National Centre for Indigenous Genomics, John Curtin School of Medical Research, Australian National University Chelsea Mayoh, Zero Childhood Cancer, Children's Cancer Institute Theodore Allnutt, Royal Botanic Gardens Victoria Materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. BioCommons_ABLeS: A PDF copy of the slides presented by the BioCommons team during the webinar. Mayoh_ABLeS: A PDF copy of the slides presented by Chelsea Mayoh   Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/Eb0z2-yaJbY   Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Computational biology, Computational infrastructure
WEBINAR: Multivariate integration of multi-omics data with mixOmics

This record includes training materials associated with the Australian BioCommons webinar ‘Multivariate integration of multi-omics data with mixOmics’. This webinar took place on 6 March 2024.
Event description
Multi-omics data (eg. transcriptomics, proteomics) collected from the same set of...

Keywords: Bioinformatics, Omics, Multiomics, Multi-omics, Data integration

WEBINAR: Multivariate integration of multi-omics data with mixOmics https://dresa.org.au/materials/webinar-multivariate-integration-of-multi-omics-data-with-mixomics This record includes training materials associated with the Australian BioCommons webinar ‘Multivariate integration of multi-omics data with mixOmics’. This webinar took place on 6 March 2024. Event description Multi-omics data (eg. transcriptomics, proteomics) collected from the same set of biospecimens or individuals is a powerful way to understand the underlying molecular mechanisms of a biological system.  mixOmics, a popular R package, integrates omics data from a wide range of sources into a single, unified view making it easier to explore and reveal interactions between omics layers. It overcomes many of the challenges of multi-omic data integration arising from data that are complex and large, with few samples (<50) and many molecules (>10,000), and generated using different technologies.  Prof Kim-Anh Lê Cao, head of the mixOmics team, is delivering this webinar to outline the different methods implemented in mixOmics and how statistical data integration is defined in this context. She will demonstrate how these approaches are applied to analysis of different multi-omics studies and outline the latest methodological developments in this area. From a study of human newborns, to multi-omics microbiomes, and multi-omics in single cells, these examples illustrate how mixOmics is used to perform variable selection and identify a signature of omics markers that characterise a specific phenotype or disease status. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Speaker: Prof Kim-Anh Lê Cao, Director of Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne. Host: Dr Melissa Burke, Australian BioCommons Training materials Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Mixomics_BioCommons: A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/5XpmQ5X89lA Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Omics, Multiomics, Multi-omics, Data integration
Tutorials to learn how to use STAN

Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics.

Keywords: Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB

Tutorials to learn how to use STAN https://dresa.org.au/materials/tutorials-to-learn-how-to-use-stan Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics. https://mc-stan.org/about/team/ Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB
Open Ecoacoustics make your own recogniser

Includes the requirements and practical steps required to make your own automated call recogniser using a convolution neural network.

The "Requirements" section includes demo data and requirements for the data you should include to develop your own recogniser as well as links to Anaconda &...

Keywords: Ecoacoustics, call recogniser, convolutional neural network

Open Ecoacoustics make your own recogniser https://dresa.org.au/materials/open-ecoacoustics-make-your-own-recogniser Includes the requirements and practical steps required to make your own automated call recogniser using a convolution neural network. The "Requirements" section includes demo data and requirements for the data you should include to develop your own recogniser as well as links to Anaconda & Raven Lite software. The "Practical Steps" provides instructions to run the required Jupyter notebook to build a recogniser with CNN. * Note additional AI methods will be available soon https://openecoacoustics.org/contact/ Ecoacoustics, call recogniser, convolutional neural network
Open Ecoacoustics wrangling sound files

An introduction to slicing, dicing, chopping, resampling, compressing etc sound files with an introduction to command line and graphical tools.

A "Requirements" section with demo data, file dependencies, and required software.

A "Presentation" section with an online introduction to storing...

Keywords: Ecoacoustics, sound files, data wrangling

Open Ecoacoustics wrangling sound files https://dresa.org.au/materials/open-ecoacoustics-wrangling-sound-files An introduction to slicing, dicing, chopping, resampling, compressing etc sound files with an introduction to command line and graphical tools. A "Requirements" section with demo data, file dependencies, and required software. A "Presentation" section with an online introduction to storing data, repairing data and segmenting files. A "Practical" section inclusive of setup, Terminal use, manipulating files with FFmpeg, using the AnalysisPrograms audio cutter, run EMU software https://openecoacoustics.org/contact/ Ecoacoustics, sound files, data wrangling
Open Ecoacoustics acoustic indices

Provides an introduction to and generation of false-colour spectrograms and indices.

Includes a "Requirements" section where demo audio files, other dependencies and required software.

Includes a "Presentation" section providing an online presentation on false colour...

Keywords: Ecoacoustics, false-colour spectrograms, acoustic indices

Open Ecoacoustics acoustic indices https://dresa.org.au/materials/open-ecoacoustics-acoustic-indices Provides an introduction to and generation of false-colour spectrograms and indices. Includes a "Requirements" section where demo audio files, other dependencies and required software. Includes a "Presentation" section providing an online presentation on false colour spectrograms. Includes a "Practical" section that provides the setup, use of terminal, Analysis Programs software, and calculation of acoustic indices. https://openecoacoustics.org/contact/ Ecoacoustics, false-colour spectrograms, acoustic indices
Open Ecoacoustics recording and labelling

This module includes recommendations for deployment, recording and labelling sounds, playing those sounds and annotation using Audacity and Raven software.

The "Requirements" section includes downloads of example data, required dependencies and software.

The "Presentation" walks through an...

Keywords: Ecoacoustics, recording sound, labelling sound, spectrograms

Open Ecoacoustics recording and labelling https://dresa.org.au/materials/open-ecoacoustics-recording-and-labelling This module includes recommendations for deployment, recording and labelling sounds, playing those sounds and annotation using Audacity and Raven software. The "Requirements" section includes downloads of example data, required dependencies and software. The "Presentation" walks through an online presentation with recommendations recorder deployment recommendations, annotation, raven software, & manual validation The "Practical" includes setup, single species annotation of spectrograms, multi-species, and generating images https://openecoacoustics.org/contact/ Ecoacoustics, recording sound, labelling sound, spectrograms
Open Ecoacoustics sound basics

This online presentation provides a review of five key concepts related to ecoacoustics: 1. Decibels, 2. clipping and gain, 3. ADC: Sample rate & bit depth, 4. Fast Fourier Transform (FFT), and 5. Spectrograms: time / frequency trade off.

Keywords: Ecoacoustics, sound basics, decibels, gain, sample rate, FFT, spectrograms

Open Ecoacoustics sound basics https://dresa.org.au/materials/open-ecoacoustics-sound-basics This online presentation provides a review of five key concepts related to ecoacoustics: 1. Decibels, 2. clipping and gain, 3. ADC: Sample rate & bit depth, 4. Fast Fourier Transform (FFT), and 5. Spectrograms: time / frequency trade off. https://openecoacoustics.org/contact/ Ecoacoustics, sound basics, decibels, gain, sample rate, FFT, spectrograms
Biosecurity Commons written support material

A variety of written material describing the fundamentals of the workflows available on Biosecurity Commons as well as guides to navigating the platform.

Includes: Risk Mapping, Dispersal Modelling, Surveillance Design, Impact Analysis and Proof of Freedom.

Keywords: Biosecurity Commons, Biosecurity, risk mapping, Species Distribution Modelling, dispersal modelling, surveillance design, impact analysis, proof of freedom

Biosecurity Commons written support material https://dresa.org.au/materials/biosecurity-commons-written-support-material A variety of written material describing the fundamentals of the workflows available on Biosecurity Commons as well as guides to navigating the platform. Includes: Risk Mapping, Dispersal Modelling, Surveillance Design, Impact Analysis and Proof of Freedom. https://www.biosecuritycommons.org.au/contact-us/ Biosecurity Commons, Biosecurity, risk mapping, Species Distribution Modelling, dispersal modelling, surveillance design, impact analysis, proof of freedom professional support ugrad masters mbr phd
Biosecurity Commons YouTube instructional videos

This growing set of instructional videos teaches users how to navigate the platform and how to run the variety of workflows available on the platform. An increasing number of these videos will be embedded into the platform https://app.biosecuritycommons.org.au/

Keywords: Biosecurity, risk mapping, Species Distribution Modelling, Biosecurity Commons

Biosecurity Commons YouTube instructional videos https://dresa.org.au/materials/biosecurity-commons-youtube-instructional-videos This growing set of instructional videos teaches users how to navigate the platform and how to run the variety of workflows available on the platform. An increasing number of these videos will be embedded into the platform https://app.biosecuritycommons.org.au/ https://www.biosecuritycommons.org.au/contact-us/ Biosecurity, risk mapping, Species Distribution Modelling, Biosecurity Commons support professional masters mbr phd
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://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://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
Ecoacoustics & EcoCommons Generalised Dissimilarity Modelling (GDM) use case

This example highlights how data collected with passive acoustic monitoring (PAM) can be used to examine spatial variation in species composition.

This example draws from an R package developed to make GDM more accessible: https://github.com/EcoCommons-Australia/community-modelling

Keywords: Generalised Dissimilarity Modelling, Ecoacoustics, EcoCommons

Ecoacoustics & EcoCommons Generalised Dissimilarity Modelling (GDM) use case https://dresa.org.au/materials/ecoacoustics-ecocommons-generalised-dissimilarity-modelling-gdm-use-case This example highlights how data collected with passive acoustic monitoring (PAM) can be used to examine spatial variation in species composition. This example draws from an R package developed to make GDM more accessible: https://github.com/EcoCommons-Australia/community-modelling https://openecoacoustics.org/contact/ Generalised Dissimilarity Modelling, Ecoacoustics, EcoCommons
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...

Keywords: Species Distribution Modelling, Ecoacoustics, Ecology, Owls, Mapping uncertainty

EcoCommons & Open EcoAcoustics 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://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://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/ Species Distribution Modelling, Ecology, R software, EcoCommons ugrad mbr phd
Get started with R: an introduction for beginners

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...

Keywords: Beginner R coding, The Carpentries, R studio, Beginer ecological modelling

Resource type: video, lesson

Get started with R: an introduction for beginners https://dresa.org.au/materials/get-started-with-r-an-introduction-for-beginners 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 pipeline operators, creating new columns based on existing ones, and summarising data The second video: Visualising data with ggplot2 covers: A recap of module 1 and getting started with ggplot2 to create plots and a variety of data visualisations Links to the R scripts are provided https://www.ecocommons.org.au/contact/ Beginner R coding, The Carpentries, R studio, Beginer ecological modelling 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://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/ Species Distribution Modelling, Ecology, EcoCommons, Beginer ecological modelling, Climate projections ugrad mbr