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Keywords: AI  or NVivo  or data stewardship  or EcoCommons 

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
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
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
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://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
Understanding your role as a Data Steward: the role of a Data Steward across the research data management lifecycle

This presentation provides an overview of the role and responsibilities of Data Steward at the University of Adelaide across the six key phases of the research data management lifecycle.

The resource was developed by the University of Adelaide Library in December 2023 as part of the...

Keywords: research data management, RDM, RDM Training, data stewardship, research data governance, role profiles

Resource type: presentation

Understanding your role as a Data Steward: the role of a Data Steward across the research data management lifecycle https://dresa.org.au/materials/understanding-your-role-as-a-data-steward-the-role-of-a-data-steward-across-the-research-data-management-lifecycle This presentation provides an overview of the role and responsibilities of Data Steward at the University of Adelaide across the six key phases of the research data management lifecycle. The resource was developed by the University of Adelaide Library in December 2023 as part of the Institutional Underpinnings program facilitated by the Australian Research Data Commons (ARDC). University of Adelaide Library contact: https://www.adelaide.edu.au/library/ask-library research data management, RDM, RDM Training, data stewardship, research data governance, role profiles mbr phd ecr researcher
WEBINAR: AlphaFold: what's in it for me?

This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023.

Event description 

AlphaFold has taken the scientific world by storm with the ability to accurately predict the...

Keywords: Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning

WEBINAR: AlphaFold: what's in it for me? https://dresa.org.au/materials/webinar-alphafold-what-s-in-it-for-me-4d1ea222-4240-4b68-b9ae-7769ac664ee0 This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023. Event description  AlphaFold has taken the scientific world by storm with the ability to accurately predict the structure of any protein in minutes using artificial intelligence (AI). From drug discovery to enzymes that degrade plastics, this promises to speed up and fundamentally change the way that protein structures are used in biological research.  Beyond the hype, what does this mean for structural biology as a field (and as a career)? Dr Craig Morton, Drug Discovery Lead at the CSIRO, is an early adopter of AlphaFold and has decades of expertise in protein structure / function, protein modelling, protein – ligand interactions and computational small molecule drug discovery, with particular interest in anti-infective agents for the treatment of bacterial and viral diseases. Craig joins this webinar to share his perspective on the implications of AlphaFold for science and structural biology. He will give an overview of how AlphaFold works, ways to access AlphaFold, and some examples of how it can be used for protein structure/function analysis. 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. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/4ytn2_AiH8s Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning
Role profiles for the Bureau's Stewardship Model

This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which...

Keywords: role profiles, data stewardship, data governance, data management, skills, training, training material

Role profiles for the Bureau's Stewardship Model https://dresa.org.au/materials/role-profiles-for-the-bureau-s-stewardship-model-19ee77b4-d15e-42da-96b4-9e3056d1b3e7 This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which provide the role description, assignment and key responsibilities. You can watch the YouTube video here: https://youtu.be/RLf6B-NIffU contact@ardc.edu.au role profiles, data stewardship, data governance, data management, skills, training, training material
Accelerating skills development in Data science and AI at scale

At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...

Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material

Accelerating skills development in Data science and AI at scale https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale-2d8a65fa-f96e-44ad-a026-cfae3f38d128 At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally. The talk will also cover our approach as outlined below •        Combined survey of gaps in skills and trainings for Data science and AI •        Provide seats to partners •        Share associate instructors/helpers/volunteers •        Develop combined training materials •        Publish a repository of open source trainings •        Train the trainer activities •        Establish a network of volunteers to deliver trainings at their local regions Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community. Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together. contact@ardc.edu.au AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
ARDC Skills Landscape

The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its...

Keywords: skills, data skills, eresearch skills, community, skilled workforce, FAIR, research data management, data stewardship, data governance, data use, data generation, training material

ARDC Skills Landscape https://dresa.org.au/materials/ardc-skills-landscape-56b224ca-9e30-4771-8615-d028c7be86a6 The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its purpose of providing Australian researchers with a competitive advantage through data.   In this presentation, Kathryn Unsworth introduces the ARDC Skills Landscape. The Landscape is a first step in developing a national skills framework to enable a coordinated and cohesive approach to skills development across the Australian eResearch sector. It is also a first step towards helping to analyse current approaches in data training to identify: - Siloed skills initiatives, and finding ways to build partnerships and improve collaboration - Skills deficits, and working to address the gaps in data skills - Areas of skills development for investment by skills stakeholders like universities, research organisations, skills and training service providers, ARDC, etc.   contact@ardc.edu.au skills, data skills, eresearch skills, community, skilled workforce, FAIR, research data management, data stewardship, data governance, data use, data generation, training material
Monash University - University of Queensland training partnership in Data science and AI

We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...

Keywords: data skills, training partnerships, data science, AI, training material

Monash University - University of Queensland training partnership in Data science and AI https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai-8082bf73-d20f-4214-ad8c-95123e25a36c We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers. contact@ardc.edu.au data skills, training partnerships, data science, AI, training material
WEBINAR: AlphaFold: what's in it for me?

This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023.

Event description 

AlphaFold has taken the scientific world by storm with the ability to accurately predict the...

Keywords: Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning

WEBINAR: AlphaFold: what's in it for me? https://dresa.org.au/materials/webinar-alphafold-what-s-in-it-for-me This record includes training materials associated with the Australian BioCommons webinar ‘WEBINAR: AlphaFold: what’s in it for me?’. This webinar took place on 18 April 2023. Event description  AlphaFold has taken the scientific world by storm with the ability to accurately predict the structure of any protein in minutes using artificial intelligence (AI). From drug discovery to enzymes that degrade plastics, this promises to speed up and fundamentally change the way that protein structures are used in biological research.  Beyond the hype, what does this mean for structural biology as a field (and as a career)? Dr Craig Morton, Drug Discovery Lead at the CSIRO, is an early adopter of AlphaFold and has decades of expertise in protein structure / function, protein modelling, protein – ligand interactions and computational small molecule drug discovery, with particular interest in anti-infective agents for the treatment of bacterial and viral diseases. Craig joins this webinar to share his perspective on the implications of AlphaFold for science and structural biology. He will give an overview of how AlphaFold works, ways to access AlphaFold, and some examples of how it can be used for protein structure/function analysis. 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. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/4ytn2_AiH8s Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning, Structural Biology, Proteins, Drug discovery, AlphaFold, AI, Artificial Intelligence, Deep learning
Role profiles for the Bureau's Stewardship Model

This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which...

Keywords: role profiles, data stewardship, data governance, data management, skills, training, training material

Role profiles for the Bureau's Stewardship Model https://dresa.org.au/materials/role-profiles-for-the-bureau-s-stewardship-model This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which provide the role description, assignment and key responsibilities. You can watch the YouTube video here: https://youtu.be/RLf6B-NIffU contact@ardc.edu.au role profiles, data stewardship, data governance, data management, skills, training, training material
ARDC Skills Landscape

The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its...

Keywords: skills, data skills, eresearch skills, community, skilled workforce, FAIR, research data management, data stewardship, data governance, data use, data generation, training material

ARDC Skills Landscape https://dresa.org.au/materials/ardc-skills-landscape The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its purpose of providing Australian researchers with a competitive advantage through data.   In this presentation, Kathryn Unsworth introduces the ARDC Skills Landscape. The Landscape is a first step in developing a national skills framework to enable a coordinated and cohesive approach to skills development across the Australian eResearch sector. It is also a first step towards helping to analyse current approaches in data training to identify: - Siloed skills initiatives, and finding ways to build partnerships and improve collaboration - Skills deficits, and working to address the gaps in data skills - Areas of skills development for investment by skills stakeholders like universities, research organisations, skills and training service providers, ARDC, etc.   contact@ardc.edu.au skills, data skills, eresearch skills, community, skilled workforce, FAIR, research data management, data stewardship, data governance, data use, data generation, training material
Accelerating skills development in Data science and AI at scale

At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...

Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material

Accelerating skills development in Data science and AI at scale https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally. The talk will also cover our approach as outlined below •        Combined survey of gaps in skills and trainings for Data science and AI •        Provide seats to partners •        Share associate instructors/helpers/volunteers •        Develop combined training materials •        Publish a repository of open source trainings •        Train the trainer activities •        Establish a network of volunteers to deliver trainings at their local regions Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community. Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together. contact@ardc.edu.au AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Monash University - University of Queensland training partnership in Data science and AI

We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...

Keywords: data skills, training partnerships, data science, AI, training material

Monash University - University of Queensland training partnership in Data science and AI https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers. contact@ardc.edu.au data skills, training partnerships, data science, AI, training material