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WEBINAR: Where to go when your bioinformatics outgrows your compute

This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.

Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute...

Keywords: Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing

WEBINAR: Where to go when your bioinformatics outgrows your compute https://dresa.org.au/materials/webinar-where-to-go-when-your-bioinformatics-outgrows-your-compute-7a5a0ff8-8f4f-4fd0-af20-a88d515a6554 This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021. Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute resources. “I don’t know what compute resources I will need”, “My analysis won’t run and I don’t know why” and "Just getting it to work" are common pain points for researchers. In this webinar, you will learn how to understand the compute requirements for your bioinformatics workflows. You will also hear about ways of accessing compute that suits your needs as an Australian researcher, including Galaxy Australia, cloud and high-performance computing services offered by the Australian Research Data Commons, the National Compute Infrastructure (NCI) and Pawsey.  We also describe bioinformatics and computing support services available to Australian researchers.  This webinar was jointly organised with the Sydney Informatics Hub at the University of Sydney. 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. Where to go when your bioinformatics outgrows your compute - slides (PDF and PPTX): Slides presented during the webinar Australian research computing resources cheat sheet (PDF): A list of resources and useful links mentioned during the webinar. Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/hNTbngSc-W0 Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing
WEBINAR: High performance bioinformatics: submitting your best NCMAS application

This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021.

Bioinformaticians are increasingly turning to specialised compute infrastructure and...

Keywords: Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS

WEBINAR: High performance bioinformatics: submitting your best NCMAS application https://dresa.org.au/materials/webinar-high-performance-bioinformatics-submitting-your-best-ncmas-application-ee80822f-74ac-41af-a5a4-e162c10e6d78 This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021. Bioinformaticians are increasingly turning to specialised compute infrastructure and efficient, scalable workflows as their research becomes more data intensive. Australian researchers that require extensive compute resources to process large datasets can apply for access to national high performance computing facilities (e.g. Pawsey and NCI) to power their research through the National Computational Merit Allocation Scheme (NCMAS). NCMAS is a competitive, merit-based scheme and requires applicants to carefully consider how the compute infrastructure and workflows will be applied.  This webinar provides life science researchers with insights into what makes a strong NCMAS application, with a focus on the technical assessment, and how to design and present effective and efficient bioinformatic workflows for the various national compute facilities. It will be followed by a short Q&A session. 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. High performance bioinformatics: submitting your best NCMAS application - slides (PDF and PPTX): Slides presented during the webinar   Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/HeFGjguwS0Y Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS
WORKSHOP: R: fundamental skills for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.

 

Event description

Biologists need data analysis skills to be able to...

Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation

WORKSHOP: R: fundamental skills for biologists https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists-81aa00db-63ad-4962-a7ac-b885bf9f676b This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.   Event description Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.  R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.  Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R. Topics covered in this workshop include: Spreadsheets, organising data and first steps with R Manipulating and analysing data with dplyr Data visualisation Summarized experiments and getting started with Bioconductor   This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI  with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. 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. Schedule (PDF): A breakdown of the topics and timings for the workshop Recommended resources (PDF): A list of resources recommended by trainers and participants Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere:   This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available. https://saskiafreytag.github.io/biocommons-r-intro/ This is derived from material produced as part of The Carpentries Incubator project https://carpentries-incubator.github.io/bioc-intro/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WORKSHOP: RNA-Seq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022.

Event description

RNA sequencing (RNA-seq) is a common method used to...

Keywords: Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re

WORKSHOP: RNA-Seq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rna-seq-reads-to-differential-genes-and-pathways-5a384156-d3de-4d5d-9797-e689bf6592f8 This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022. Event description RNA sequencing (RNA-seq) is a common method used to understand the differences in gene expression and molecular pathways between two or more groups. This workshop introduces the fundamental concepts of RNA sequencing experiments and will allow you to try out the analysis using data from a study of Williams-Beuren Syndrome, a rare disease.  In the first part of the workshop you will learn how to convert sequence reads into analysis ready count data. To do this we will use nf-core/rnaseq - a portable, scalable, reproducible and publicly available workflow on Pawsey Nimbus Cloud. In the second part of the workshop you will use the count data you created to identify differential genes and pathways using R/Rstudio. By the end of the workshop, you should be able to perform your own RNA-seq analysis for differential gene expression and pathway analysis! This workshop is presented by the Australian BioCommons and Sydney Informatics Hub with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. 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. RNAseq reads to differential genes and pathways - Additional Resources (PDF): Additional resources compiled by the Sydney Informatics Hub rnaseq_DE_analysis_Day2.html: HTML version of code used on day 2 of the workshop rnaseq_DE_analysis_Day2.Rmd: R Markdown version of code used on day 2 of the workshop RNAseq reads to differential genes and pathways_Q_and_A (PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere: This workshop follows the tutorial ‘RNA-seq: reads to differential gene expression workshop series’ developed by the Sydney Informatics Hub. https://sydney-informatics-hub.github.io/training.RNAseq.series-quarto/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097 FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration.

MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a...

Keywords: Small satellites, metadata, vocabularies, training material

MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration. https://dresa.org.au/materials/metasat-an-open-collaboratively-developed-metadata-toolkit-to-support-the-future-of-space-exploration-49af7d4d-f0d1-4f95-9fbe-afbd45170a6a MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a longstanding need for a vocabulary to span these community standards. A vocabulary to annotate the data and information outputs of these satellite missions, to enable search across disparate data repositories, and provide support for application of analytical services to retrieved datasets. A common problem among small satellite teams is finding information about how other small satellites were put together, what parts worked well, what weren't compatible, what were the mission goals and outcomes. A lot of this information can be found, but it's not usually described in a consistent and searchable way across projects. MetaSat helps by building a uniform language of description which can be embedded into small satellite databases and tools to connect information across projects. Although a relatively new vocabulary initiative, MetaSat has secured early adoption by SatNOGS, a global network of ground stations that collects, manages & enables access to satellite observations. Also partnering with NASA's Small Satellite Reliability Initiative, and in discussion with NASA concerning implementation of the vocabulary in other areas of its information infrastructure. You can watch the full presentation on YouTube here: https://www.youtube.com/watch?v=uaCOzNL1eh4 contact@ardc.edu.au Small satellites, metadata, vocabularies, training material
WORKSHOP: RNA-Seq: reads to differential genes and pathways

This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022.

Event description

RNA sequencing (RNA-seq) is a common method...

Keywords: Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re

WORKSHOP: RNA-Seq: reads to differential genes and pathways https://dresa.org.au/materials/workshop-rna-seq-reads-to-differential-genes-and-pathways This record includes training materials associated with the Australian BioCommons workshop ‘RNA-Seq: reads to differential genes and pathways’. This workshop took place over two, 3.5 hour sessions on 27 and 28 September 2022. **Event description** RNA sequencing (RNA-seq) is a common method used to understand the differences in gene expression and molecular pathways between two or more groups. This workshop introduces the fundamental concepts of RNA sequencing experiments and will allow you to try out the analysis using data from a study of Williams-Beuren Syndrome, a rare disease.  In the first part of the workshop you will learn how to convert sequence reads into analysis ready count data. To do this we will use nf-core/rnaseq - a portable, scalable, reproducible and publicly available workflow on Pawsey Nimbus Cloud. In the second part of the workshop you will use the count data you created to identify differential genes and pathways using R/Rstudio. By the end of the workshop, you should be able to perform your own RNA-seq analysis for differential gene expression and pathway analysis! This workshop is presented by the Australian BioCommons and Sydney Informatics Hub with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. 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. * RNAseq reads to differential genes and pathways - Additional Resources (PDF): Additional resources compiled by the Sydney Informatics Hub * rnaseq_DE_analysis_Day2.html: HTML version of code used on day 2 of the workshop * rnaseq_DE_analysis_Day2.Rmd: R Markdown version of code used on day 2 of the workshop * RNAseq reads to differential genes and pathways_Q_and_A (PDF): Archive of questions and their answers from the workshop Slack Channel. **Materials shared elsewhere:** This workshop follows the tutorial ‘RNA-seq: reads to differential gene expression workshop series’ developed by the Sydney Informatics Hub. https://sydney-informatics-hub.github.io/training.RNAseq.series-quarto/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Transcriptomics, RNA-seq, Workflows, Nextflow, nf-co.re
WORKSHOP: R: fundamental skills for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.

Event description

Biologists need data analysis skills to be able to...

Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation

WORKSHOP: R: fundamental skills for biologists https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022. **Event description** Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.  R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.  Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R. Topics covered in this workshop include: - Spreadsheets, organising data and first steps with R - Manipulating and analysing data with dplyr - Data visualisation - Summarized experiments and getting started with Bioconductor This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI  with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. 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. - Schedule (PDF): A breakdown of the topics and timings for the workshop - Recommended resources (PDF): A list of resources recommended by trainers and participants - Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel. **Materials shared elsewhere:** This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available. https://saskiafreytag.github.io/biocommons-r-intro/ This is derived from material produced as part of The Carpentries Incubator project https://carpentries-incubator.github.io/bioc-intro/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WEBINAR: Where to go when your bioinformatics outgrows your compute

This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021.

Bioinformatics analyses are often complex, requiring multiple software tools and specialised...

Keywords: Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing

WEBINAR: Where to go when your bioinformatics outgrows your compute https://dresa.org.au/materials/webinar-where-to-go-when-your-bioinformatics-outgrows-your-compute This record includes training materials associated with the Australian BioCommons webinar ‘Where to go when your bioinformatics outgrows your compute’. This webinar took place on 19 August 2021. Bioinformatics analyses are often complex, requiring multiple software tools and specialised compute resources. “I don’t know what compute resources I will need”, “My analysis won’t run and I don’t know why” and "Just getting it to work" are common pain points for researchers. In this webinar, you will learn how to understand the compute requirements for your bioinformatics workflows. You will also hear about ways of accessing compute that suits your needs as an Australian researcher, including Galaxy Australia, cloud and high-performance computing services offered by the Australian Research Data Commons, the National Compute Infrastructure (NCI) and Pawsey.  We also describe bioinformatics and computing support services available to Australian researchers.  This webinar was jointly organised with the Sydney Informatics Hub at the University of Sydney. 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. - Where to go when your bioinformatics outgrows your compute - slides (PDF and PPTX): Slides presented during the webinar - Australian research computing resources cheat sheet (PDF): A list of resources and useful links mentioned during the webinar. **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/hNTbngSc-W0 Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High performance computing, HPC, Galaxy Australia, Nectar Research Cloud, Pawsey Supercomputing Centre, NCI, NCMAS, Cloud computing
WEBINAR: High performance bioinformatics: submitting your best NCMAS application

This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021.

Bioinformaticians are increasingly turning to specialised compute infrastructure and...

Keywords: Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS

WEBINAR: High performance bioinformatics: submitting your best NCMAS application https://dresa.org.au/materials/webinar-high-performance-bioinformatics-submitting-your-best-ncmas-application This record includes training materials associated with the Australian BioCommons webinar ‘High performance bioinformatics: submitting your best NCMAS application’. This webinar took place on 20 August 2021. Bioinformaticians are increasingly turning to specialised compute infrastructure and efficient, scalable workflows as their research becomes more data intensive. Australian researchers that require extensive compute resources to process large datasets can apply for access to national high performance computing facilities (e.g. Pawsey and NCI) to power their research through the National Computational Merit Allocation Scheme (NCMAS). NCMAS is a competitive, merit-based scheme and requires applicants to carefully consider how the compute infrastructure and workflows will be applied.  This webinar provides life science researchers with insights into what makes a strong NCMAS application, with a focus on the technical assessment, and how to design and present effective and efficient bioinformatic workflows for the various national compute facilities. It will be followed by a short Q&A session. 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. - High performance bioinformatics: submitting your best NCMAS application - slides (PDF and PPTX): Slides presented during the webinar **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/HeFGjguwS0Y Melissa Burke (melissa@biocommons.org.au) Computational Biology, Bioinformatics, High Performance Computing, HPC, NCMAS
MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration.

MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a...

Keywords: Small satellites, metadata, vocabularies, training material

MetaSat. An open, collaboratively-developed metadata toolkit to support the future of space exploration. https://dresa.org.au/materials/metasat-an-open-collaboratively-developed-metadata-toolkit-to-support-the-future-of-space-exploration MetaSat is an open metadata toolkit for describing small satellite (and even large satellite) missions in a uniform and shareable way. Optimised for small satellite missions, MetaSat fills an informatics gap. Although there have been a number of relevant metadata sets, there has been a longstanding need for a vocabulary to span these community standards. A vocabulary to annotate the data and information outputs of these satellite missions, to enable search across disparate data repositories, and provide support for application of analytical services to retrieved datasets. A common problem among small satellite teams is finding information about how other small satellites were put together, what parts worked well, what weren't compatible, what were the mission goals and outcomes. A lot of this information can be found, but it's not usually described in a consistent and searchable way across projects. MetaSat helps by building a uniform language of description which can be embedded into small satellite databases and tools to connect information across projects. Although a relatively new vocabulary initiative, MetaSat has secured early adoption by SatNOGS, a global network of ground stations that collects, manages & enables access to satellite observations. Also partnering with NASA's Small Satellite Reliability Initiative, and in discussion with NASA concerning implementation of the vocabulary in other areas of its information infrastructure. You can watch the full presentation on YouTube here: https://www.youtube.com/watch?v=uaCOzNL1eh4 contact@ardc.edu.au Small satellites, metadata, vocabularies, training material
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-bba41a59-8479-4f4f-b9ee-337b9eb294bf FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management