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://zenodo.org/records/6766951
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)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Doyle, Maria
Ansell, Brendan (orcid: 0000-0003-0297-897X)
Varshney, Akriti
Bourke, Caitlin (orcid: 0000-0002-4466-6563)
Conradsen, Cara (orcid: 0000-0001-9797-3412)
Jung, Chol-Hee (orcid: 0000-0002-2992-3162)
Sandoval, Claudia
Chandrananda, Dineika (orcid: 0000-0002-8834-9500)
Zhang, Eden (orcid: 0000-0003-0294-3734)
Rosello, Fernando (orcid: 0000-0003-3885-8777)
Iacono, Giulia (orcid: 0000-0002-1527-0754)
Tarasova, Ilariya (orcid: 0000-0002-0895-9385)
Chung, Jessica (orcid: 0000-0002-0627-0955)
Moffet, Joel
Gustafsson, Johan (orcid: 0000-0002-2977-5032)
Ding, Ke
Feher, Kristen
Perlaza-Jimenez, Laura (orcid: 0000-0002-8511-1134)
Crowe, Mark (orcid: 0000-0002-9514-2487)
Ma, Mengyao
Kandhari, Nitika (orcid: 0000-0002-0261-727X)
Williams, Sarah
Nelson, Tiffanie (orcid: 0000-0002-5341-312X)
Schreiber, Veronika (orcid: 0000-0001-6088-7828)
Pinzon Perez, William
Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
ARDC 2023 Skills Summit - Frameworks Panel Discussion (Day 2 - February 10, 2023)
Presentations to the ARDC Skills Summit 2023 (Panel Talks Day 2 - February 10th, 2023)
Dr Peter Derbyshire - Unpacking the ATSE report - Our STEM skilled future and the need for a national skills taxonomy
Anthony Beitz - Applying Skills Framework for the Information Age (SFIA) within DSTG
Kate...
Keywords: training material, research, training, skills, framework, sfia, eresearch, skills frameworks, skills taxonomies, skills classifications, skill shortages, transferrable skills, applying SFIA, training gaps, workforce requirements, job requirements, DReSA, digital literacy, applying skills frameworks, Australian Skills Classification framework, ASC
ARDC 2023 Skills Summit - Frameworks Panel Discussion (Day 2 - February 10, 2023)
https://zenodo.org/records/7711287
https://dresa.org.au/materials/ardc-2023-skills-summit-frameworks-panel-discussion-day-2-february-10-2023-c00730b5-3444-4ccd-8f8f-9ae8ec3dfbe6
Presentations to the ARDC Skills Summit 2023 (Panel Talks Day 2 - February 10th, 2023)
Dr Peter Derbyshire - Unpacking the ATSE report - Our STEM skilled future and the need for a national skills taxonomy
Anthony Beitz - Applying Skills Framework for the Information Age (SFIA) within DSTG
Kate Morrison - A national skills taxonomy - Australian Skills Classification (ASC)
Kathryn Unsworth - ARDC Digital Research Capabilities & Skills Framework
Peter Embelton - Enhancing skills uplift for researchers through the alignment and implementation of skills frameworks
These presentations cover skills frameworks/taxonomies/classifications, skill shortages, transferrable skills, applying SFIA (Skills Framework for the Information Age), Australian Skills Classification framework, training gaps, workforce/job requirements, Digital Research Skills Australasia (DReSA), digital literacy and applying skills frameworks.
contact@ardc.edu.au
Derbyshire, Peter
Beitz, Anthony (orcid: 0000-0002-2071-2852)
Morrison, Kate
Unsworth, Kathryn (orcid: 0000-0002-5407-9987)
Embelton, Peter
training material, research, training, skills, framework, sfia, eresearch, skills frameworks, skills taxonomies, skills classifications, skill shortages, transferrable skills, applying SFIA, training gaps, workforce requirements, job requirements, DReSA, digital literacy, applying skills frameworks, Australian Skills Classification framework, ASC
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://zenodo.org/records/5094034
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
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Martinez, Paula A. (orcid: 0000-0002-8990-1985)
Simons, Natasha (orcid: 0000-0003-0635-1998)
Russell, Keith (orcid: 0000-0001-5390-2719)
McCafferty, Siobhann (orcid: 0000-0002-2491-0995)
Ferrers, Richard (orcid: 0000-0002-2923-9889)
McEachern, Steve (orcid: 0000-0001-7848-4912)
Barlow, Melanie (orcid: 0000-0002-3956-5784)
Brady, Catherine (orcid: 0000-0002-7919-7592)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Quiroga, Maria del Mar (orcid: 0000-0002-8943-2808)
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://zenodo.org/records/5832057
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
Bouquin, Daina (orcid: 0000-0003-2626-3688)
Chivvis, Daniel (orcid: 0000-0001-6656-160X)
Small satellites, metadata, vocabularies, training material
ARDC 2023 Skills Summit - Frameworks Panel Discussion (Day 2 - February 10, 2023)
Presentations to the ARDC Skills Summit 2023 (Panel Talks Day 2 - February 10th, 2023)
Dr Peter Derbyshire - Unpacking the ATSE report - Our STEM skilled future and the need for a national skills taxonomy
Anthony Beitz - Applying Skills Framework for the Information Age (SFIA) within DSTG
Kate...
Keywords: training material, research, training, skills, framework, sfia, eresearch, skills frameworks, skills taxonomies, skills classifications, skill shortages, transferrable skills, applying SFIA, training gaps, workforce requirements, job requirements, DReSA, digital literacy, applying skills frameworks, Australian Skills Classification framework, ASC
ARDC 2023 Skills Summit - Frameworks Panel Discussion (Day 2 - February 10, 2023)
https://zenodo.org/record/7711287
https://dresa.org.au/materials/ardc-2023-skills-summit-frameworks-panel-discussion-day-2-february-10-2023
Presentations to the ARDC Skills Summit 2023 (Panel Talks Day 2 - February 10th, 2023)
Dr Peter Derbyshire - Unpacking the ATSE report - Our STEM skilled future and the need for a national skills taxonomy
Anthony Beitz - Applying Skills Framework for the Information Age (SFIA) within DSTG
Kate Morrison - A national skills taxonomy - Australian Skills Classification (ASC)
Kathryn Unsworth - ARDC Digital Research Capabilities & Skills Framework
Peter Embelton - Enhancing skills uplift for researchers through the alignment and implementation of skills frameworks
These presentations cover skills frameworks/taxonomies/classifications, skill shortages, transferrable skills, applying SFIA (Skills Framework for the Information Age), Australian Skills Classification framework, training gaps, workforce/job requirements, Digital Research Skills Australasia (DReSA), digital literacy and applying skills frameworks.
contact@ardc.edu.au
Derbyshire, Peter
Beitz, Anthony (orcid: 0000-0002-2071-2852)
Morrison, Kate
Unsworth, Kathryn (orcid: 0000-0002-5407-9987)
Embelton, Peter
training material, research, training, skills, framework, sfia, eresearch, skills frameworks, skills taxonomies, skills classifications, skill shortages, transferrable skills, applying SFIA, training gaps, workforce requirements, job requirements, DReSA, digital literacy, applying skills frameworks, Australian Skills Classification framework, ASC
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://zenodo.org/record/6766951
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)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Doyle, Maria
Ansell, Brendan (orcid: 0000-0003-0297-897X)
Varshney, Akriti
Bourke, Caitlin (orcid: 0000-0002-4466-6563)
Conradsen, Cara (orcid: 0000-0001-9797-3412)
Jung, Chol-Hee (orcid: 0000-0002-2992-3162)
Sandoval, Claudia
Chandrananda, Dineika (orcid: 0000-0002-8834-9500)
Zhang, Eden (orcid: 0000-0003-0294-3734)
Rosello, Fernando (orcid: 0000-0003-3885-8777)
Iacono, Giulia (orcid: 0000-0002-1527-0754)
Tarasova, Ilariya (orcid: 0000-0002-0895-9385)
Chung, Jessica (orcid: 0000-0002-0627-0955)
Moffet, Joel
Gustafsson, Johan (orcid: 0000-0002-2977-5032)
Ding, Ke
Feher, Kristen
Perlaza-Jimenez, Laura (orcid: 0000-0002-8511-1134)
Crowe, Mark (orcid: 0000-0002-9514-2487)
Ma, Mengyao
Kandhari, Nitika (orcid: 0000-0002-0261-727X)
Williams, Sarah
Nelson, Tiffanie (orcid: 0000-0002-5341-312X)
Schreiber, Veronika (orcid: 0000-0001-6088-7828)
Pinzon Perez, William
Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
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://zenodo.org/record/5832057
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
Bouquin, Daina (orcid: 0000-0003-2626-3688)
Chivvis, Daniel (orcid: 0000-0001-6656-160X)
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://zenodo.org/record/5094034
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
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Martinez, Paula A. (orcid: 0000-0002-8990-1985)
Simons, Natasha (orcid: 0000-0003-0635-1998)
Russell, Keith (orcid: 0000-0001-5390-2719)
McCafferty, Siobhann (orcid: 0000-0002-2491-0995)
Ferrers, Richard (orcid: 0000-0002-2923-9889)
McEachern, Steve (orcid: 0000-0001-7848-4912)
Barlow, Melanie (orcid: 0000-0002-3956-5784)
Brady, Catherine (orcid: 0000-0002-7919-7592)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Quiroga, Maria del Mar (orcid: 0000-0002-8943-2808)
training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management