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Authors: Unsworth, Kathryn (orcid: 0...  or Zhang, Eden (orcid: 0000-00... 

WORKSHOP: Introduction to Machine Learning in R - from data to knowledge

This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Machine Learning in R - from data to knowledge’. This workshop took place over one, 4 hour sessions on 09 December 2024.
Event description
With the rise in high-throughput sequencing...

Keywords: Bioinformatics, Machine Learning

WORKSHOP: Introduction to Machine Learning in R - from data to knowledge https://dresa.org.au/materials/workshop-introduction-to-machine-learning-in-r-from-data-to-knowledge This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Machine Learning in R - from data to knowledge’. This workshop took place over one, 4 hour sessions on 09 December 2024. Event description With the rise in high-throughput sequencing technologies, the volume of omics data has grown exponentially. A major issue is to mine useful knowledge from these heterogeneous collections of data. The analysis of complex high-volume data is not trivial and classical tools cannot be used to explore their full potential. Machine Learning (ML), a discipline in which computers perform automated learning without being programmed explicitly and assist humans to make sense of large and complex data sets, can thus be very useful in mining large omics datasets to uncover new insights that can advance the field of bioinformatics. This hands-on workshop will introduce participants to the ML taxonomy and the applications of common ML algorithms to health data. The workshop will cover the foundational concepts and common methods being used to analyse omics data sets by providing a practical context through the use of basic but widely used R libraries. Participants will acquire an understanding of the standard ML processes, as well as the practical skills in applying them on familiar problems and publicly available real-world data sets. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Lead trainers: Dr Fotis Psomopoulos, Senior Researcher,  Institute of Applied Biosciences (INAB), Center for Research and Technology Hellas (CERTH) Facilitators: Dr Giorgia Mori, Australian BioCommons Dr Eden Zhang, Sydney Informatics Hub Dr Erin Graham, Queensland Cyber Infrastructure Foundation (QCIF) Infrastructure provision: Uwe Winter, Australian BioCommons Host: Dr. Giorgia Mori, 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. Training materials webpage Data and documentation     Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning
ARDC Digital Research Capabilities and Skills Framework: The Framework and Its Components

The ARDC's Digital Research Capabilities and Skills Framework, released in 2022, provides a structure for training programs to develop essential and advanced digital research skills. It aims to help researchers and professionals identify the necessary skills they need to leverage emerging...

Keywords: training material, skills framework, ARDC skills framework, ARDC capabilities framework, national skills framework, learning path, role profile, capabilities, FAIR implementation, skills, data management, research software, data governance, digital research infrastructure

ARDC Digital Research Capabilities and Skills Framework: The Framework and Its Components https://dresa.org.au/materials/ardc-digital-research-capabilities-and-skills-framework-the-framework-and-its-components The ARDC's Digital Research Capabilities and Skills Framework, released in 2022, provides a structure for training programs to develop essential and advanced digital research skills. It aims to help researchers and professionals identify the necessary skills they need to leverage emerging opportunities in data management, data analysis, data linking, AI, and machine learning. The framework aligns with technological advancements and encourages ongoing discussion and contributions to evolve the coverage of digital research skills. The framework focuses on digital research skills, excluding broader professional skills, and is intended for a wide range of stakeholders. It provides a structured approach for project teams and organisations to develop and enhance their digital research skills through six main components: a skills taxonomy, a skills glossary, a list of generalised roles, roles and skills-related profiles, learning paths, and a skills and roles matrix. The skills taxonomy classifies digital research skills into four capability families: Governance, Data, Software, and Digital Research Infrastructure Management. It provides a standard terminology for identifying and describing these skills. contact@ardc.edu.au Russell, Keith (type: Editor) Wong, Adeline (type: Editor) Lyrtzis, Ellen (type: Editor) training material, skills framework, ARDC skills framework, ARDC capabilities framework, national skills framework, learning path, role profile, capabilities, FAIR implementation, skills, data management, research software, data governance, digital research infrastructure
Ten Simple Rules for Researchers: Upskilling for a Rapidly Evolving Workforce

The following recommendations were inspired by the Australian Research Data Commons (ARDC) Digital Research Skills Summit 2023, that brought together Researchers, Learning Designers, Skills Trainers, and Librarians in productive discussions on how to run effective researcher skills training....

Keywords: Training, Training Material, Short Format Training, Digital Skills, Researcher Training, Learning

Ten Simple Rules for Researchers: Upskilling for a Rapidly Evolving Workforce https://dresa.org.au/materials/ten-simple-rules-for-researchers-upskilling-for-a-rapidly-evolving-workforce The following recommendations were inspired by the Australian Research Data Commons (ARDC) Digital Research Skills Summit 2023, that brought together Researchers, Learning Designers, Skills Trainers, and Librarians in productive discussions on how to run effective researcher skills training. These rules outline how to think about skills learning for researchers, plan training sessions, and efficiently maximize learning. We offer recommendations on how to design and develop learner-centered training programs (Rules 1 and 2), foster outreach, and connect with trainer communities (Rules 3 and 4). We then provide tips to manage and optimize training (Rules 5, 6, and 7), and conclude with valuable insights on preparing for uncertainty and the importance of post-training operations and continued learning (Rules 8, 9, and 10). contact@ardc.edu.au Training, Training Material, Short Format Training, Digital Skills, Researcher Training, Learning
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
DReSA: Project team reflections

This presentation provides thoughts and reflections from the Digital Research Skills Australaisa (DReSA) project team on DReSA. Team members highlight their perspectives on value propositions and benefits for their respective institutiosn/organisations and nationally, as well as individual...

Keywords: training events, training material, training repository, skilled workforce, digital research skills, digital research training, digital research, trainers, FAIR training

DReSA: Project team reflections https://dresa.org.au/materials/dresa-project-team-reflections-9dcb8538-6b7c-4822-b0ee-fbe57085dc70 This presentation provides thoughts and reflections from the Digital Research Skills Australaisa (DReSA) project team on DReSA. Team members highlight their perspectives on value propositions and benefits for their respective institutiosn/organisations and nationally, as well as individual reflections on collaboration and working together on the project so far. You can watch the video on YouTube here: https://youtu.be/qqH92itI8SI   contact@ardc.edu.au training events, training material, training repository, skilled workforce, digital research skills, digital research training, digital research, trainers, FAIR training
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
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://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 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 Training Materials Metadata Checklist v1.1

The ARDC Training Materials Metadata Checklist aims to support learning designers, training materials creators, trainers and national training infrastructure providers to capture key information and apply appropriate mechanisms to enable sharing and reuse of their training materials

Keywords: checklist, Training material, FAIR, standard, requirements, metadata

ARDC Training Materials Metadata Checklist v1.1 https://dresa.org.au/materials/ardc-training-materials-metadata-checklist-v1-1 The ARDC Training Materials Metadata Checklist aims to support learning designers, training materials creators, trainers and national training infrastructure providers to capture key information and apply appropriate mechanisms to enable sharing and reuse of their training materials contact@ardc.edu.au checklist, Training material, FAIR, standard, requirements, metadata
Show & Tell - Tackling 'no shows'

In this session, questions were asked on how to tackle 'no shows' for training events:

  • What are the motivations behind ‘no shows’?

  • What % of ‘no shows’ is acceptable? Any data on that?

  • Do we need to lay some gentle guilt trips?

  • Community Slides

  • Tackling ‘no shows’. What is your...

Keywords: training attendance, no shows, skills training, training material

Show & Tell - Tackling 'no shows' https://dresa.org.au/materials/show-tell-tackling-no-shows-9f0d32c0-b2af-4624-9df1-d4e087da81b6 In this session, questions were asked on how to tackle 'no shows' for training events: - What are the motivations behind ‘no shows’? - What % of ‘no shows’ is acceptable? Any data on that? - Do we need to lay some gentle guilt trips? - Community Slides - Tackling ‘no shows’. What is your approach? What would you be willing to try? contact@ardc.edu.au training attendance, no shows, skills training, training material
National skills ecosystem - call to action

In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4.

  • Skilled trainers / facilitators

  • National training registry

  • National training event calendar

  • Jointly developed training

  • Research...

Keywords: national skills initiatives, data skills, training, skills community, training material

National skills ecosystem - call to action https://dresa.org.au/materials/national-skills-ecosystem-call-to-action-ffd9b4ed-b557-496b-ac35-72467c03c71b In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4. - Skilled trainers / facilitators - National training registry - National training event calendar - Jointly developed training - Research support professionals: career/progression contact@ardc.edu.au national skills initiatives, data skills, training, skills community, training material
ARDC Skills Impact and Strategy Community Discussion

The focus of this community event arose from the ARDC SKills Summit 2021, hosted in collaboration with eResearch Australasia Conference. Two key themes identified at the Summit formed the focus of this event: 1) How to convince senior management the value of digital skills training so that they...

Keywords: training impact, evaluation, skills training, resourcing, value proposition, training material

ARDC Skills Impact and Strategy Community Discussion https://dresa.org.au/materials/ardc-skills-impact-and-strategy-community-discussion-e9d63cee-0d9c-4f8d-9c0f-58afe99b649b The focus of this community event arose from the ARDC SKills Summit 2021, hosted in collaboration with eResearch Australasia Conference. Two key themes identified at the Summit formed the focus of this event: 1) How to convince senior management the value of digital skills training so that they don't question resourcing 2) Evaluating the long-term impact of digital skills training on researchers’ workflows and outputs. You can watch the full video presentation on YouTube here: https://youtu.be/iSnE7OBILqs contact@ardc.edu.au training impact, evaluation, skills training, resourcing, value proposition, training material
Exploratory Data Analysis

This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).

Module 1: https://youtu.be/dMwHFhKWRRI

Module 3:...

Keywords: Data analysis, training material

Exploratory Data Analysis https://dresa.org.au/materials/exploratory-data-analysis This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH). **Module 1**: [https://youtu.be/dMwHFhKWRRI](https://youtu.be/dMwHFhKWRRI) **Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R) *The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub) sih.training@sydney.edu.au Mori, Giorgia (orcid: 0000-0003-3469-5632) Data analysis, training material
Fundamentals of Machine Learning

This is the first of four modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).

Module 2: https://youtu.be/HVAFflj2PS0
Module 3:...

Keywords: Machine Learning, training material

Fundamentals of Machine Learning https://dresa.org.au/materials/fundamentals-of-machine-learning This is the first of four modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH). **Module 2**: [https://youtu.be/HVAFflj2PS0](https://youtu.be/HVAFflj2PS0) **Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R) *The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub) sih.training@sydney.edu.au Machine Learning, training material