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Authors: Unsworth, Kathryn (orcid: 0...  or The Carpentries 

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
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
Databases and SQL

A relational database is an extremely efficient, fast and widespread means of storing structured data, and Structured Query Language (SQL) is the standard means for reading from and writing to databases. Databases use multiple tables, linked by well-defined relationships, to store large amounts...

Keywords: SQL

Databases and SQL https://dresa.org.au/materials/databases-and-sql A relational database is an extremely efficient, fast and widespread means of storing structured data, and Structured Query Language (SQL) is the standard means for reading from and writing to databases. Databases use multiple tables, linked by well-defined relationships, to store large amounts of data without needless repetition while maintaining the integrity of your data. Moving from spreadsheets and text documents to a structured relational database can be a steep learning curve, but one that will reward you many times over in speed, efficiency and power. Developed using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. Understand and compose a query using SQL Use the SQL syntax to select, sort and filter data Calculate new values from existing data Aggregate data into sums, averages, and other operations Combine data from multiple tables Design and build your own relational databases The course has no prerequisites. training@intersect.org.au SQL
Unix Shell and Command Line Basics

The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of...

Keywords: Unix

Unix Shell and Command Line Basics https://dresa.org.au/materials/unix-shell-and-command-line-basics The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you’ll learn at this course are generally transferable to other Unix environments. Navigate and work with files and directories (folders) Use a selection of essential tools Combine data and tools to build a processing workflow Automate repetitive analysis using the command line The course has no prerequisites. training@intersect.org.au Unix
Data Manipulation in R

R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.

In this workshop, you will learn how to manipulate, explore and get insights...

Keywords: R

Data Manipulation in R https://dresa.org.au/materials/data-manipulation-in-r R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. DataFrame Manipulation using the dplyr package DataFrame Transformation using the tidyr package Either \Learn to Program: R\ or \Learn to Program: R\ and \R for Research\ needed to attend this course. If you already have experience with programming, please check the topics covered in the \Learn to Program: R\ and \R for Research\ courses to ensure that you are familiar with the knowledge needed for this course. training@intersect.org.au R
Learn to Program: R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.

But getting started with R can be...

Keywords: R

Learn to Program: R https://dresa.org.au/materials/learn-to-program-r R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. Introduction to the RStudio interface for programming Basic syntax and data types in R How to load external data into R Creating functions (FUNCTIONS) Repeating actions and analysing multiple data sets (LOOPS) Making choices (IF STATEMENTS – CONDITIONALS) Ways to visualise data in R No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found \here\. training@intersect.org.au R
Python for Research

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data.

This workshop is an introduction to data structures (DataFrames...

Keywords: Python

Python for Research https://dresa.org.au/materials/python-for-research Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data. This workshop is an introduction to data structures (DataFrames using the pandas library) and visualisation (using the matplotlib library) in Python. The targeted audience for this workshop is researchers who are already familiar with the basic concepts in programming such as loops, functions, and conditionals. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. Introduction to Libraries and Built-in Functions in Python Introduction to DataFrames using the pandas library Reading and writing data in DataFrames Selecting values in DataFrames Quick introduction to Plotting using the matplotlib library \Learn to Program: Python\ or any of the \Learn to Program: R\, \Learn to Program: MATLAB\ or \Learn to Program: Julia\, needed to attend this course. If you already have some experience with programming, please check the topics covered in the \Learn to Program: Python\ course to ensure that you are familiar with the knowledge needed for this course. training@intersect.org.au Python
Data Manipulation in Python

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data.

In this workshop, you will explore DataFrames in depth (using...

Keywords: Python

Data Manipulation in Python https://dresa.org.au/materials/data-manipulation-in-python Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. Working with pandas DataFrames Indexing, slicing and subsetting in pandas DataFrames Missing data values Combine multiple pandas DataFrames Either \Learn to Program: Python\ or \Learn to Program: Python\ and \Python for Research\ needed to attend this course. If you already have experience with programming, please check the topics covered in the \Learn to Program: Python\ and \Python for Research\ courses to ensure that you are familiar with the knowledge needed for this course. training@intersect.org.au Python
Version Control with Git

Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there...

Keywords: Git

Version Control with Git https://dresa.org.au/materials/version-control-with-git Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there to answer all your questions while you gain hands on experience in using Git, one of the most popular version control systems available. Join us for this workshop where we cover the fundamentals of version control using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. keep versions of data, scripts, and other files examine commit logs to find which files were changed when restore earlier versions of files compare changes between versions of a file push your versioned files to a remote location, for backup and to facilitate collaboration The course has no prerequisites. training@intersect.org.au Git
R for Social Scientists

R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment.

But getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this...

Keywords: R

R for Social Scientists https://dresa.org.au/materials/r-for-social-scientists R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment. But getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this introductory course comes in. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Data Carpentry. Basic syntax and data types in R RStudio interface How to import CSV files into R The structure of data frames A brief introduction to data wrangling and data transformation How to calculate summary statistics A brief introduction to visualise data No prior experience with programming needed to attend this course. training@intersect.org.au R
R for Research

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.

This workshop is an introduction to data...

Keywords: R

R for Research https://dresa.org.au/materials/r-for-research R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. This workshop is an introduction to data structures (DataFrames) and visualisation (using the ggplot2 package) in R. The targeted audience for this workshop is researchers who are already familiar with the basic concepts in programming such as loops, functions, and conditionals. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. Project Management with RStudio Introduction to Data Structures in R Introduction to DataFrames in R Selecting values in DataFrames Quick introduction to Plotting using the ggplot2 package \Learn to Program: R\ or any of the \Learn to Program: Python\, \Learn to Program: MATLAB\, \Learn to Program: Julia\, needed to attend this course. If you already have some experience with programming, please check the topics covered in the \Learn to Program: R\ course to ensure that you are familiar with the knowledge needed for this course. training@intersect.org.au R
Learn to Program: MATLAB

MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you’re just getting started – with MATLAB and, more generally, with programming?

Nothing beats a hands-on, face-to-face training session to get you past the inevitable syntax errors! ...

Keywords: Matlab

Learn to Program: MATLAB https://dresa.org.au/materials/learn-to-program-matlab MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you’re just getting started – with MATLAB and, more generally, with programming? Nothing beats a hands-on, face-to-face training session to get you past the inevitable syntax errors! So join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. Introduction to the MATLAB interface for programming Basic syntax and data types in MATLAB How to load external data into MATLAB Creating functions (FUNCTIONS) Repeating actions and analysing multiple data sets (LOOPS) Making choices (IF STATEMENTS – CONDITIONALS) Ways to visualise data in MATLAB In order to participate, attendees must have a licensed copy of MATLAB installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found \here\. training@intersect.org.au Matlab