23 (research data) Things
23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:
- Getting started
- Learn more
- Challenge me
All resources used in the program are online...
Keywords: research data management, training material
23 (research data) Things
https://zenodo.org/records/3955524
https://dresa.org.au/materials/23-research-data-things-793872d2-c221-4cd6-91be-11a313c74b78
23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:
* Getting started
* Learn more
* Challenge me
All resources used in the program are online and free to use and reuse under a Creative Commons Attribution 4.0 International licence. You could use all of them as a self-paced course, or choose components to integrate into your own course.
The 23 things are designed to build knowledge as the program progresses, so if you’re new to the world of research data management, we suggest you start with things 1-3 and then decide where you want to go from there.
These materials supported an international community-based training program delivered in 2016 by the Australian National Data Service.
This release migrates these materials to a GitHub repository for continued maintenance. Some updates were made to material that was outdated.
We welcome contributions and suggestions via GitHub Issue or Pull Request.
contact@ardc.edu.au
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Stokes, Liz (orcid: 0000-0002-2973-5647)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Kelly, Andrew (orcid: 0000-0002-5377-5526)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Levett, Kerry (orcid: 0000-0001-5963-0195)
Brady, Catherine (orcid: 0000-0002-7919-7592)
research data management, 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/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
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...
Databases and SQL
https://intersect.org.au/training/course/sql101
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
The Carpentries
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...
Unix Shell and Command Line Basics
https://intersect.org.au/training/course/unix101
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
The Carpentries
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...
Data Manipulation in R
https://intersect.org.au/training/course/r201
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
The Carpentries
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...
Learn to Program: R
https://intersect.org.au/training/course/r101
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
The Carpentries
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...
Python for Research
https://intersect.org.au/training/course/python110
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
The Carpentries
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...
Data Manipulation in Python
https://intersect.org.au/training/course/python201
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
The Carpentries
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...
Version Control with Git
https://intersect.org.au/training/course/git101
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
The Carpentries
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...
R for Social Scientists
https://intersect.org.au/training/course/r103
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
The Carpentries
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...
R for Research
https://intersect.org.au/training/course/r110
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
The Carpentries
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! ...
Learn to Program: MATLAB
https://intersect.org.au/training/course/matlab101
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
The Carpentries
Matlab
