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Difficulty level: Beginner 

Fluoroquinolone antibiotics and Aortic Aneurysm or Dissection 

The main objective of this project was to provide education on the use of data translated to the OMOP common data model. We aimed to showcase how the Atlas interface tool could be used to generate evidence for a highly relevant and significant research question. The clinical question that was...

Keywords: OMOP, Aortic Aneurysm, Fluoroquinolone antibiotics

Fluoroquinolone antibiotics and Aortic Aneurysm or Dissection  https://dresa.org.au/materials/fluoroquinolone-antibiotics-and-aortic-aneurysm-or-dissection The main objective of this project was to provide education on the use of data translated to the OMOP common data model. We aimed to showcase how the Atlas interface tool could be used to generate evidence for a highly relevant and significant research question. The clinical question that was used to demonstrate the process revolved around investigating the potential association between the use of fluoroquinolones to treat urinary tract infection and the risk of experiencing aortic aneurysm and dissection within 30 days, 3 months, or 12 months of treatment initiation compared to other commonly used antibiotics. The workshop aimed to describe how data are translated to the OMOP CDM, how cohorts can be derived in these data, how to execute a robust analysis, and lastly, how to interpret the results of the study. Specifically, we described the process of translating Australian medicines dispensing data to the OMOP CDM, including the translation of the Australia Pharmaceutical Benefits Schedule data to the international RxNorm standard vocabulary. The outcome of the project is an on-line training resource that highlights the process of study execution from start to finish. This training package will serve as an exemplar for researchers in Australia to unlock the value of their data that has been translated into the OMOP CDM. The audience for this project was database programmers, researchers, and decision-makers, and all those interested in using data to inform healthcare. Roger Ward, Nicole Pratt Christine Hallinan OMOP, Aortic Aneurysm, Fluoroquinolone antibiotics
Introduction to REDCap at Griffith University

This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases.

Keywords: REDCap, survey instruments

Resource type: tutorial

Introduction to REDCap at Griffith University https://dresa.org.au/materials/introduction-to-redcap-at-griffith-university This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases. y.banens@griffith.edu.au REDCap, survey instruments mbr phd ecr researcher support
Advanced Data Wrangling with OpenRefine

This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine.

Keywords: data skills, data

Resource type: tutorial

Advanced Data Wrangling with OpenRefine https://dresa.org.au/materials/advanced-data-wrangling-with-openrefine This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine. s.stapleton@griffith.edu.au data skills, data mbr phd ecr researcher support professional
Introduction to Data Cleaning with OpenRefine

Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data...

Keywords: data skills, Data analysis

Resource type: tutorial

Introduction to Data Cleaning with OpenRefine https://dresa.org.au/materials/introduction-to-data-cleaning-with-openrefine Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data in a structured or semi-structured format. s.stapleton@griffith.edu.au; Sharron Stapleton data skills, Data analysis mbr phd ecr researcher support professional
Introduction to Unix

A hands-on workshop covering the basics of the Unix command line interface.

Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing...

Keywords: Unix, Command line, Command-line, CLI

Resource type: tutorial

Introduction to Unix https://dresa.org.au/materials/introduction-to-unix A hands-on workshop covering the basics of the Unix command line interface. Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing your way around a command-line interface is highly valuable. This workshop will introduce you to Unix concepts by way of a series of hands-on exercises. This workshop is designed for participants with little or no command-line knowledge. Tools: Standard Unix commands, FileZilla Topic overview: Section 1: Getting started Section 2: Exploring your current directory Section 3: Making and changing directories Section 4: Viewing and manipulating files Section 5: Removing files and directories Section 6: Searching files Section 7: Putting it all together Section 8: Transferring files Tutorial instructions available here: https://www.melbournebioinformatics.org.au/tutorials/tutorials/unix/unix/ For queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au). Find out when we are next running this training as an in-person workshop, by visiting the Melbourne Bioinformaitcs Eventbrite page: https://www.eventbrite.com.au/o/melbourne-bioinformatics-13058846490 For queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au). Unix, Command line, Command-line, CLI ugrad masters mbr phd ecr researcher support professional
Managing Active Research Data

In this train-the-trainer workshop, we will be exploring and discussing methods for active data management.

Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data,...

Keywords: RDM Training, CloudStor, cloud

Resource type: lesson

Managing Active Research Data https://dresa.org.au/materials/managing-active-research-data In this train-the-trainer workshop, we will be exploring and discussing methods for active data management. Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data, and understand safe and secure ways of sharing and storing data. Topics such as cloud storage, collaborative editing, versioning and data sharing will be discussed and demonstrated. Sara King RDM Training, CloudStor, cloud phd support masters ecr researcher
Learn R or Python, generate Species Distribution Models (SDM) or SDM Climate Projections

EcoCommons has a variety of videos, R scripts, and support articles that introduce users to learning how to code in R or Python, how to generate Species Distribution Models (SDMs) or generate SDM climate projections.

We also have a growing number of use cases where users can see and work...

Keywords: Species Distribution Modelling, Beginner R coding, Beginer ecological modelling, Climate projections

Learn R or Python, generate Species Distribution Models (SDM) or SDM Climate Projections https://dresa.org.au/materials/learn-r-or-python-generate-species-distribution-models-sdm-or-sdm-climate-projections EcoCommons has a variety of videos, R scripts, and support articles that introduce users to learning how to code in R or Python, how to generate Species Distribution Models (SDMs) or generate SDM climate projections. We also have a growing number of use cases where users can see and work through examples that highlight the power of bringing data together. support@ecocommons.org.au EcoCommons Species Distribution Modelling, Beginner R coding, Beginer ecological modelling, Climate projections ugrad mbr phd ecr professional
Programming and tidy data analysis in R

A workshop to expand the skill-set of someone who has basic familiarity with R. Covers programming constructs such as functions and for-loops, and working with data frames using the dplyr and tidyr packages. Explains the importance of a "tidy" data representation, and goes through common steps...

Keywords: R, Tidyverse, Programming

Resource type: tutorial

Programming and tidy data analysis in R https://dresa.org.au/materials/programming-and-tidy-data-analysis-in-r A workshop to expand the skill-set of someone who has basic familiarity with R. Covers programming constructs such as functions and for-loops, and working with data frames using the dplyr and tidyr packages. Explains the importance of a "tidy" data representation, and goes through common steps needed to load data and convert it into a tidy form. To be taught as a hands on workshop, typically as two half-days. Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given. Paul Harrison paul.harrison@monash.edu R, Tidyverse, Programming phd ecr researcher
Linear models in R

A workshop on linear models in R. Learning to use linear models provides a foundation for modelling, estimation, prediction, and statistical testing in R. Many commonly used statistical tests can be performed using linear models. Ideas introduced using linear models are applicable to many of the...

Keywords: R statistics

Resource type: tutorial

Linear models in R https://dresa.org.au/materials/linear-models-in-r A workshop on linear models in R. Learning to use linear models provides a foundation for modelling, estimation, prediction, and statistical testing in R. Many commonly used statistical tests can be performed using linear models. Ideas introduced using linear models are applicable to many of the more complicated statistical and machine learning models available in R. To be taught as a hands on workshop, typically as two half-days. Developed by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given. Paul Harrison paul.harrison@monash.edu R statistics phd ecr researcher
Introduction to Jupyter Notebooks

This workshop will introduce you to Jupyter Notebooks, a digital tool that has exploded in popularity in recent years for those working with data.

You will learn what they are, what they do and why you might like to use them. It is an introductory set of lessons for those who are brand new,...

Keywords: jupyter, Introductory, training material, CloudStor, markdown, Python, R

Resource type: tutorial

Introduction to Jupyter Notebooks https://dresa.org.au/materials/introduction-to-jupyter-notebooks This workshop will introduce you to Jupyter Notebooks, a digital tool that has exploded in popularity in recent years for those working with data. You will learn what they are, what they do and why you might like to use them. It is an introductory set of lessons for those who are brand new, have little or no knowledge of coding and computational methods in research. This workshop is targeted at those who are absolute beginners or ‘tech-curious’. It includes a hands-on component, using basic programming commands, but requires no previous knowledge of programming. sara.king@aarnet.edu.au Mason, Ingrid jupyter, Introductory, training material, CloudStor, markdown, Python, R
Heurist Tutorials

A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface.

Keywords: Heurist, Data management, Data visualisation, Digital Humanities, Databasing, website

Resource type: tutorial

Heurist Tutorials https://dresa.org.au/materials/heurist-tutorials A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface. michael.falk@sydney.edu.au Johnson, Ian Osmakov, Artem Heurist, Data management, Data visualisation, Digital Humanities, Databasing, website mbr phd ecr researcher support
Network Know-how and Data Handling Workshop

This workshop is a ‘train-the-trainer’ session that covers topics such as jargon busting, network literacy and data movement solutions. The workshop will also provide a peek at some collaborative research tools such as Jupyter Notebooks and CloudStor. You will learn about networks, integrated...

Keywords: Networks, data handling

Resource type: lesson, presentation

Network Know-how and Data Handling Workshop https://dresa.org.au/materials/network-know-how-and-data-handling-workshop This workshop is a ‘train-the-trainer’ session that covers topics such as jargon busting, network literacy and data movement solutions. The workshop will also provide a peek at some collaborative research tools such as Jupyter Notebooks and CloudStor. You will learn about networks, integrated tools, data and storage and where all these things fit in the researcher’s toolkit. This workshop is targeted at staff who would like to be more confident in giving advice to researchers about the options available to them. It is especially tailored for those with little to no technical knowledge and includes a hands-on component, using basic programming commands, but requires no previous knowledge of programming. Sara King - sara.king@aarnet.edu.au Burke, Melissa (orcid: 0000-0002-5571-8664) Networks, data handling
The Living Book of Digital Skills

The Living Book of Digital Skills (You never knew you needed until now) is a living, open source online guide to 'modern not-quite-technical computer skills' for researchers and the broader academic community.

A collaboration between Australia's Academic Research Network (AARNet) and the...

Keywords: digital skills, digital dexterity, community, open source

Resource type: guide

The Living Book of Digital Skills https://dresa.org.au/materials/the-living-book-of-digital-skills *The Living Book of Digital Skills (You never knew you needed until now)* is a living, open source online guide to 'modern not-quite-technical computer skills' for researchers and the broader academic community. A collaboration between Australia's Academic Research Network (AARNet) and the Council of Australian Librarians (CAUL), this book is the creation of the CAUL Digital Dexterity Champions and their communities. **Contributing to the Digital Skills GitBook** The Digital Skills GitBook is an open source project and like many projects on GitHub we welcome your contributions. If you have knowledge or expertise on one of our [requested topics](https://aarnet.gitbook.io/digital-skills-gitbook-1/requested-articles), we would love you to write an article for the book. Please let us know what you'd like to write about via our [contributor form](https://github.com/AARNet/Digital-Skills-GitBook/issues/new?assignees=sarasrking&labels=contributors&template=contributor-form.yml&title=Contributor+form%3A+). There are other ways to contribute too. For example, you might: * have a great idea for a new topic to be included in one of our chapters (make a new page) * notice some information that’s out-of-date or that could be explained better (edit a page) * come across something in the GitBook that’s not working as it should be (submit an issue) Sara King - sara.king@aarnet.edu.au Sara King Miah de Francesch Emma Chapman Katie Mills Ruth Cameron digital skills, digital dexterity, community, open source ugrad masters mbr phd ecr researcher support
Create a website resume

Written for the Qld Research Bazaar conference 2021, this self paced lesson breaks down how to use Github pages to make a resume, with a simple and basic template to start off with. It discusses how to use Markdown and minimum HTML to customize the template, and offers explanations on how the...

Keywords: personal development, website

Resource type: tutorial, guide

Create a website resume https://dresa.org.au/materials/create-a-website-resume Written for the Qld Research Bazaar conference 2021, this self paced lesson breaks down how to use Github pages to make a resume, with a simple and basic template to start off with. It discusses how to use Markdown and minimum HTML to customize the template, and offers explanations on how the components work together. a.miotto@griffith.edu.au personal development, website
10 Reproducible Research things - Building Business Continuity

The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are...

Keywords: reproducibility, data management

Resource type: tutorial, video

10 Reproducible Research things - Building Business Continuity https://dresa.org.au/materials/9-reproducible-research-things-building-business-continuity The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are replicable due to lack of information on the process. Therefore, reproducibility in research is extremely important. Researchers genuinely want to make their research more reproducible, but sometimes don’t know where to start and often don’t have the available time to investigate or establish methods on how reproducible research can speed up every day work. We aim for the philosophy “Be better than you were yesterday”. Reproducibility is a process, and we highlight there is no expectation to go from beginner to expert in a single workshop. Instead, we offer some steps you can take towards the reproducibility path following our Steps to Reproducible Research self paced program. Video: https://www.youtube.com/watch?v=bANTr9RvnGg Tutorial: https://guereslib.github.io/ten-reproducible-research-things/ a.miotto@griffith.edu.au; s.stapleton@griffith.edu.au; i.jennings@griffith.edu.au; Sharron Stapleton Isaac Jennings reproducibility, data management masters phd ecr researcher support
Data Storytelling

Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert...

Keywords: data storytelling, data visualisation

Data Storytelling https://dresa.org.au/materials/data-storytelling Nowadays, more information created than our audience could possibly analyse on their own! A study by Stanford professor Chip Heath found that during the recall of speeches, 63% of people remember stories and how they made them feel, but only 5% remember a single statistic. So, you should convert your insights and discovery from data into stories to share with non-experts with a language they understand. But how? This tutorial helps you construct stories that incite an emotional response and create meaning and understanding for the audience by applying data storytelling techniques. m.yamaguchi@griffith.edu.au a.miotto@griffith.edu.au data storytelling, data visualisation support masters phd researcher
Basic Linux/Unix commands

A series of eight videos (each between 5 and 10 minutes long) following the content of the Software Carpentry workshop "The Unix Shell".

Sessions 1, 2 and 3 provide instructions on the minimal level of Linux/Unix commands recommended for new...

Keywords: HPC, high performance computer, Unix, Linux, Software Carpentry

Resource type: video, guide

Basic Linux/Unix commands https://dresa.org.au/materials/basic-linux-unix-commands A series of eight videos (each between 5 and 10 minutes long) following the content of the Software Carpentry workshop ["The Unix Shell"](https://swcarpentry.github.io/shell-novice/). Sessions 1, 2 and 3 provide instructions on the minimal level of Linux/Unix commands recommended for new users of HPC. 1 – An overview of how to find out where a user is in the filesystem, list the files there, and how to get help on Unix commands 2 – How to move around the file system and change into other directories 3 – Explains the difference between an absolute and relative path 4 – Overview of how to create new directories, and to create and edit new files with nano 5 – How to use the vi editor to edit files 6 – Overview of file viewers available 7 – How to copy and move files and directories 8 – How to remove files and directories Further details and exercises with solutions can be found on the Software Carpentry "The Unix Shell" page (https://swcarpentry.github.io/shell-novice/) QCIF Training (training@qcif.edu.au) HPC, high performance computer, Unix, Linux, Software Carpentry
Transferring files and data

A short video outlining the basics on how to use FileZilla to establish a secure file transfer protocol (sftp) connection to HPC to use a drag and drop interface to transfer files between the HPC and a desktop computer.

Keywords: sftp, file transfer, HPC, high performance computer

Resource type: video, guide

Transferring files and data https://dresa.org.au/materials/transferring-files-and-data A short video outlining the basics on how to use FileZilla to establish a secure file transfer protocol (sftp) connection to HPC to use a drag and drop interface to transfer files between the HPC and a desktop computer. QCIF Training (training@qcif.edu.au) sftp, file transfer, HPC, high performance computer
Connecting to HPC

A series of three short videos introducing how to use PuTTY to connect from a Windows PC to a secure HPC (high performance computing) cluster.

1 - The very basics on how to establish a connection to HPC.
2 - How to add more specific options for the connection to HPC.
3 - How to save the...

Keywords: HPC, high performance computer, ssh

Resource type: video, guide

Connecting to HPC https://dresa.org.au/materials/connecting-to-hpc A series of three short videos introducing how to use PuTTY to connect from a Windows PC to a secure HPC (high performance computing) cluster. 1 - The very basics on how to establish a connection to HPC. 2 - How to add more specific options for the connection to HPC. 3 - How to save the details and options for a connection for future use. QCIF Training (training@qcif.edu.au) HPC, high performance computer, ssh
Use the Trove Newspaper & Gazette Harvester (web app version)

This video shows how you can use the web app version of the Trove Newspaper & Gazette Harvester to download large quantities of digitised newspaper articles from Trove. Just give it a search from the Trove web interface, and the harvester will...

Keywords: Trove, newspapers, GLAM Workbench, HASS

Resource type: video

Use the Trove Newspaper & Gazette Harvester (web app version) https://dresa.org.au/materials/use-the-trove-newspaper-gazette-harvester-web-app-version-to-download-large-quantities-of-digitised-articles This video shows how you can use the web app version of the [Trove Newspaper & Gazette Harvester](https://glam-workbench.net/trove-harvester/) to download large quantities of digitised newspaper articles from Trove. Just give it a search from the Trove web interface, and the harvester will save the metadata of all the articles from the search results in a CSV (spreadsheet) file for further analysis. You can also save the full text of every article, as well as copies of the articles as JPG images, and even PDFs. The GLAM Workbench is a collection of tools, examples, tutorials, and apps that help you make use of collection data from GLAM organisations (Galleries, Libraries, Archives, and Museums). See: [https://glam-workbench.net/](https://glam-workbench.net/) Tim Sherratt (tim@timsherratt.org and @wragge on Twitter) Trove, newspapers, GLAM Workbench, HASS ugrad masters phd ecr researcher support
Research Data Management (RDM) Online Orientation Module (Macquarie University)

This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify.
The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata,...

Keywords: research data, data management, FAIR data, training

Resource type: quiz, activity, other

Research Data Management (RDM) Online Orientation Module (Macquarie University) https://dresa.org.au/materials/macquarie-university-research-data-management-rdm-online This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify. The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata, benefits of data sharing, licensing, repositories, and best practice including the FAIR principles. Embedded activities and examples help extend learner experience and awareness. The course was designed to assist research students and early career researchers in complying with policies and legislative requirements, understand safe data practices, raise awareness of the benefits of data curation and data sharing (efficiency and impact) and equip them with the required knowledge to plan their data management early in their projects. This course is divided into four sections 1. Crawl - What is Research Data and why care for it? Policy and legislative requirements. The Research Data Life-cycle. Data Management Planning (~30 mins) 2. Walk - Data sensitivity, identifiability, storage, and security (~60 mins) 3. Run - Record keeping, data retention, file naming, folder structures, version control, metadata, data sharing, open data, licences, data repositories, data citation, and ethics (~75 mins) 4. Jump - Best practice FAIR data principles (~45 mins) 5. Fight - Review - a quiz designed to review and reinforce knowledge (~15 mins) https://rise.articulate.com/share/-AWqSPaEI_jTbHwzQHdmQ43R50edrCl0 * *Password: "FAIR" *Password: "FAIR" Any queries or suggestions for course improvement can be directed to the Macquarie University Research Integrity Team: Dr Paul Sou (paul.sou@mq.edu.au) or Dr Shannon Smith (shannon.smith@mq.edu.au). Scorm files can be made available upon request. research data, data management, FAIR data, training
Deep Learning for Natural Language Processing

This workshop is designed to be instructor led and consists of two parts.
Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset.
Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for...

Keywords: Deep learning, NLP, Machine learning

Resource type: presentation, tutorial

Deep Learning for Natural Language Processing https://dresa.org.au/materials/deep-learning-for-natural-language-processing This workshop is designed to be instructor led and consists of two parts. Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset. Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for attendees to train their own RNN. The Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises. This workshop introduces natural language as data for deep learning. We discuss various techniques and software packages (e.g. python strings, RegEx, NLTK, Word2Vec) that help us convert, clean, and formalise text data “in the wild” for use in a deep learning model. We then explore the training and testing of a Recurrent Neural Network on the data to complete a real world task. We will be using TensorFlow v2 for this purpose. datascienceplatform@monash.edu Deep learning, NLP, Machine learning
Visualisation and Storytelling

This workshop explores how data visualisation techniques could be utilised to better understand data and to communicate research efforts and outcomes. The workshop covers a broad range of techniques from simple and static 2D graphics to advanced 3D visualisations in order to provide a broad...

Keywords: data visualisation, storytelling

Resource type: presentation, tutorial

Visualisation and Storytelling https://dresa.org.au/materials/visualisation-and-storytelling This workshop explores how data visualisation techniques could be utilised to better understand data and to communicate research efforts and outcomes. The workshop covers a broad range of techniques from simple and static 2D graphics to advanced 3D visualisations in order to provide a broad overview of the tools available for data analysis, presentation and storytelling. We explore, among others, animated charts and graphs, web visualisation tools such as scrollytellers, and the possibilities of 3D, interactive, and even immersive visualisations. We use real world, concrete examples along the way in order to tangibly illustrate how these visualisations can be created and how viewers perceive and interact with them. We also introduce the various tools and skill sets you would need to be proficient at presenting your data to the world. By the conclusion of this workshop, you would gain familiarity with the various possibilities for presenting your own research data and outcomes. You would have a more intuitive understanding of the strengths and weaknesses of various modes of data visualisation and storytelling, and would have a starting point to obtain the right skill sets relevant to developing your visualisations of choice. datascienceplatform@monash.edu data visualisation, storytelling
Introduction to Deep Learning and TensorFlow

This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise.
Part 1 - Introduction to Deep Learning and TensorFlow
Part 2 - Introduction to Convolutional Neural Networks
The Powerpoints contain...

Keywords: Deep learning, convolutional neural network, tensorflow, Machine learning

Resource type: presentation, tutorial

Introduction to Deep Learning and TensorFlow https://dresa.org.au/materials/introduction-to-deep-learning-and-tensorflow This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise. Part 1 - Introduction to Deep Learning and TensorFlow Part 2 - Introduction to Convolutional Neural Networks The Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises. This workshop is an introduction to how deep learning works and how you could create a neural network using TensorFlow v2. We start by learning the basics of deep learning including what a neural network is, how information passes through the network, and how the network learns from data through the automated process of gradient descent. Workshop attendees would build, train and evaluate a neural network using a cloud GPU (Google Colab). In part 2, we look at image data and how we could train a convolution neural network to classify images. Workshop attendees will extend their knowledge from the first part to design, train and evaluate this convolutional neural network. datascienceplatform@monash.edu Deep learning, convolutional neural network, tensorflow, Machine learning
Use QueryPic to visualise searches in Trove's digitised newspapers (part 2)

This video shows how you can construct and visualise more complex searches for digitised newspaper articles in Trove using QueryPic (see part 1 for the basics). This includes limiting the date range of your query, and changing the time...

Keywords: Trove, GLAM Workbench, visualisation, newspapers, HASS

Resource type: video

Use QueryPic to visualise searches in Trove's digitised newspapers (part 2) https://dresa.org.au/materials/use-querypic-to-visualise-searches-in-trove-s-digitised-newspapers-part-2 This video shows how you can construct and visualise more complex searches for digitised newspaper articles in Trove using [QueryPic](https://glam-workbench.net/trove-newspapers/#querypic) (see part 1 for the basics). This includes limiting the date range of your query, and changing the time scale to zoom in and out of your search results. The GLAM Workbench is a collection of tools, examples, tutorials, and apps that help you make use of collection data from GLAM organisations (Galleries, Libraries, Archives, and Museums). See: https://glam-workbench.net/ Tim Sherratt (tim@timsherratt.org and @wragge on Twitter) Trove, GLAM Workbench, visualisation, newspapers, HASS ugrad masters phd ecr researcher
Use QueryPic to visualise searches in Trove's digitised newspapers (part 1)

This video demonstrates how to use the GLAM Workbench to visualise searches for digitised newspaper articles in Trove. Using the latest version of QueryPic, we can explore the complete result set, showing how the number of matching articles...

Keywords: Trove, GLAM Workbench, visualisation, newspapers, HASS

Resource type: video

Use QueryPic to visualise searches in Trove's digitised newspapers (part 1) https://dresa.org.au/materials/use-querypic-to-visualise-searches-in-trove-s-digitised-newspapers-part-1 This video demonstrates how to use the GLAM Workbench to visualise searches for digitised newspaper articles in Trove. Using the latest version of [QueryPic](https://glam-workbench.net/trove-newspapers/#querypic), we can explore the complete result set, showing how the number of matching articles changes over time. We can even compare queries to visualise changes in language or technology. It's a great way to start exploring the possibilities of GLAM data. The GLAM Workbench is a collection of tools, examples, tutorials, and apps that help you make use of collection data from GLAM organisations (Galleries, Libraries, Archives, and Museums). See: https://glam-workbench.net/ Tim Sherratt (tim@timsherratt.org & @wragge on Twitter) Trove, GLAM Workbench, visualisation, newspapers, HASS ugrad masters ecr researcher
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.

Keywords: training material, FAIR data, research data, data management, FAIR

Resource type: presentation, quiz, activity

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/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. ARDC Contact us: https://ardc.edu.au/contact-us/ training material, FAIR data, research data, data management, FAIR phd ecr researcher support
Software publishing, licensing, and citation

A short presentation for reuse includes speaker notes.

Making software citable using a code repository, an ORCID and a licence.

Cite as
Liffers, Matthias. (2021, July 12). Software publishing, licensing, and citation. Zenodo. https://doi.org/10.5281/zenodo.5091717

Keywords: software citation, software publishing, software registry, software repository, research software

Resource type: presentation

Software publishing, licensing, and citation https://dresa.org.au/materials/software-publishing-licensing-and-citation A short presentation for reuse includes speaker notes. Making software citable using a code repository, an ORCID and a licence. **Cite as** Liffers, Matthias. (2021, July 12). Software publishing, licensing, and citation. Zenodo. https://doi.org/10.5281/zenodo.5091717 ARDC Contact us: https://ardc.edu.au/contact-us/ software citation, software publishing, software registry, software repository, research software phd ecr researcher support
ARDC Guide to making Software Citable

A short guide to making software citable using a code repository, an ORCID and a licence.

Cite as
Liffers, Matthias, & Honeyman, Tom. (2021). ARDC Guide to making software citable. Zenodo. https://doi.org/10.5281/zenodo.5003989

Keywords: software citation, software publishing, software registry, software repository, research software

Resource type: guide

ARDC Guide to making Software Citable https://dresa.org.au/materials/ardc-guide-to-making-software-citable A short guide to making software citable using a code repository, an ORCID and a licence. **Cite as** Liffers, Matthias, & Honeyman, Tom. (2021). ARDC Guide to making software citable. Zenodo. https://doi.org/10.5281/zenodo.5003989 ARDC Contact us: https://ardc.edu.au/contact-us/ software citation, software publishing, software registry, software repository, research software phd ecr researcher support
ARDC Research Data Rights Management Guide

A practical guide for people and organisations working with data, about rights information and licences, and to raise awareness of the implications of not having licences on data.

Who is this for? This guide is primarily directed toward members of the research sector, particularly data rights...

Keywords: research data

Resource type: guide

ARDC Research Data Rights Management Guide https://dresa.org.au/materials/ardc-research-data-rights-management-guide A practical guide for people and organisations working with data, about rights information and licences, and to raise awareness of the implications of not having licences on data. Who is this for? This guide is primarily directed toward members of the research sector, particularly data rights holders users and suppliers. Some general reference is made to characteristics and management of government data, acknowledging that this kind of data can be input to the research process. Government readers should consult their agency’s data management policies, in addition to reading this guide. **Cite as** Australian Research Data Commons. (2019). ARDC Research Data Rights Management Guide. Zenodo. https://doi.org/10.5281/zenodo.5091580 ARDC Contact us: contact@ardc.edu.au research data mbr phd ecr researcher support professional