7 Steps towards Reproducible Research
This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.
We will also examine how Reproducible Research builds business continuity...
Keywords: reproducibility, Reproducibility, reproducible workflows
Resource type: full-course, tutorial
7 Steps towards Reproducible Research
https://amandamiotto.github.io/ReproducibleResearch/
https://dresa.org.au/materials/7-steps-towards-reproducible-research
This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.
We will also examine how Reproducible Research builds business continuity into your research group, how the culture in your institute ecosystem can affect Reproducibility and how you can identify and address risks to your knowledge.
The workshop can be used as self-paced or as an instructor
Amanda Miotto - a.miotto@griffith.edu.au
Amanda Miotto
reproducibility, Reproducibility, reproducible workflows
phd
support
Sharing a Trove List as a CollectionBuilder exhibition
You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. CollectionBuilder creates online exhibitions using static web...
Keywords: Trove, Trove List, CollectionBuilder, collection, GLAM Workbench, exhibition, HASS
Resource type: tutorial
Sharing a Trove List as a CollectionBuilder exhibition
https://tdg.glam-workbench.net/pathways/collections/collectionbuilder.html
https://dresa.org.au/materials/sharing-a-trove-list-as-a-collectionbuilder-exhibition
You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. [CollectionBuilder](https://collectionbuilder.github.io/) creates online exhibitions using static web technologies. But how do you get your List data from Trove into CollectionBuilder?
This tutorial from the Trove Data Guide walks through the complete process step-by-step.
Tim Sherratt (tim@timsherratt.au)
Tim Sherratt
ARDC Community Data Lab
Trove, Trove List, CollectionBuilder, collection, GLAM Workbench, exhibition, HASS
Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps
Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP,...
Keywords: Trove, maps, Gazetteer of Historical Australian Placenames (GHAP), GLAM Workbench, geospatial, HASS
Resource type: tutorial
Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps
https://tdg.glam-workbench.net/pathways/geospatial/maps-to-ghap.html
https://dresa.org.au/materials/create-a-layer-in-the-gazetteer-of-historical-australian-placenames-using-metadata-from-trove-s-digitised-maps
Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP, but how do you get the data from Trove in a format that can be uploaded as a layer?
This tutorial from the Trove Data Guide walks through the complete process step-by-step.
Tim Sherratt (tim@timsherratt.au)
Tim Sherratt
ARDC Community Data Lab
Trove, maps, Gazetteer of Historical Australian Placenames (GHAP), GLAM Workbench, geospatial, HASS
Comparing manuscript collections from Trove in Mirador
You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The Mirador viewer can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get...
Keywords: Trove, images, manuscripts, GLAM Workbench, IIIF, HASS, Mirador
Resource type: tutorial
Comparing manuscript collections from Trove in Mirador
https://tdg.glam-workbench.net/pathways/images/mirador.html
https://dresa.org.au/materials/comparing-manuscript-collections-in-mirador
You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The [Mirador viewer](https://projectmirador.org/) can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get manuscript collections from Trove to Mirador?
This tutorial from the Trove Data Guide walks through the complete process step-by-step.
Tim Sherratt (tim@timsherratt.au)
Tim Sherratt
ARDC Community Data Lab
Trove, images, manuscripts, GLAM Workbench, IIIF, HASS, Mirador
Working with a Trove collection in Tropy
You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. Tropy is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into...
Keywords: Trove, images, Tropy, IIIF, GLAM Workbench, HASS
Resource type: tutorial
Working with a Trove collection in Tropy
https://tdg.glam-workbench.net/pathways/images/tropy.html
https://dresa.org.au/materials/working-with-a-trove-collection-in-tropy
You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. [Tropy](https://tropy.org/) is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into Tropy?
This tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step.
Tim Sherratt (tim@timsherratt.au)
Tim Sherratt
ARDC Community Data Lab
Trove, images, Tropy, IIIF, GLAM Workbench, HASS
Analysing keywords in Trove’s digitised newspapers
You want to explore differences in language use across a collection of digitised newspaper articles. The Australian Text Analytics Platform provides a Keywords Analysis tool that helps you...
Keywords: text analysis, Australian Text Analytics Platform (ATAP), Trove, GLAM Workbench, Trove Newspaper and Gazette Harvester, newspapers, HASS
Resource type: tutorial
Analysing keywords in Trove’s digitised newspapers
https://tdg.glam-workbench.net/pathways/text/newspapers-keywords.html
https://dresa.org.au/materials/analysing-keywords-in-trove-s-digitised-newspapers
You want to explore differences in language use across a collection of digitised newspaper articles. The [Australian Text Analytics Platform](https://www.atap.edu.au/) provides a [Keywords Analysis tool](https://github.com/Australian-Text-Analytics-Platform/keywords-analysis) that helps you examine whether particular words are over or under-represented across collections of text. But how do get data from Trove’s newspapers to the keyword analysis tool?
This tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step.
Tim Sherratt (tim@timsherratt.au)
Tim Sherratt
ARDC Community Data Lab
text analysis, Australian Text Analytics Platform (ATAP), Trove, GLAM Workbench, Trove Newspaper and Gazette Harvester, newspapers, HASS
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
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/record/3955524
https://dresa.org.au/materials/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 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/record/5094034
https://dresa.org.au/materials/ardc-fair-data-101-self-guided-bba41a59-8479-4f4f-b9ee-337b9eb294bf
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub.
contact@ardc.edu.au
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Martinez, Paula A. (orcid: 0000-0002-8990-1985)
Simons, Natasha (orcid: 0000-0003-0635-1998)
Russell, Keith (orcid: 0000-0001-5390-2719)
McCafferty, Siobhann (orcid: 0000-0002-2491-0995)
Ferrers, Richard (orcid: 0000-0002-2923-9889)
McEachern, Steve (orcid: 0000-0001-7848-4912)
Barlow, Melanie (orcid: 0000-0002-3956-5784)
Brady, Catherine (orcid: 0000-0002-7919-7592)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Quiroga, Maria del Mar (orcid: 0000-0002-8943-2808)
training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
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://amandamiotto.github.io/ResumeLesson/HowIMadeThis
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
Amanda Miotto
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://guereslib.github.io/ten-reproducible-research-things/
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;
Amanda Miotto
Julie Toohey
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://griffithunilibrary.github.io/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
Masami Yamaguchi
Amanda Miotto
Brett Parker
data storytelling, data visualisation
support
masters
phd
researcher