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://zenodo.org/records/14188836
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
Unsworth, Kathryn (orcid: 0000-0002-5407-9987)
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
ARDC Research Software Rights Management Guide
How researchers may license their research software in order to share it with others.
It addresses the types of open‑source licences, and considerations you (as a researcher) should have in deciding which licence to adopt for sharing.
Keywords: Software citation, Software licensing, Software, research software, licence, License, training material
ARDC Research Software Rights Management Guide
https://zenodo.org/records/5003962
https://dresa.org.au/materials/ardc-research-software-rights-management-guide
How researchers may license their research software in order to share it with others.
It addresses the types of open‑source licences, and considerations you (as a researcher) should have in deciding which licence to adopt for sharing.
contact@ardc.edu.au
Australian Research Data Commons
Laughlin, Greg (type: Editor)
Appleyard, Baden (type: Editor)
Martinez, Paula Andrea (type: ProjectLeader)
Software citation, Software licensing, Software, research software, licence, License, training material
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
An open source textbook for research software engineering
Over the past year, a group of Carpentries instructors have been working on an open source textbook called Research Software Engineering with Python. The book is a ready-to-go university semester course aimed at helping learners go from writing code for themselves, to creating tools that help...
Keywords: data skills, software skills, open source, research software, research software engineering, training material
An open source textbook for research software engineering
https://zenodo.org/records/4287860
https://dresa.org.au/materials/an-open-source-textbook-for-research-software-engineering-f275be2a-698e-4e8a-94a4-5b701b26eef8
Over the past year, a group of Carpentries instructors have been working on an open source textbook called Research Software Engineering with Python. The book is a ready-to-go university semester course aimed at helping learners go from writing code for themselves, to creating tools that help their entire field advance. A physical version of the book will be published with Taylor & Francis in early 2021. During the review phase of the publication process, we are seeking feedback on the content and scope of the book from the digital skills training community.
contact@ardc.edu.au
Irving, Damien (orcid: 0000-0003-1258-5002)
data skills, software skills, open source, research software, research software engineering, training material
How can software containers help your research?
This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility.
Software Containers in research are a solution that addresses the challenge of a...
Keywords: containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material
How can software containers help your research?
https://zenodo.org/records/5091260
https://dresa.org.au/materials/how-can-software-containers-help-your-research-ca0f9d41-d83b-463b-a548-402c6c642fbf
This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility.
Software Containers in research are a solution that addresses the challenge of a replicable computational environment and supports reproducibility of research results. Understanding the concept of software containers enables researchers to better communicate their research needs with their colleagues and other researchers using and developing containers.
Watch the video here: https://www.youtube.com/watch?v=HelrQnm3v4g
If you want to share this video please use this:
Australian Research Data Commons, 2021. How can software containers help your research?. [video] Available at: https://www.youtube.com/watch?v=HelrQnm3v4g DOI: http://doi.org/10.5281/zenodo.5091260 [Accessed dd Month YYYY].
contact@ardc.edu.au
Australian Research Data Commons
Martinez, Paula Andrea (type: ProjectLeader)
Sam Muirhead (type: Producer)
The ARDC Communications Team (type: Editor)
The ARDC Skills and Workforce Development Team (type: ProjectMember)
The ARDC eResearch Infrastructure & Services (type: ProjectMember)
The ARDC Nectar Cloud Services team (type: ProjectMember)
containers, software, research, reproducibility, RSE, standard, agility, portable, reusable, code, application, reproducible, standardisation, package, system, cloud, server, version, reliability, program, collaborator, ARDC_AU, training material
ARDC Research Software Rights Management Guide 2021
How researchers may license their research software in order to share it with others.
It addresses the types of open‑source licences, and considerations you (as a researcher) should have in deciding which licence to adopt for sharing.
Keywords: Software citation, Software licensing, Software, research software, licence, License, training material
ARDC Research Software Rights Management Guide 2021
https://zenodo.org/records/5003962
https://dresa.org.au/materials/ardc-research-software-rights-management-guide-d147c836-6ba8-4c76-a258-88e4c293569c
How researchers may license their research software in order to share it with others.
It addresses the types of open‑source licences, and considerations you (as a researcher) should have in deciding which licence to adopt for sharing.
contact@ardc.edu.au
Australian Research Data Commons
Laughlin, Greg (type: Editor)
Appleyard, Baden (type: Editor)
Martinez, Paula Andrea (type: ProjectLeader)
Software citation, Software licensing, Software, research software, licence, License, training material
CheckEM User Guide
CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for...
Keywords: stereo-video, fish, annotation
CheckEM User Guide
https://globalarchivemanual.github.io/CheckEM/articles/manuals/CheckEM_user_guide.html
https://dresa.org.au/materials/checkem-user-guide
CheckEM is an open-source web based application which provides quality control assessments on metadata and image annotations of fish stereo-imagery. It is available at marine-ecology.shinyapps.io/CheckEM. The application can assess a range of sampling methods and annotation data formats for common inaccuracies made whilst annotating stereo imagery. CheckEM creates interactive plots and tables in a graphical interface, and provides summarised data and a report of potential errors to download.
brooke.gibbons@uwa.edu.au
Brooke Gibbons
stereo-video, fish, annotation
EventMeasure Annotation Guide
EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length
Keywords: fish, stereo-video, annotation
EventMeasure Annotation Guide
https://globalarchivemanual.github.io/CheckEM/articles/manuals/EventMeasure_annotation_guide.html
https://dresa.org.au/materials/eventmeasure-annotation-guide
EventMeasure annotation guide for baited remote underwater stereo video systems (stereo-BRUVs) for count and length
tim.langlois@uwa.edu.au
Brooke Gibbons
Tim Langlois
Claude Spencer
fish, stereo-video, annotation
Stereo-video workflows for fish and benthic ecologists
Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range...
Keywords: stereo-video, fish, sharks, habitats
Resource type: tutorial
Stereo-video workflows for fish and benthic ecologists
https://globalarchivemanual.github.io/CheckEM/index.html
https://dresa.org.au/materials/stereo-video-workflows-for-fish-and-benthic-ecologists
Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way.
tim.langlois@uwa.edu.au
Tim Langlois
Brooke Gibbons
Claude Spencer
stereo-video, fish, sharks, habitats
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