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166 material found

Astronomy Data And Computing Services - Upskilling the Australian astronomy community

The Astronomy Data And Computing Services (ADACS) initiative has been working with the Australian astronomy community for just over 3 years now. Our vision is to deliver astronomy-focused training, support and expertise to maximise the scientific return on investments in astronomical data &...

Keywords: astronomy, data skills, eresearch skills, skills, computational skills, training, skills gaps, astronomy-focused training, training material

Astronomy Data And Computing Services - Upskilling the Australian astronomy community https://dresa.org.au/materials/astronomy-data-and-computing-services-upskilling-the-australian-astronomy-community The Astronomy Data And Computing Services (ADACS) initiative has been working with the Australian astronomy community for just over 3 years now. Our vision is to deliver astronomy-focused training, support and expertise to maximise the scientific return on investments in astronomical data & computing infrastructure. During these last 3 years, we have delivered dozens of face-to-face, hands-on workshops and created several hours worth of online tutorial materials. This talk will focus on our journey to deliver this computational skills training to the community, exploring how we chose different delivery pathways and content, based both on community input as well as our professional expertise and understanding of existing skill gaps. Most importantly we will discuss our plans for the future and how we are working on actively including the community in developing new training material beyond the usual skills survey. Come along to this talk if you would like to hear about a national effort to deliver computational skills training and would like to know more about potential new avenues to provide just-in-time training and how to collaborate with ADACS.  contact@ardc.edu.au astronomy, data skills, eresearch skills, skills, computational skills, training, skills gaps, astronomy-focused training, training material
Accelerating skills development in Data science and AI at scale

At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...

Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material

Accelerating skills development in Data science and AI at scale https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale At the Monash Data Science and AI  platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally. The talk will also cover our approach as outlined below •        Combined survey of gaps in skills and trainings for Data science and AI •        Provide seats to partners •        Share associate instructors/helpers/volunteers •        Develop combined training materials •        Publish a repository of open source trainings •        Train the trainer activities •        Establish a network of volunteers to deliver trainings at their local regions Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community. Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together. contact@ardc.edu.au AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Opening the Skills Summit - introduction and brief overview of ARDC

Introduction and welcome to the Skills Summit, a brief overwiew of ARDC, its purpose, mission and activities, including ARDC's role in skills development.

Keywords: ARDC, Skills Development, Skills Summit, training material

Opening the Skills Summit - introduction and brief overview of ARDC https://dresa.org.au/materials/opening-the-skills-summit-introduction-and-brief-overview-of-ardc Introduction and welcome to the Skills Summit, a brief overwiew of ARDC, its purpose, mission and activities, including ARDC's role in skills development. contact@ardc.edu.au ARDC, Skills Development, Skills Summit, training material
Training resources for sharing and reuse

This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis...

Keywords: FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance

Training resources for sharing and reuse https://dresa.org.au/materials/training-resources-for-sharing-and-reuse This presentation outlines the work completed during a consultancy for ARDC by Dr Paula Martinez to develop new and publish existing national skills materials for reuse by the sector. She was responsible for the work package targeted to co-develop national skills materials with a strong emphasis on sharing and reuse. This was a very collaborative project with the opportunity to work with different target audiences, topics and support expertise. To accommodate for a short timeline. We defined the scope to six topics. 1) Containers in Research 2) Data Governance 3) Software citation and Licensing 4) FAIR Data 101 5) Metadata for Training Materials 6) Machine Learning Resources. You can watch the video on YouTube here: https://youtu.be/10Yv_BFa-mw contact@ardc.edu.au FAIR training material, training material, guides, software citation, software publishing, containers, software licensing, training materials checklist, research data governance
Time to fill the gaps: Building out a national training inventory

 

This community discussion seeks to bring together the instructors and facilitators tasked with upskilling researchers and support staff. While this collective dialogue among instructors is not new, what is new is the traction that various groups are getting.

The newly formed group of...

Keywords: training inventory, training registry, national skills initiatives, training material

Time to fill the gaps: Building out a national training inventory https://dresa.org.au/materials/time-to-fill-the-gaps-building-out-a-national-training-inventory   This community discussion seeks to bring together the instructors and facilitators tasked with upskilling researchers and support staff. While this collective dialogue among instructors is not new, what is new is the traction that various groups are getting. The newly formed group of eResearch support staff gathered by the Melbourne Data Analytics Platform (MDAP) and Sydney Informatics Hub (SIH) is one such group, as is the Lightweight Working Group (LWG): Researcher digital skills training data for enabling digital infrastructure use, spearheaded by University of Melbourne’s David Flanders during the pre-Skills Summit discussions. In this session we seek to build on the momentum, by including a hands-on working session. Participants are asked to come with information to share and questions they seek to answer. During the first half of this session, attendees will populate a public document with shareable training details. The goal is to at least double the size of the new cross-institutional national training collection started by the LWG. The second half of this session will be to ask questions to arrive at next steps. What do we need to do to continue building out this national training inventory and who will be in charge of maintaining and distributing the archive? What platforms exist and are used to capture training data and material and make it readily maintainable and findable? Can the material be reused and how do we recognise and capture re-use? Do we know about how to apply a license to our materials for appropriate reuse or do we need guidance? While there will likely be more questions than these, one question has been answered. When can we move from talking to doing? That time is now. contact@ardc.edu.au training inventory, training registry, national skills initiatives, training material
Persistent Identifiers for Research: a talk to the Australasian DMP Interest Group

ARDC's Data Management Planning Interest Group hosted a meetup on persistent identifiers and data management planning infrastructure on 17 June 2021. These slides accompanied Siobhann McCafferty's talk on PIDs infrastructure, RAiD and the Instruments for Identifiers Australasia Interest Group...

Keywords: DMP, data management plans, infrastructure, research support, persistent identifiers, research data management, research infrastructure, training material

Persistent Identifiers for Research: a talk to the Australasian DMP Interest Group https://dresa.org.au/materials/persistent-identifiers-for-research-a-talk-to-the-australasian-dmp-interest-group ARDC's Data Management Planning Interest Group hosted a meetup on persistent identifiers and data management planning infrastructure on 17 June 2021. These slides accompanied Siobhann McCafferty's talk on PIDs infrastructure, RAiD and the Instruments for Identifiers Australasia Interest Group (I4IOZ). contact@ardc.edu.au DMP, data management plans, infrastructure, research support, persistent identifiers, research data management, research infrastructure, training material
eResearch Services and Capabilities

Over the last two years, the Federation for the Advancement of Victorian eResearch (FAVeR) has been working towards some understanding of the eResearch roles space, leading to the establishment of a project called 'Advancing the professionalisation of our eResearch workforce'.

The goal of this...

Keywords: skills, training, digitally skilled workforce, eresearch services, capabilities, training material

eResearch Services and Capabilities https://dresa.org.au/materials/eresearch-services-and-capabilities Over the last two years, the Federation for the Advancement of Victorian eResearch (FAVeR) has been working towards some understanding of the eResearch roles space, leading to the establishment of a project called 'Advancing the professionalisation of our eResearch workforce'. The goal of this project is to provide a common understanding of the eResearch capabilities, from which appropriate skill sets can be derived for positions or teams. In this presentation we will share an overview of the project, including: FAVeR and the APeRW Working Group, the eResearch Value Proposition and Chain, draft eResearch Services, and example capabilities. In addition, we will share the early results of a planned community consultation, which has been proposed as a ‘Birds of a Feather’ session at eResearch Australasia 2020. This consultation aims to elicit feedback, from the broader eResearch community, on the following questions: ● Are there other aspects of eResearch Services? What falls outside the scope of the service and capabilities descriptions? ● Is there a priority between eResearch Services? e.g. Mandatory, optional, and dependencies. What’s required when for deploying an e/Digital Research support unit. What’s the priority order and what’s the minimum required? ● Is there a distinction between general and specialised capabilities? e.g. Are there cross service eResearch capabilities. This presentation will be of interest primarily to Decision-makers and managers and Digitally focussed research support professionals. contact@ardc.edu.au skills, training, digitally skilled workforce, eresearch services, capabilities, training material
OECD Report - Building digital workforce capacity and skills for data-intensive science (2020)

 

As a lead contributor to the OECD's Building Digital Workforce Capacity and Skills for Data-Intensive Science (2020) report, Dr Michelle Barker outlines in this presentation the goal of the report, i.e. to make recommendations to policy makers on how to facilitate the digital workforce...

Keywords: international skills initiatives, skills, training, OECD, EOSC, Capability building, Skills uplift, skills development, digital skilled workforce, training material

OECD Report - Building digital workforce capacity and skills for data-intensive science (2020) https://dresa.org.au/materials/oecd-report-building-digital-workforce-capacity-and-skills-for-data-intensive-science-2020   As a lead contributor to the OECD's Building Digital Workforce Capacity and Skills for Data-Intensive Science (2020) report, Dr Michelle Barker outlines in this presentation the goal of the report, i.e. to make recommendations to policy makers on how to facilitate the digital workforce capacity needed for data-intensive science, based on analysis of best practice. The presentation highlights: - Digital workforce capacity and COVID19: the importance of digital skills, the need for shared access to open data, software and code, and the shortfall in skills to enable a comprehensive response to such emergencies - The ongoing need for a digital skilled workforce for data-intensive science - Five focus areas in the report include: 1. Enablers for digital workforce capacity development 2. Defining needs: digital skills, frameworks and roles 3. Provision of training 4. Community development 5. Career paths and reward structures - Recommendations for actors incl. universities, national or regional governments contact@ardc.edu.au international skills initiatives, skills, training, OECD, EOSC, Capability building, Skills uplift, skills development, digital skilled workforce, training material
Software publishing, licensing and citation

This presentation was part of an “Orientation to ARDC services and expertise” series, specifically aimed at people involved in one of the ARDC co-investment projects commencing early 2021. In addition to co-investment of money, ARDC contributes expertise and services in a range of areas: research...

Keywords: software, code, Repositories, code sharing, training material

Software publishing, licensing and citation https://dresa.org.au/materials/software-publishing-licensing-and-citation-432694d3-0366-45bb-ad49-84ffd7587dcb This presentation was part of an “Orientation to ARDC services and expertise” series, specifically aimed at people involved in one of the ARDC co-investment projects commencing early 2021. In addition to co-investment of money, ARDC contributes expertise and services in a range of areas: research vocabularies, persistent identifiers, data discovery catalogues, metadata issues, licensing, governance, underpinning infrastructure (e.g. Nectar Research Cloud) and more. ARDC can also connect projects to national and international communities and initiatives trying to solve common challenges and outline best practice. This session explained why and how to publish, licence and cite software. A video recording of this session can also be found on ARDC's YouTube channel: https://youtu.be/l2acLeuF_QE contact@ardc.edu.au software, code, Repositories, code sharing, training material
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: data, rights, management, licence, licensing, research, policy, guide, training material

ARDC Research Data Rights Management Guide https://dresa.org.au/materials/ardc-research-data-rights-management-guide-a5c12e9a-672b-4a42-b9d1-e1315d733aae 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. contact@ardc.edu.au Laughlin, Greg (type: Editor) Appleyard, Baden (type: Editor) data, rights, management, licence, licensing, research, policy, guide, training material
Institutional Research Data Management Policies and Procedures

This is a guide for those developing or updating policies and procedures related to the management of research data as an institutional asset.
The guide covers:
- Why have a research data management policy or policies?
- Possible approaches to constructing a research data policy suite
- Examples...

Keywords: research data, research data management, institutional data policies, institutional data procedures, institutional research data management, RDM, Australia, Australian research institutions, ARDC, Australian Research Data Commons, training material

Institutional Research Data Management Policies and Procedures https://dresa.org.au/materials/institutional-research-data-management-policies-and-procedures This is a guide for those developing or updating policies and procedures related to the management of research data as an institutional asset. The guide covers: - Why have a research data management policy or policies? - Possible approaches to constructing a research data policy suite - Examples of data management policies - Key topics to include in a research data policy suite - Checklist for a Research Data Management Policy for Australian Universities / Institutions contact@ardc.edu.au research data, research data management, institutional data policies, institutional data procedures, institutional research data management, RDM, Australia, Australian research institutions, ARDC, Australian Research Data Commons, training material
ML4AU: Trainings, trainers and building an ML community

This lightning talk provides an update on the current state of machine lerning training activities. Additionally, the talk will introduce the training portal on the ML4AU website, which has been created to address some of the challenges faced by the trainer community.

You can watch the YouTube...

Keywords: machine learning, training, skills, community of practice, trainers, training material

ML4AU: Trainings, trainers and building an ML community https://dresa.org.au/materials/ml4au-trainings-trainers-and-building-an-ml-community This lightning talk provides an update on the current state of machine lerning training activities. Additionally, the talk will introduce the training portal on the ML4AU website, which has been created to address some of the challenges faced by the trainer community. You can watch the YouTube video here: https://youtu.be/cQS0guC5_Cg contact@ardc.edu.au machine learning, training, skills, community of practice, trainers, training material
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://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 Laughlin, Greg (type: Editor) Appleyard, Baden (type: Editor) Martinez, Paula Andrea (type: ProjectLeader) Software citation, Software licensing, Software, research software, licence, License, training material
Data Management at CLEX

In this presentation, Paula Petrelli outlines the opportunities and challenges of data management for climate science, and how she implemented DMPOnline to facilitate better workflows for publishing research data. This talk was presented to the Australasian Data Management Plans Interest Group on...

Keywords: Data management, DMP, Data management planning, DMP Online, Climate research, Data publishing, DOIs, training material

Data Management at CLEX https://dresa.org.au/materials/data-management-at-clex In this presentation, Paula Petrelli outlines the opportunities and challenges of data management for climate science, and how she implemented DMPOnline to facilitate better workflows for publishing research data. This talk was presented to the Australasian Data Management Plans Interest Group on 19 August 2021. The group is hosted by Liz Stokes and meets every two months to discuss data management planning infrastructure. contact@ardc.edu.au Stokes, Liz (type: Other) Data management, DMP, Data management planning, DMP Online, Climate research, Data publishing, DOIs, 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://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 training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
ARDC Guide to making software citable

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

Keywords: Software citation, Software publishing, Software registries, Software repositories, Research software, training material

ARDC Guide to making software citable https://dresa.org.au/materials/ardc-guide-to-making-software-citable-d859df17-e9cf-4a7a-9a63-dfea5d561445 A short guide to making software citable using a code repository, an ORCID and a licence. contact@ardc.edu.au Martinez, Paula Andrea (type: ProjectLeader) Software citation, Software publishing, Software registries, Software repositories, Research software, training material
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
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...

Keywords: reproducibility, data management

Resource type: tutorial, video

9 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/Reproducible-Research-Things/ a.miotto@griffith.edu.au reproducibility, data management support masters phd researcher
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
Porting the multi-GPU SELF-Fluids code to HIPFort

In this presentation by Dr. Joseph Schoonover of Fluid Numerics LLC, Joe shares their experience with the porting process for SELF-Fluids from multi-GPU CUDA-Fortran to multi-GPU HIPFort.

The presentation covers the design principles and roadmap for SELF and the strategy to port from...

Keywords: AMD, GPUs, supercomputer, supercomputing

Resource type: presentation

Porting the multi-GPU SELF-Fluids code to HIPFort https://dresa.org.au/materials/porting-the-multi-gpu-self-fluids-code-to-hipfort In this presentation by Dr. Joseph Schoonover of Fluid Numerics LLC, Joe shares their experience with the porting process for SELF-Fluids from multi-GPU CUDA-Fortran to multi-GPU HIPFort. The presentation covers the design principles and roadmap for SELF and the strategy to port from Nvidia-only platforms to AMD & Nvidia GPUs. Also discussed are the hurdles encountered along the way and considerations for developing multi-GPU accelerated applications in Fortran. SELF is an object-oriented Fortran library that supports the implementation of Spectral Element Methods for solving partial differential equations. SELF-Fluids is an implementation of SELF that solves the compressible Navier Stokes equations on CPU only and GPU accelerated compute platforms using the Discontinuous Galerkin Spectral Element Method. The SELF API is designed based on the assumption that SEM developers and researchers need to be able to implement derivatives in 1-D and divergence, gradient, and curl in 2-D and 3-D on scalar, vector, and tensor functions using spectral collocation, continuous Galerkin, and discontinuous Galerkin spectral element methods. The presentation discussion is placed in context of the Exascale era, where we're faced with a zoo of available compute hardware. Because of this, SELF routines provide support for GPU acceleration through AMD’s HIP and support for multi-core, multi-node, and multi-GPU platforms with MPI. training@pawsey.org.au AMD, GPUs, supercomputer, supercomputing
Embracing new solutions for in-situ visualisation

This PPT was used by Jean Favre, senior visualisation software engineer at CSCS, the Swiss National Supercomputing Centre during his presentation at P'Con '21 (Pawsey's first PaCER Conference).

This material discusses the upcoming release of ParaView v5.10, a leading scientific visualisation...

Keywords: ParaView, GPUs, supercomputer, supercomputing, visualisation, data visualisation

Resource type: presentation

Embracing new solutions for in-situ visualisation https://dresa.org.au/materials/embracing-new-solutions-for-in-situ-visualisation This PPT was used by Jean Favre, senior visualisation software engineer at CSCS, the Swiss National Supercomputing Centre during his presentation at P'Con '21 (Pawsey's first PaCER Conference). This material discusses the upcoming release of ParaView v5.10, a leading scientific visualisation application. In this release ParaView consolidates its implementation of the Catalyst API, a specification developed for simulations and scientific data producers to analyse and visualise data in situ. The material reviews some of the terminology and issues of different in-situ visualisation scenarios, then reviews early Data Adaptors for tight-coupling of simulations and visualisation solutions. This is followed by an introduction of Conduit, an intuitive model for describing hierarchical scientific data. Both ParaView-Catalyst and Ascent use Conduit’s Mesh Blueprint, a set of conventions to describe computational simulation meshes. Finally, the materials present CSCS’ early experience in adopting ParaView-Catalyst and Ascent via two concrete examples of instrumentation of some proxy numerical applications. training@pawsey.org.au ParaView, GPUs, supercomputer, supercomputing, visualisation, data visualisation
HPC file systems and what users need to consider for appropriate and efficient usage

Three videos on miscellaneous aspects of HPC usage - useful reference for new users of HPC systems.

1 – General overview of different file systems that might be available on HPC. The video goes through shared file systems such as /home and /scratch, local compute node file systems (local...

Keywords: HPC, high performance computer, File systems

Resource type: video, presentation

HPC file systems and what users need to consider for appropriate and efficient usage https://dresa.org.au/materials/hpc-file-systems-and-what-users-need-to-consider-for-appropriate-and-efficient-usage Three videos on miscellaneous aspects of HPC usage - useful reference for new users of HPC systems. 1 – General overview of different file systems that might be available on HPC. The video goes through shared file systems such as /home and /scratch, local compute node file systems (local scratch or $TMPDIR) and storage file system. It outlines what users need to consider if they wish to use any of these in their workflows. 2 – Overview of the different directories that might be present on HPC. These could include /home, /scratch, /opt, /lib and lib64, /sw and others. 3 – Overview of the Message-of-the-day file and the message that is displayed to users every time they log in. This displays info about general help and often current problems or upcoming outages. QCIF Training (training@qcif.edu.au) HPC, high performance computer, File systems
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
Getting Started with Deep Learning

This lecture provides a high level overview of how you could get started with developing deep learning applications. It introduces deep learning in a nutshell and then provides advice relating to the concepts and skill sets you would need to know and have in order to build a deep learning...

Keywords: Deep learning, Machine learning

Resource type: presentation

Getting Started with Deep Learning https://dresa.org.au/materials/getting-started-with-deep-learning This lecture provides a high level overview of how you could get started with developing deep learning applications. It introduces deep learning in a nutshell and then provides advice relating to the concepts and skill sets you would need to know and have in order to build a deep learning application. The lecture also provides pointers to various resources you could use to gain a stronger foothold in deep learning. This lecture is targeted at researchers who may be complete beginners in machine learning, deep learning, or even with programming, but who would like to get into the space to build AI systems hands-on. datascienceplatform@monash.edu Deep learning, Machine learning