[{"id":350,"title":"ARDC Digital Research Skills Strategy Tool","url":"https://staging.dresa.org.au/materials/ardc-digital-research-skills-strategy-tool.json","description":"This is a decision tool to help you determine components of a digital research skills strategy.\nWhen you create a skills strategy, you need to work out:\n\nWhich people\nNeed which skills\nAt what level\nDelivered how\n\nThis tool helps you:\n\nCreate typical user roles that outline groups who need distinct clusters of skills;\nDescribe training preferences and pain points for each role;\nIdentify which skills in the ARDC Digital Research Capabilities and Skills Framework each role needs;\nNominate the level of competency each role requires; and\nMap out the training approach for each skill.\n\nThe Skilled Workforce Development Team of the Australian Research Data Commons developed this tool to support the ARDC mission to accelerate Australian research and innovation.","doi":"10.5281/zenodo.16892111","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":349,"title":"Submitting a Data Request to Health Data Australia: Documentation for Data Requesters","url":"https://staging.dresa.org.au/materials/submitting-a-data-request-to-health-data-australia-documentation-for-data-requesters.json","description":"This documentation is a supplementary resource for researchers submitting a formal request for access to a dataset listed on the Health Data Australia (HDA) platform. This was developed as part of a work package for Health Studies Australian National Data Asset.","doi":"10.5281/zenodo.15725594","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":348,"title":"Secondary Use of Clinical Trials Data in Health Research: A Practical Guide","url":"https://staging.dresa.org.au/materials/secondary-use-of-clinical-trials-data-in-health-research-a-practical-guide-4be3f4e3-4c86-4b57-b686-60a8fe6483cf.json","description":"This document presents a theoretical framework for the use of clinical trials and other health data for secondary research purposes, which was derived from research papers, consultation with stakeholders and the research community.  \nFour overall scenarios for data reuse were identified; scenario 1: evidence synthesis, scenario 2: secondary analyses, scenario 3: reproducibility, replication and validation, and scenario 4: education and methods development.\nView an online version of this pdf document on the ARDC website.","doi":"10.5281/zenodo.14984904","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":347,"title":"ARDC Digital Research Capabilities and Skills Framework: The Framework and Its Components","url":"https://staging.dresa.org.au/materials/ardc-digital-research-capabilities-and-skills-framework-the-framework-and-its-components.json","description":"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. \nThe 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.","doi":"10.5281/zenodo.14188836","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":346,"title":"Ten Simple Rules for Researchers: Upskilling for a Rapidly Evolving Workforce","url":"https://staging.dresa.org.au/materials/ten-simple-rules-for-researchers-upskilling-for-a-rapidly-evolving-workforce.json","description":"The following recommendations were inspired by the Australian Research Data Commons (ARDC) Digital Research Skills Summit 2023, that brought together Researchers, Learning Designers, Skills Trainers, and Librarians in productive discussions on how to run effective researcher skills training. These rules outline how to think about skills learning for researchers, plan training sessions, and efficiently maximize learning. We offer recommendations on how to design and develop learner-centered training programs (Rules 1 and 2), foster outreach, and connect with trainer communities (Rules 3 and 4). We then provide tips to manage and optimize training (Rules 5, 6, and 7), and conclude with valuable insights on preparing for uncertainty and the importance of post-training operations and continued learning (Rules 8, 9, and 10).","doi":"10.5281/zenodo.13989494","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":345,"title":"Randomised Controlled Trials with REDCap","url":"https://staging.dresa.org.au/materials/randomised-controlled-trials-with-redcap.json","description":"REDCap is a powerful and extensible application for managing and running longitudinal data collection activities. In this course, learn how to manage a Randomised Controlled Trial using REDCap, including the randomisation module, adverse event reporting and automated participant withdrawals. This course will introduce some of REDCap’s more advanced features for running randomised trials, and builds on the material taught in REDCAP201 – Longitudinal Trials with REDCap.\n\n- Create Data Access Groups (DAGs) and assign users to manage trial sites\n- Build randomisation allocation table \n- Enable and implement participant randomisation module\n- Design an adverse reporting system using Automated Survey Invitations and Alerts\n- Create an automated participant withdrawal process\n- Customise record dashboards\n\nLearners should have a solid understanding of REDCap and be familiar with the content of [Data Capture and Surveys with REDCap](https://intersectaustralia.github.io/training/REDCAP101/) and [Longitudinal Trials with REDCap](https://intersectaustralia.github.io/training/REDCAP201/).","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":335,"title":"Data Fluency: a community of practice supporting a digitally skilled workforce","url":"https://staging.dresa.org.au/materials/data-fluency-a-community-of-practice-supporting-a-digitally-skilled-workforce-5910b4fe-00a6-44f2-a94f-b8d2b17dec62.json","description":"This presentation showcases the impact of the Monash Data Fluency Community of Practice upon digitally skilled Graduate Research students involved as learners and instructors in the program. The strong focus on building community to complement training, has fostered an environment of learning, networking and sharing of expertise. Hear what the Graduate research students have to say about the value of skills training and how it has impacted their research; how the community has enabled them to network with a broad range of researchers and affiliate partner groups they would not ordinarily be in contact with; how their research journey has been enhanced by working as part of a multi-disciplinary team, as well as sharpening their teaching skills.\nThe rapid refocus from face - face to online delivery, as a result of the pandemic, highlights the importance of the multi-faceted online approach including workshops, drop-in sessions, SLACK chat and online learning resources. As a result of the shift to online, the range of strategic external partner/affiliate groups has extended and demand for workshops and drop-ins has increased.  Learn how the instructors have altered their pedagogical approach to engage workshop and drop-in participants; how they have overcome some of the challenges of facilitating in an online environment; and how this is preparing them to become part of a digitally skilled workforce.","doi":"10.5281/zenodo.4287752","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":334,"title":"European Open Science Cloud (EOSC) skills \u0026 training working group","url":"https://staging.dresa.org.au/materials/european-open-science-cloud-eosc-skills-training-working-group-ebd60580-5cd1-4029-8f79-ea0568dadc7f.json","description":"European Open Science Cloud (EOSC) skills \u0026amp; training working group","doi":"10.5281/zenodo.4289348","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":336,"title":"OECD Report - Building digital workforce capacity and skills for data-intensive science (2020)","url":"https://staging.dresa.org.au/materials/oecd-report-building-digital-workforce-capacity-and-skills-for-data-intensive-science-2020-0f3cab8c-8028-4bdc-8bb0-ed2cbc70948c.json","description":" \n\nAs 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.\n\nThe presentation highlights:\n\n- 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\n\n- The ongoing need for a digital skilled workforce for data-intensive science\n\n- Five focus areas in the report include:\n\n1. Enablers for digital workforce capacity development\n\n2. Defining needs: digital skills, frameworks and roles\n\n3. Provision of training\n\n4. Community development\n\n5. Career paths and reward structures - Recommendations for actors incl. universities, national or regional governments","doi":"10.5281/zenodo.4289356","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":337,"title":"DReSA: Project team reflections","url":"https://staging.dresa.org.au/materials/dresa-project-team-reflections-63e8d99f-a564-4d77-a221-b7488489c19f.json","description":"This presentation provides thoughts and reflections from the Digital Research Skills Australaisa (DReSA) project team on DReSA. Team members highlight their perspectives on value propositions and benefits for their respective institutiosn/organisations and nationally, as well as individual reflections on collaboration and working together on the project so far.\n\nYou can watch the video on YouTube here: https://youtu.be/qqH92itI8SI \n\n ","doi":"10.5281/zenodo.5712129","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":339,"title":"ARDC Skills Landscape","url":"https://staging.dresa.org.au/materials/ardc-skills-landscape-dd7401f0-702a-4813-b651-28d7cedf5c40.json","description":"The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its purpose of providing Australian researchers with a competitive advantage through data.  \n\nIn this presentation, Kathryn Unsworth introduces the ARDC Skills Landscape. The Landscape is a first step in developing a national skills framework to enable a coordinated and cohesive approach to skills development across the Australian eResearch sector. It is also a first step towards helping to analyse current approaches in data training to identify:\n- Siloed skills initiatives, and finding ways to build partnerships and improve collaboration\n- Skills deficits, and working to address the gaps in data skills\n- Areas of skills development for investment by skills stakeholders like universities, research organisations, skills and training service providers, ARDC, etc.\n\n ","doi":"10.5281/zenodo.4287743","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":338,"title":"Developing an organisation-wide framework to transform and uplift data capabilities","url":"https://staging.dresa.org.au/materials/developing-an-organisation-wide-framework-to-transform-and-uplift-data-capabilities-58f678ce-fbae-4b74-818d-49116a6a8eb8.json","description":"At the Bureau, data is the core of everything we do. We collect millions of observations from our networks and external sources and convert these into essential weather, climate, water and ocean services. To respond effectively to the rapidly evolving data landscape, the Data 2022 and Beyond approach has been developed to position the organisation to maximise the impact and value of data.\n\nThe approach means transforming our data governance, practices and processes. It provides opportunities to leverage, enhance and grow data skills and competencies, while harnessing innovative technologies and methodologies for managing and using data. The Bureau will highlight the complexities of developing an organisation wide data management program in an operational environment and share some examples, learnings and reflections on the uplift journey so far. Key topics will include establishing the team, resources and tools to enhance data governance practices as well as engaging and collaborating with stakeholders.","doi":"10.5281/zenodo.4287866","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":340,"title":"How can software containers help your research?","url":"https://staging.dresa.org.au/materials/how-can-software-containers-help-your-research-6f5d48e1-5b63-4c5f-b306-628e04754917.json","description":"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. \n\nSoftware 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.\n\nWatch the video here: https://www.youtube.com/watch?v=HelrQnm3v4g\n\nIf you want to share this video please use this:\n\nAustralian 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].","doi":"10.5281/zenodo.5091260","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":341,"title":"Institutional Research Data Management Policies and Procedures","url":"https://staging.dresa.org.au/materials/institutional-research-data-management-policies-and-procedures-0ff03ac7-e4cd-4345-9c06-0ff79343d937.json","description":"This is a guide for those developing or updating policies and procedures related to the management of research data as an institutional asset.\nThe guide covers:\n- Why have a research data management policy or policies?\n- Possible approaches to constructing a research data policy suite\n- Examples of data management policies\n- Key topics to include in a research data policy suite\n- Checklist for a Research Data Management Policy for Australian Universities / Institutions","doi":"10.5281/zenodo.5784765","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":342,"title":"ARDC 2023 Skills Summit Lightning Talks (Day 2 - February 10, 2023)","url":"https://staging.dresa.org.au/materials/ardc-2023-skills-summit-lightning-talks-day-2-february-10-2023.json","description":"Presentations to the ARDC Skills Summit 2023 (Lightning Talks Day 2 - February 10th, 2023)\nDr Nisha Ghatak - From local to the global: NeSI's efforts in building digital skills capabilities across Aotearoa\nDr Melissa Burke - No one has time for training. Is doing less the answer?\nDr Giorgia Mori - Industry training collaborations. Is this the future?\nAnn Backhaus - Skills pathways for developing the research workforce - status quo or let's get creative?\n\nThese presentations cover a national perspective of New Zealand's digital skills capability and partnerships, The Carpentries, bioinformatics training, innovative and cooperative training approaches, industry-partnered training, learner pathways, and the importance of user guidance.","doi":"10.5281/zenodo.7711377","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":343,"title":"ARDC 2023 Skills Summit Lightning Talks (Day 1 - February 9, 2023)","url":"https://staging.dresa.org.au/materials/ardc-2023-skills-summit-lightning-talks-day-1-february-9-2023.json","description":"Presentations to the ARDC Skills Summit 2023 (Lightning Talks Day 1 - February 9th, 2023)\nDr Pablo Franco - Assessing the effectiveness of training: Teaching digital skills to researchers\nAidan Wilson - Scaling training operations \u0026amp; succession planning\nDr Paula Martinez - Building community\nDr Mark Crowe - Bringing training to research communities - ResBaz\nLiz Stokes - The Carpentries Partnership\n\nThese presentations cover theoretical frameworks for assessing training, The Kirkpatrick Model of Training Evaluation, outreach, RezBaz, impact assessment, training at scale, succession planning, automated training organisation systems, trainer workforce, research software community, participation models, community building ideas, visible research software interest group, The Carpentries and social infrastructure.","doi":"10.5281/zenodo.7710856","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":344,"title":"ARDC 2023 Skills Summit - Frameworks Panel Discussion (Day 2 - February 10, 2023)","url":"https://staging.dresa.org.au/materials/ardc-2023-skills-summit-frameworks-panel-discussion-day-2-february-10-2023.json","description":"Presentations to the ARDC Skills Summit 2023 (Panel Talks Day 2 - February 10th, 2023)\n\n\nDr Peter Derbyshire - Unpacking the ATSE report - Our STEM skilled future and the need for a national skills taxonomy\nAnthony Beitz - Applying Skills Framework for the Information Age (SFIA) within DSTG\nKate Morrison - A national skills taxonomy - Australian Skills Classification (ASC)\nKathryn Unsworth - ARDC Digital Research Capabilities \u0026amp; Skills Framework\nPeter Embelton - Enhancing skills uplift for researchers through the alignment and implementation of skills frameworks\n\n\nThese presentations cover skills frameworks/taxonomies/classifications, skill shortages, transferrable skills, applying SFIA (Skills Framework for the Information Age), Australian Skills Classification framework, training gaps, workforce/job requirements, Digital Research Skills Australasia (DReSA), digital literacy and applying skills frameworks.","doi":"10.5281/zenodo.7711287","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":321,"title":"Secondary use of clinical trials data in health research: A Practical Guide","url":"https://staging.dresa.org.au/materials/secondary-use-of-clinical-trials-data-in-health-research-a-practical-guide.json","description":"This document presents a theoretical framework for the use of clinical trials and other health data for secondary research purposes, which was derived from research papers, consultation with stakeholders and the research community.  Four overall scenarios for data reuse were identified; scenario 1: evidence synthesis, scenario 2: secondary analyses, scenario 3: reproducibility, replication and validation, and scenario 4: education and methods development.","doi":"10.5281/zenodo.12768050","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":322,"title":"Evaluating training at Pawsey: Motivated, confident \u0026 \"changed\"","url":"https://staging.dresa.org.au/materials/evaluating-training-at-pawsey-motivated-confident-changed-f3d03b3a-de69-4845-94ab-68c11411f504.json","description":"This presentation outlines the digital reserach skills training evaluation methods used at Pawsey. Using the Kirpatrick Training Evaluation model in designing their training evaluation survey, Pawsey measure learning motivation (How did the participant respond to the training?), improved confidence of the learner (Did participants understand the training?) and were there any behavioual changes (How participants applied their new knowledge in practice?).\n\nYou can watch the video of the presentation on YouTube here: https://youtu.be/IOKVrBumEBQ","doi":"10.5281/zenodo.5739608","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":323,"title":"Setting The Scene","url":"https://staging.dresa.org.au/materials/setting-the-scene.json","description":"Opening Address for the ARDC Skills Summit 2023\n\nThis presentation provides a welcome to the ARDC Skills Summit 2023, and includes an outline of the importance of digital research skills to data-enriched research, the value of skills training and highly skilled research workforce to the broader economy, and an overview of related ARDC activity.","doi":"10.5281/zenodo.7710621","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":326,"title":"Successful data training stories from NCI","url":"https://staging.dresa.org.au/materials/successful-data-training-stories-from-nci-6421d59c-b3ed-444f-8123-83186e58391b.json","description":"NCI Australia manages a multi-petabyte sized data repository, collocated with its HPC systems and data services, which allows high performance access to many scientific research datasets across many earth science domains.\nAn important aspect is to provide training materials that proactively engages with the research community to improve their understanding of the data available, and to share knowledge and best practices in the use of tools and other software. We have developed multiple levels of training modules (introductory, intermediate and advanced) to cater for users with different levels of experience and interest. We have also tailored courses for each scientific domain, so that the use-cases and software will be most relevant to their interests and needs.\nFor our training, we combine brief lectures followed by hands-on training examples on how to use datasets, using working examples of well-known tools and software that people can use as a template and modify to fit their needs. For example, we take representative use-cases from some scientific activities, from our collaborations and from user support issues, and convert to Jupyter notebook examples so that people can repeat the workfIow and reproduce the results. We also use the training as an opportunity to raise awareness of growing issues in resource management. Some examples include a familiarity of the FAIR data principles, licensing, citation, data management and trusted digital repositories. This approach to both our online training materials and workshops has been well-received by PhD students, early careers, and cross disciplinary users.","doi":"10.5281/zenodo.4287750","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":324,"title":"ARDC digital research capabilities and skills framework","url":"https://staging.dresa.org.au/materials/ardc-digital-research-capabilities-and-skills-framework.json","description":"This informational flyer outlines the value of skills frameworks and describes at a high level the various elements of the ARDC's Capabilities and Skills Framework.\n\n\n\tCapabilities and Skills Landscape\n\tGlossary - Framework terminology\n\tData and Digital Research roles\n\tSkills/Role profiles\n\tLearning paths\n\tSkills/Data roles matrix","doi":"10.5281/zenodo.6558642","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":325,"title":"An open source textbook for research software engineering","url":"https://staging.dresa.org.au/materials/an-open-source-textbook-for-research-software-engineering-f23f4f43-6214-4fa6-bb1d-83ed51d4d7da.json","description":"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 \u0026amp; 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.","doi":"10.5281/zenodo.4287860","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":327,"title":"Data Management at CLEX","url":"https://staging.dresa.org.au/materials/data-management-at-clex-b527df82-18cb-49d7-a6ae-fa1c655ff5fb.json","description":"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.","doi":"10.5281/zenodo.5403344","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":328,"title":"Accelerating skills development in Data science and AI at scale","url":"https://staging.dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale-4cbed0c1-843b-4d30-af59-9bf6e098a810.json","description":"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.\n\nThe talk will also cover our approach as outlined below\n•        Combined survey of gaps in skills and trainings for Data science and AI\n•        Provide seats to partners\n•        Share associate instructors/helpers/volunteers\n•        Develop combined training materials\n•        Publish a repository of open source trainings\n•        Train the trainer activities\n•        Establish a network of volunteers to deliver trainings at their local regions\n\nIndustry 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.\n\nFinally, 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.","doi":"10.5281/zenodo.4287746","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":329,"title":"Astronomy Data And Computing Services - Upskilling the Australian astronomy community","url":"https://staging.dresa.org.au/materials/astronomy-data-and-computing-services-upskilling-the-australian-astronomy-community-aa4f8d82-6727-4b38-91a8-e124077c44ad.json","description":"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 \u0026amp; computing infrastructure.\n\nDuring 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.\n\nCome 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. ","doi":"10.5281/zenodo.4287748","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":330,"title":"Professionalizing Training - Origin Stories for the Modern Researcher","url":"https://staging.dresa.org.au/materials/professionalizing-training-origin-stories-for-the-modern-researcher.json","description":"Keynote Presentation for the ARDC Skills Summit 2023\n\nThis keynote presentation provides a brief outline of Jason William’s experience and an overview of the training initiatives he has been involved in. His presentation looks at what makes a good researcher and provokes thinking about modern researchers and the need for them to get serious bout career-spanning training. Jason also provides an overview of the Bike Principles and focuses on the first Bike Principles recommendation - Professionalize the training of short-format training instructors and instructional designers.","doi":"10.5281/zenodo.7710785","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":331,"title":"Persistent Identifiers for Research: a talk to the Australasian DMP Interest Group","url":"https://staging.dresa.org.au/materials/persistent-identifiers-for-research-a-talk-to-the-australasian-dmp-interest-group-d06fce47-ce80-460d-9b13-4e1aaf9ae646.json","description":"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).","doi":"10.5281/zenodo.5002519","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":332,"title":"Intersect: Training portfolio","url":"https://staging.dresa.org.au/materials/intersect-training-portfolio-69b950ff-d1b3-48b5-86aa-253ab43294a0.json","description":"This presentation explores Intersect's training evaluation model. Short term evaluation for immediate satisfaction and value of the training. Long term evaluation methods with a specific survey design to determine behavioural change and impact over time of the training on researchers' workflows, use of support services post training and looking for links between digital tools/technologies training and research outputs and grants.\n\nYou can watch the full video on YouTube here: https://youtu.be/J3tCC-t_eO4","doi":"10.5281/zenodo.5739603","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":333,"title":"Research Data Governance","url":"https://staging.dresa.org.au/materials/research-data-governance-1b84a9f4-8c7f-40c2-9658-dd2ee4b50d9d.json","description":"This video contains key information for those who make research data-related decisions. It will help project leaders to start investigating ways to develop their own data governance policy, roles and responsibilities and procedures with the input of appropriate stakeholders.\n\nIf you want to share the video please use this:\n\nAustralian Research Data Commons, 2021. Research Data Governance. [video] Available at: https://youtu.be/K_xVQRdgCIc  DOI: http://doi.org/10.5281/zenodo.5044585 [Accessed dd Month YYYY].","doi":"10.5281/zenodo.5044585","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]}]