[{"id":285,"title":"Learn to Program: Python","url":"https://staging.dresa.org.au/materials/learn-to-program-python-7f13ec4e-d275-486b-be8d-3c0b8d082a7a.json","description":"Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data.\n\nWe teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research.\n\nJoin us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\n- Introduction to the JupyterLab interface for programming\n- Basic syntax and data types in Python\n- How to load external data into Python\n- Creating functions (FUNCTIONS)\n- Repeating actions and anylsing multiple data sets (LOOPS)\n- Making choices (IF STATEMENTS – CONDITIONALS)\n- Ways to visualise data in Python\n\n**No prior experience with programming** needed to attend this course.\n\nWe strongly recommend attending the [Start Coding without Hesitation: Programming Languages Showdown](https://intersect.org.au/training/course/coding001/) and [Thinking like a computer: The Fundamentals of Programming](https://intersect.org.au/training/course/coding003/) webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/).","doi":"10.5281/zenodo.57492","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":286,"title":"Learn to Program: R","url":"https://staging.dresa.org.au/materials/learn-to-program-r-ce8796ad-a8ad-48b7-9a30-b43c8046d8d1.json","description":"R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.\n\nBut getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this introductory course comes in.\n\nWe teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly.\n\nJoin us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\n- Introduction to the RStudio interface for programming\n- Basic syntax and data types in R\n- How to load external data into R\n- Creating functions (FUNCTIONS)\n- Repeating actions and analysing multiple data sets (LOOPS)\n- Making choices (IF STATEMENTS – CONDITIONALS)\n- Ways to visualise data in R\n\n**No prior experience with programming** needed to attend this course.\n\nWe strongly recommend attending the [Start Coding without Hesitation: Programming Languages Showdown](https://intersect.org.au/training/course/coding001/) and [Thinking like a computer: The Fundamentals of Programming](https://intersect.org.au/training/course/coding003/) webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/).","doi":"10.5281/zenodo.57541","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":248,"title":"Data Manipulation in R","url":"https://staging.dresa.org.au/materials/data-manipulation-in-r.json","description":"R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.  \n  \n In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package).  \n  \n We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly.  \n  \n Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation.\n\nDataFrame Manipulation using the dplyr package  \n DataFrame Transformation using the tidyr package\n\nThe skills developed in [Learn to Program: R](https://intersect.org.au/training/course/r101/) are needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) course to ensure that you are familiar with the knowledge needed for this course.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":265,"title":"Databases and SQL","url":"https://staging.dresa.org.au/materials/databases-and-sql.json","description":"A relational database is an extremely efficient, fast and widespread means of storing structured data, and Structured Query Language (SQL) is the standard means for reading from and writing to databases. Databases use multiple tables, linked by well-defined relationships, to store large amounts of data without needless repetition while maintaining the integrity of your data.  \n  \n Moving from spreadsheets and text documents to a structured relational database can be a steep learning curve, but one that will reward you many times over in speed, efficiency and power.  \n  \n Developed using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nUnderstand and compose a query using SQL  \n Use the SQL syntax to select, sort and filter data  \n Calculate new values from existing data  \n Aggregate data into sums, averages, and other operations  \n Combine data from multiple tables  \n Design and build your own relational databases\n\nThe course has no prerequisites.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":245,"title":"Learn to Program: R","url":"https://staging.dresa.org.au/materials/learn-to-program-r.json","description":"R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.  \n  \n But getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this introductory course comes in.  \n  \n We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly.  \n  \n Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nIntroduction to the RStudio interface for programming  \n Basic syntax and data types in R  \n How to load external data into R  \n Creating functions (FUNCTIONS)  \n Repeating actions and analysing multiple data sets (LOOPS)  \n Making choices (IF STATEMENTS – CONDITIONALS)  \n Ways to visualise data in R\n\nNo prior experience with programming needed to attend this course.  \n  \n We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found \\here\\.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":268,"title":"Collecting Web Data","url":"https://staging.dresa.org.au/materials/collecting-web-data.json","description":"Web scraping is a technique for extracting information from websites. This can be done manually but it is usually faster, more efficient and less error-prone if it can be automated.  \n  \n Web scraping allows you to convert non-tabular or poorly structured data into a usable, structured format, such as a .csv file or spreadsheet. But scraping is about more than just acquiring data: it can help you track changes to data online, and help you archive data. In short, it’s a skill worth learning.  \n  \n So join us for this web scraping workshop to learn web scraping, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nThe concept of structured data  \n The use of XPath queries on HTML document  \n How to scrape data using browser extensions  \n How to scrape using Python and Scrapy  \n How to automate the scraping of multiple web pages\n\nA good knowledge of the basic concepts and techniques in Python. Consider taking our \\Learn to Program: Python\\ and \\Python for Research\\ courses to come up to speed beforehand.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":246,"title":"R for Social Scientists","url":"https://staging.dresa.org.au/materials/r-for-social-scientists.json","description":"R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment.  \n  \n But getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this introductory course comes in.  \n  \n Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Data Carpentry.\n\nBasic syntax and data types in R  \n RStudio interface  \n How to import CSV files into R  \n The structure of data frames  \n A brief introduction to data wrangling and data transformation  \n How to calculate summary statistics  \n A brief introduction to visualise data\n\nNo prior experience with programming needed to attend this course.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":267,"title":"Unix Shell and Command Line Basics","url":"https://staging.dresa.org.au/materials/unix-shell-and-command-line-basics.json","description":"The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line.  \n  \n Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run.  \n  \n We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you’ll learn at this course are generally transferable to other Unix environments.\n\n- Navigate and work with files and directories (folders)\n- Use a selection of essential tools\n- Combine data and tools to build a processing workflow\n- Automate repetitive analysis using the command line\n\nThe course has no prerequisites.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":247,"title":"R for Research","url":"https://staging.dresa.org.au/materials/r-for-research.json","description":"R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.  \n  \n This workshop is an introduction to data structures (DataFrames) and visualisation (using the ggplot2 package) in R. The targeted audience for this workshop is researchers who are already familiar with the basic concepts in programming such as loops, functions, and conditionals.  \n  \n We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly.  \n  \n Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nProject Management with RStudio  \n Introduction to Data Structures in R  \n Introduction to DataFrames in R  \n Selecting values in DataFrames  \n Quick introduction to Plotting using the ggplot2 package\n\n\\Learn to Program: R\\ or any of the \\Learn to Program: Python\\, \\Learn to Program: MATLAB\\, \\Learn to Program: Julia\\, needed to attend this course. If you already have some experience with programming, please check the topics covered in the \\Learn to Program: R\\ course to ensure that you are familiar with the knowledge needed for this course.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":236,"title":"Learn to Program: Python","url":"https://staging.dresa.org.au/materials/learn-to-program-python.json","description":"Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.\n\nWe teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research.\n\nJoin us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\n#### You'll learn:\n\n- Introduction to the JupyterLab interface for programming\n- Basic syntax and data types in Python\n- How to load external data into Python\n- Creating functions (FUNCTIONS)\n- Repeating actions and analysing multiple data sets (LOOPS)\n- Making choices (IF STATEMENTS - CONDITIONALS)\n- Ways to visualise data in Python\n\n#### Prerequisites:\n\nNo prior experience with programming is needed to attend this course.\n\nWe strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/).\n\n  \n  \n  \n**For more information, please click [here](https://intersect.org.au/training/course/python101).**","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":237,"title":"Python for Research","url":"https://staging.dresa.org.au/materials/python-for-research.json","description":"Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data.  \n  \n This workshop is an introduction to data structures (DataFrames using the pandas library) and visualisation (using the matplotlib library) in Python. The targeted audience for this workshop is researchers who are already familiar with the basic concepts in programming such as loops, functions, and conditionals.  \n  \n We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research.  \n  \n Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nIntroduction to Libraries and Built-in Functions in Python  \n Introduction to DataFrames using the pandas library  \n Reading and writing data in DataFrames  \n Selecting values in DataFrames  \n Quick introduction to Plotting using the matplotlib library\n\n\\Learn to Program: Python\\ or any of the \\Learn to Program: R\\, \\Learn to Program: MATLAB\\ or \\Learn to Program: Julia\\, needed to attend this course. If you already have some experience with programming, please check the topics covered in the \\Learn to Program: Python\\ course to ensure that you are familiar with the knowledge needed for this course.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":227,"title":"Version Control with Git","url":"https://staging.dresa.org.au/materials/version-control-with-git.json","description":"Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there to answer all your questions while you gain hands on experience in using Git, one of the most popular version control systems available.  \n  \n Join us for this workshop where we cover the fundamentals of version control using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nkeep versions of data, scripts, and other files  \n examine commit logs to find which files were changed when  \n restore earlier versions of files  \n compare changes between versions of a file  \n push your versioned files to a remote location, for backup and to facilitate collaboration\n\nThe course has no prerequisites.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":233,"title":"Learn to Program: MATLAB","url":"https://staging.dresa.org.au/materials/learn-to-program-matlab.json","description":"MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you’re just getting started – with MATLAB and, more generally, with programming?  \n  \n Nothing beats a hands-on, face-to-face training session to get you past the inevitable syntax errors!  \n  \n So join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.\n\nIntroduction to the MATLAB interface for programming  \n Basic syntax and data types in MATLAB  \n How to load external data into MATLAB  \n Creating functions (FUNCTIONS)  \n Repeating actions and analysing multiple data sets (LOOPS)  \n Making choices (IF STATEMENTS – CONDITIONALS)  \n Ways to visualise data in MATLAB\n\nIn order to participate, attendees must have a licensed copy of MATLAB installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software.  \n  \n No prior experience with programming needed to attend this course.  \n  \n We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found \\here\\.","doi":null,"remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":219,"title":"Tweet hydration tutorial","url":"https://staging.dresa.org.au/materials/tweet-hydration-tutorial.json","description":"how to hydrate tweets (test listing, not currently published) - alice's edits","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":218,"title":"WEBINAR: Protection of genomic data and the Australian Privacy Act: when is genomic data 'personal information'?","url":"https://staging.dresa.org.au/materials/webinar-protection-of-genomic-data-and-the-australian-privacy-act-when-is-genomic-data-personal-information.json","description":"This record includes training materials associated with the Australian BioCommons webinar ‘Protection of genomic data and the Australian Privacy Act: when is genomic data ‘personal information’?’. This webinar took place on 6 April 2022.\n\nEvent description \n\nIt is easy to assume that genomic data will be captured by legal definitions of ‘health information’ and ‘genetic information’, but the legal meaning of ‘genetic information’ need not align with scientific categories. \n\nThere are many different types of genomic data, with varied characteristics, uses and applications.  Clarifying when genomic data is covered by the Privacy Act 1988 (Cth) is an ongoing evaluative exercise but is important for at least 3 reasons: \n\n\n\tthose subject to the Privacy Act need to be able to confidently navigate their responsibilities\n\tunderstanding current controls is a prerequisite for meaningful external critique (and this is particularly important at a time when the Privacy Act is under review), and\n\twhile legislation that applies to state public sector agencies is generally distinct from the Privacy Act there are similarities that extend the relevance of the question when is genomic data ‘personal information’ under the Privacy Act?\n\n\nIn this presentation, Mark will explore the relationship between the legal concept of genetic information and the concept of genomic data relevant to health and medical research, reflect on the characteristics of each, and the possibility\n\nMaterials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tTaylor_Slides (PDF): A PDF copy of the slides presented during the webinar.\n\t\n\n\nMaterials shared elsewhere:\n\nA recording of this webinar is available on the Australian BioCommons YouTube Channel:\n\nhttps://youtu.be/Iaei-9Gu-AI","doi":"10.5281/zenodo.6423621","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":216,"title":"WORKSHOP: Introduction to Metabarcoding using QIIME2","url":"https://staging.dresa.org.au/materials/workshop-introduction-to-metabarcoding-using-qiime2.json","description":"This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Metabarcoding using QIIME2’. This workshop took place on 22 February 2022.\n\nEvent description\n\nMetabarcoding has revolutionised the study of biodiversity science. By combining DNA taxonomy with high-throughput DNA sequencing, it offers the potential to observe a larger diversity in the taxa within a single sample, rapidly expanding the scope of microbial analysis and generating high-quality biodiversity data. \n\nThis workshop will introduce the topic of metabarcoding and how you can use Qiime2 to analyse 16S data and gain simultaneous identification of all taxa within a sample. Qiime2 is a popular tool used to perform powerful microbiome analysis that can transform your raw data into publication quality visuals and statistics. In this workshop, using example 16S data from the shallow-water marine anemone E. diaphana, you will learn how to use this pipeline to run essential steps in microbial analysis including generating taxonomic assignments and phylogenic trees, and performing both alpha- and beta- diversity analysis. \n\nMaterials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tSchedule (PDF): A breakdown of the topics and timings for the workshop\n\t\n\n\nMaterials shared elsewhere:\n\nThis workshop follows the tutorial ‘Introduction to metabarcoding with QIIME2’ which has been made publicly available by Melbourne Bioinformatics.\n\nhttps://www.melbournebioinformatics.org.au/tutorials/tutorials/qiime2/qiime2/","doi":"10.5281/zenodo.6350808","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":217,"title":"WEBINAR: Conservation genomics in the age of extinction","url":"https://staging.dresa.org.au/materials/webinar-conservation-genomics-in-the-age-of-extinction.json","description":"This record includes training materials associated with the Australian BioCommons webinar ‘Conservation genomics in the age of extinction’. This webinar took place on 8 March 2022.\n\nEvent description \n\nBiodiversity is crashing and millions of plant and animal species are at the edge of extinction. Understanding the genetic diversity of these species is an important tool for conservation biology but obtaining high quality genomes for threatened species is not always straightforward.\n\nIn this webinar Dr Carolyn Hogg speaks about the work she has been doing with the Threatened Species Initiative to build genomic resources to understand and protect Australia’s threatened species. Using examples such as the Kroombit Tinker Frog and the Greater Bilby, Carolyn describes some of the complexities and challenges of generating genomes from short reads and HiFi reads for critically endangered species. She outlines the technologies and resources being used and how these are bridging the gap between genomicists, bioinformaticians and conservation experts to help save Australian species.\n\nMaterials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\n\nMaterials shared elsewhere:\n\nA recording of this webinar is available on the Australian BioCommons YouTube Channel:\n\nhttps://youtu.be/Bl7CaiGQ91s\n\n ","doi":"10.5281/zenodo.6350785","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":215,"title":"WEBINAR: Establishing Gen3 to enable better human genome data sharing in Australia","url":"https://staging.dresa.org.au/materials/webinar-establishing-gen3-to-enable-better-human-genome-data-sharing-in-australia.json","description":"This record includes training materials associated with the Australian BioCommons webinar ‘Establishing Gen3 to enable better human genome data sharing in Australia’. This webinar took place on 16 February 2022.\n\nEvent description \n\nAustralian human genome initiatives are generating vast amounts of human genome data. There is a desire and need to share data with collaborators but researchers face significant infrastructural, technical and administrative barriers in achieving this. To efficiently share and distribute their genome data they need scalable services and infrastructure that: is easily administered; allows for the efficient data management; enables sharing and interoperability; and is aligned with global standards for human genome data sharing.\n\nAustralian BioCommons has brought together a team from Zero Childhood Cancer (Zero), the University of Melbourne Centre for Cancer Research (UMCCR) and Australian Access Federation to explore the use of Gen3 technology. Establishing systems for easier management and sharing of their human genome data holdings is no simple task, and the group wants to ensure that other Australian providers and Institutions can benefit from their experience and easily deploy the same solution in the future.\n\nGen3 is an open source software suite that makes use of private and public clouds to tackle the challenges of data management, interoperability, data sharing and analysis. It has been used in several very large NIH-funded projects that collectively house and describe data derived from hundreds of thousands of human samples (e.g. NCI Genomic Data Commons, BioData Catalyst, BloodPAC, BrainCommons, Kids First Data Commons).\n\nIn this webinar you’ll hear from UMCCR and Zero about their experiences and progress towards establishing Gen3 instances to better enable better human genome data sharing in Australia. They will outline the challenges and opportunities that have arisen through this Australian BioCommons project and demonstrate the capabilities of Gen3 for human genome research.\n\nMaterials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tGen3_Webinar_Slides (PDF): Slides presented during the webinar\n\t\n\n\n \n\nMaterials shared elsewhere:\n\nA recording of this webinar is available on the Australian BioCommons YouTube Channel:\n\nhttps://youtu.be/1F6B03Byigk","doi":"10.5281/zenodo.6233075","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":206,"title":"ARDC Research Software Rights Management Guide","url":"https://staging.dresa.org.au/materials/ardc-research-software-rights-management-guide.json","description":"How researchers may license their research software in order to share it with others.\n\nIt addresses the types of open‑source licences, and considerations you (as a researcher) should have in deciding which licence to adopt for sharing.","doi":"10.5281/zenodo.5003962","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":207,"title":"National skills ecosystem - call to action","url":"https://staging.dresa.org.au/materials/national-skills-ecosystem-call-to-action.json","description":"In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4.\n\n- Skilled trainers / facilitators\n\n- National training registry\n\n- National training event calendar\n\n- Jointly developed training\n\n- Research support professionals: career/progression","doi":"10.5281/zenodo.4289335","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":168,"title":"An open source textbook for research software engineering","url":"https://staging.dresa.org.au/materials/an-open-source-textbook-for-research-software-engineering.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":169,"title":"Software publishing, licensing, and citation","url":"https://staging.dresa.org.au/materials/software-publishing-licensing-and-citation.json","description":"A short presentation for reuse includes speaker notes.\n\nMaking software citable using a code repository, an ORCID and a licence.","doi":"10.5281/zenodo.5091717","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":170,"title":"How can software containers help your research?","url":"https://staging.dresa.org.au/materials/how-can-software-containers-help-your-research.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":171,"title":"ARDC Research Data Rights Management Guide","url":"https://staging.dresa.org.au/materials/ardc-research-data-rights-management-guide.json","description":"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.\n\nWho 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.","doi":"10.5281/zenodo.5091580","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":173,"title":"Research Data Governance","url":"https://staging.dresa.org.au/materials/research-data-governance.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":[]},{"id":174,"title":"ARDC Guide to making software citable","url":"https://staging.dresa.org.au/materials/ardc-guide-to-making-software-citable.json","description":"A short guide to making software citable using a code repository, an ORCID and a licence.","doi":"10.5281/zenodo.5003989","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":175,"title":"ML4AU: Trainings, trainers and building an ML community","url":"https://staging.dresa.org.au/materials/ml4au-trainings-trainers-and-building-an-ml-community.json","description":"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.\n\nYou can watch the YouTube video here: https://youtu.be/cQS0guC5_Cg","doi":"10.5281/zenodo.5711863","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":176,"title":"Coding and Software Club at the Burnet Institute: a Sisyphean story of normalising peer-to-peer learning","url":"https://staging.dresa.org.au/materials/coding-and-software-club-at-the-burnet-institute-a-sisyphean-story-of-normalising-peer-to-peer-learning.json","description":"This presentation outlines the Burnet Institute and its Coding and Software Club. What motivated the establishment of the Club and what keeps it going, the tools used to engage, teach and learn and finally, how the Club has impacted people at various levels of the organisation. Also explored are the challenges, opportunities and lessons learnt - valuable insights into what it tkaes to keep a community focused and enduring.\n\nYou can watch the video on YouTube here: https://youtu.be/c2syM1Dfqbo","doi":"10.5281/zenodo.5739771","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":177,"title":"Software publishing, licensing and citation","url":"https://staging.dresa.org.au/materials/software-publishing-licensing-and-citation-63cd319a-f148-4716-84e7-f3fdd052f2d9.json","description":"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.\n\nThis session explained why and how to publish, licence and cite software.\n\nA video recording of this session can also be found on ARDC's YouTube channel: https://youtu.be/l2acLeuF_QE","doi":"10.5281/zenodo.4816879","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":178,"title":"Why am I being asked for metadata about my research data?","url":"https://staging.dresa.org.au/materials/why-am-i-being-asked-for-metadata-about-my-research-data.json","description":"Find out why metadata are important for your research data collection. This brochure shares the reasons why researchers should use metadata for their data collections.\n\nThis brochure was prepared for the ARDC Data Retention Project https://ardc.edu.au/collaborations/strategic-activities/data-retention-project/.\nIt is for researchers at any institution in Australia.","doi":"10.5281/zenodo.5778322","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]}]