[{"id":374,"title":"7 Steps towards Reproducible Research","url":"https://dresa.org.au/materials/7-steps-towards-reproducible-research.json","description":"This workshop aims to take you further down your reproducibility path, by providing concepts and tools you can use in your everyday workflows. It is discipline and experience agnostic, and no coding experience is needed.\r\n\r\nWe will also examine how Reproducible Research builds business continuity into your research group, how the culture in your institute ecosystem can affect Reproducibility and how you can identify and address risks to your knowledge.\r\n\r\nThe workshop can be used as self-paced or as an instructor","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":367,"title":"Sharing a Trove List as a CollectionBuilder exhibition","url":"https://dresa.org.au/materials/sharing-a-trove-list-as-a-collectionbuilder-exhibition.json","description":"You’ve been collecting and annotating items relating to your research project in a Trove List. You’d like to display the contents of your list as an online exhibition for others to explore. [CollectionBuilder](https://collectionbuilder.github.io/) creates online exhibitions using static web technologies. But how do you get your List data from Trove into CollectionBuilder?\r\n\r\nThis tutorial from the Trove Data Guide walks through the complete process step-by-step.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":366,"title":"Create a layer in the Gazetteer of Historical Australian Placenames using metadata from Trove’s digitised maps","url":"https://dresa.org.au/materials/create-a-layer-in-the-gazetteer-of-historical-australian-placenames-using-metadata-from-trove-s-digitised-maps.json","description":"Trove includes thousands of digitised maps, created and published across the last few centuries. You want to create a collection of maps relating to your area of interest and explore it using the Gazetteer of Historical Australian Placenames (GHAP). You know it’s possible to add layers to GHAP, but how do you get the data from Trove in a format that can be uploaded as a layer?\r\n\r\nThis tutorial from the Trove Data Guide walks through the complete process step-by-step.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":365,"title":"Comparing manuscript collections from Trove in Mirador","url":"https://dresa.org.au/materials/comparing-manuscript-collections-in-mirador.json","description":"You want to compare the contents of two digitised manuscript collections and examine individual documents side-by-side. The [Mirador viewer](https://projectmirador.org/) can be configured as a flexible, research workspace that displays multiple images from different sources, but how do you get manuscript collections from Trove to Mirador?\r\n\r\nThis tutorial from the Trove Data Guide walks through the complete process step-by-step.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":364,"title":"Working with a Trove collection in Tropy","url":"https://dresa.org.au/materials/working-with-a-trove-collection-in-tropy.json","description":"You want to be able to work on a collection of digitised images from Trove on your desktop – adding notes, transcriptions, and annotations. [Tropy](https://tropy.org/) is a useful tool for managing collections of research images, but how do you import a collection of images from Trove into Tropy?\r\n\r\nThis tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":363,"title":"Analysing keywords in Trove’s digitised newspapers","url":"https://dresa.org.au/materials/analysing-keywords-in-trove-s-digitised-newspapers.json","description":"You want to explore differences in language use across a collection of digitised newspaper articles. The [Australian Text Analytics Platform](https://www.atap.edu.au/) provides a [Keywords Analysis tool](https://github.com/Australian-Text-Analytics-Platform/keywords-analysis) that helps you examine whether particular words are over or under-represented across collections of text. But how do get data from Trove’s newspapers to the keyword analysis tool?\r\n\r\nThis tutorial from the [Trove Data Guide](https://tdg.glam-workbench.net/home.html) walks through the complete process step-by-step.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":214,"title":"Stereo-video workflows for fish and benthic ecologists","url":"https://dresa.org.au/materials/stereo-video-workflows-for-fish-and-benthic-ecologists.json","description":"Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":177,"title":"Introduction to REDCap at Griffith University","url":"https://dresa.org.au/materials/introduction-to-redcap-at-griffith-university.json","description":"This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":176,"title":"Introduction to text mining and analysis","url":"https://dresa.org.au/materials/introduction-to-text-mining-and-analysis.json","description":"In this self-paced workshop you will learn steps to: \r\n- Build data sets: find where and how to gather textual data for your corpus or data set.  \r\n- Prepare data for analysis: explore useful processes and tools to prepare and clean textual data for analysis\r\n- Analyse data: identify different types of analysis used to interrogate content and uncover new insights","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":175,"title":"Introducing Computational Thinking","url":"https://dresa.org.au/materials/introducing-computational-thinking.json","description":"This workshop is for researchers at all career stages who want to understand the uses and the building blocks of computational thinking. This skill is useful for all kinds of problem solving, whether in real life or in computing.\r\n\r\nThe workshop will not teach computer programming per se. Instead it will cover the thought processes involved should you want to learn to program.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":174,"title":"Advanced Data Wrangling with OpenRefine","url":"https://dresa.org.au/materials/advanced-data-wrangling-with-openrefine.json","description":"This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":173,"title":"Introduction to Data Cleaning with OpenRefine","url":"https://dresa.org.au/materials/introduction-to-data-cleaning-with-openrefine.json","description":"Learn basic data cleaning techniques in this self-paced online workshop using open data from data.qld.gov.au and open source tool OpenRefine openrefine.org. Learn techniques to prepare messy tabular data for comupational analysis. Of most relevance to HASS disciplines, working with textual data in a structured or semi-structured format.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":165,"title":"Introduction to Unix","url":"https://dresa.org.au/materials/introduction-to-unix.json","description":"A hands-on workshop covering the basics of the Unix command line interface.\r\n\r\nKnowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on a high-performance computing system, knowing your way around a command-line interface is highly valuable. This workshop will introduce you to Unix concepts by way of a series of hands-on exercises.\r\n\r\nThis workshop is designed for participants with little or no command-line knowledge.\r\n\r\nTools: Standard Unix commands, FileZilla\r\n\r\nTopic overview:\r\n\r\nSection 1: Getting started\r\nSection 2: Exploring your current directory\r\nSection 3: Making and changing directories\r\nSection 4: Viewing and manipulating files\r\nSection 5: Removing files and directories\r\nSection 6: Searching files\r\nSection 7: Putting it all together\r\nSection 8: Transferring files\r\n \r\nTutorial instructions available here: https://www.melbournebioinformatics.org.au/tutorials/tutorials/unix/unix/\r\n\r\nFor queries relating to this workshop, contact Melbourne Bioinformatics (bioinformatics-training@unimelb.edu.au).\r\n\r\nFind out when we are next running this training as an in-person workshop, by visiting the Melbourne Bioinformaitcs Eventbrite page: https://www.eventbrite.com.au/o/melbourne-bioinformatics-13058846490","doi":"10.5281/zenodo.7059239","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":160,"title":"VOSON Lab Code Blog","url":"https://dresa.org.au/materials/voson-lab-code-blog.json","description":"The VOSON Lab Code Blog is a space to share methods, tips, examples and code. Blog posts provide techniques to construct and analyse networks from various API and other online data sources, using the VOSON open-source software and other R based packages.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":155,"title":"Programming and tidy data analysis in R","url":"https://dresa.org.au/materials/programming-and-tidy-data-analysis-in-r.json","description":"A workshop to expand the skill-set of someone who has basic familiarity with R. Covers programming constructs such as functions and for-loops, and working with data frames using the dplyr and tidyr packages. Explains the importance of a \"tidy\" data representation, and goes through common steps needed to load data and convert it into a tidy form.\r\n\r\nTo be taught as a hands on workshop, typically as two half-days.\r\n\r\nDeveloped by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":154,"title":"Linear models in R","url":"https://dresa.org.au/materials/linear-models-in-r.json","description":"A workshop on linear models in R. Learning to use linear models provides a foundation for modelling, estimation, prediction, and statistical testing in R. Many commonly used statistical tests can be performed using linear models. Ideas introduced using linear models are applicable to many of the more complicated statistical and machine learning models available in R. \r\n\r\nTo be taught as a hands on workshop, typically as two half-days.\r\n\r\nDeveloped by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":153,"title":"Introduction to R","url":"https://dresa.org.au/materials/introduction-to-r.json","description":"An introduction to R, for people with zero coding experience. \r\n\r\nTo be taught as a hands on workshop, typically as two half-days.\r\n\r\nDeveloped by the Monash Bioinformatics Platform and taught as part of the Data Fluency program at Monash University. License is CC-BY-4. You are free to share and adapt the material so long as attribution is given.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":152,"title":"Introduction to Jupyter Notebooks","url":"https://dresa.org.au/materials/introduction-to-jupyter-notebooks.json","description":"This workshop will introduce you to Jupyter Notebooks, a digital tool that has exploded in popularity in recent years for those working with data.\r\n\r\nYou will learn what they are, what they do and why you might like to use them. It is an introductory set of lessons for those who are brand new, have little or no knowledge of coding and computational methods in research.\r\n\r\nThis workshop is targeted at those who are absolute beginners or ‘tech-curious’. It includes a hands-on component, using basic programming commands, but requires no previous knowledge of programming.","doi":"https://doi.org/10.5281/zenodo.6859120","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":99,"title":"Heurist Tutorials","url":"https://dresa.org.au/materials/heurist-tutorials.json","description":"A set of video tutorials with accompanying walkthroughs for building your first Heurist database and website. The first three tutorials show you how to get started in Heurist. The five subsequent tutorials introduce you to the five main menus in the Heurist interface.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":29,"title":"Create a website resume","url":"https://dresa.org.au/materials/create-a-website-resume.json","description":"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.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":28,"title":"10 Reproducible Research things - Building Business Continuity","url":"https://dresa.org.au/materials/9-reproducible-research-things-building-business-continuity.json","description":"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.\r\nResearchers 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.\r\n\r\nVideo:\r\nhttps://www.youtube.com/watch?v=bANTr9RvnGg\r\nTutorial:\r\nhttps://guereslib.github.io/ten-reproducible-research-things/","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":18,"title":"Deep Learning for Natural Language Processing","url":"https://dresa.org.au/materials/deep-learning-for-natural-language-processing.json","description":"This workshop is designed to be instructor led and consists of two parts.\r\nPart 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset.\r\nPart 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for attendees to train their own RNN.\r\nThe Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises.\r\n\r\nThis 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.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":16,"title":"Visualisation and Storytelling","url":"https://dresa.org.au/materials/visualisation-and-storytelling.json","description":"This workshop explores how data visualisation techniques could be utilised to better understand data and to communicate research efforts and outcomes. The workshop covers a broad range of techniques from simple and static 2D graphics to advanced 3D visualisations in order to provide a broad overview of the tools available for data analysis, presentation and storytelling. We explore, among others, animated charts and graphs, web visualisation tools such as scrollytellers, and the possibilities of 3D, interactive, and even immersive visualisations. We use real world, concrete examples along the way in order to tangibly illustrate how these visualisations can be created and how viewers perceive and interact with them. We also introduce the various tools and skill sets you would need to be proficient at presenting your data to the world.\r\nBy the conclusion of this workshop, you would gain familiarity with the various possibilities for presenting your own research data and outcomes. You would have a more intuitive understanding of the strengths and weaknesses of various modes of data visualisation and storytelling, and would have a starting point to obtain the right skill sets relevant to developing your visualisations of choice.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":15,"title":"Semi-Supervised Deep Learning","url":"https://dresa.org.au/materials/semi-supervised-deep-learning.json","description":"Modern deep neural networks require large amounts of labelled data to train. Obtaining the required labelled data is often an expensive and time consuming process. Semi-supervised deep learning involves the use of various creative techniques to train deep neural networks on partially labelled data. If successful, it allows better training of a model despite the limited amount of labelled data available.\r\n\r\nThis workshop is designed to be instructor led and covers various semi-supervised learning techniques available in the literature. The workshop consists of a lecture introducing at a high level a selection of techniques that are suitable for semi-supervised deep learning. We discuss how these techniques can be implemented and the underlying assumptions they require. The lecture is followed by a hands-on session where attendees implement a semi-supervised learning technique to train a neural network. We observe and discuss the changing performance and behaviour of the network as varying degrees of labelled and unlabelled data is provided to the network during training.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":14,"title":"Introduction to Deep Learning and TensorFlow","url":"https://dresa.org.au/materials/introduction-to-deep-learning-and-tensorflow.json","description":"This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise.\r\nPart 1 - Introduction to Deep Learning and TensorFlow\r\nPart 2 - Introduction to Convolutional Neural Networks\r\nThe Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises.\r\n\r\nThis workshop is an introduction to how deep learning works and how you could create a neural network using TensorFlow v2. We start by learning the basics of deep learning including what a neural network is, how information passes through the network, and how the network learns from data through the automated process of gradient descent. Workshop attendees would build, train and evaluate a neural network using a cloud GPU (Google Colab).\r\nIn part 2, we look at image data and how we could train a convolution neural network to classify images. Workshop attendees will extend their knowledge from the first part to design, train and evaluate this convolutional neural network.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]}]