Session List

Welcome to ResBaz: When all you have is a hammer, every problem looks like a nail: why you should consider learning a new digital tool, and what is the right one to use

Chris will provide insights from his personal experiences of having had to use a range of different digital tools in research. He'll compare the time spent leaning vs that saved with colleagues who have stuck to their 'hammers', (Excel - I'm looking at you) and hope to show you the benefit of time spent developing a 'toolbox' of digital tools. He will also talk about the advantages and disadvantages of the digital tools that he has encountered with the goal of helping you find identify the right 'tool' for your need.

This open session is designed to help attendees to identify other ResBaz sessions that may be useful to them. Zoom link

Research Data Management (Part 1): Planning, Organising & Storing

Research data: that which is created, collected or observed in the course of producing original research, regardless of format. This introductory workshop is aimed at researchers, particularly those embarking on their research career or starting a new research project. Attendees will develop strategies for capturing and organising research data, sharing and reusing data, and have an opportunity to draft a Data Management Plan (DMP). You will be introduced to data management concepts, best practices, services and useful tools to support you managing and sharing your research data. Book here
Research Data Management (Part 2) - Sharing, archiving and publishing

Researchers are increasingly being asked by funders, publishers and their institutions to share their research data. Come along to this workshop to learn about how you can prepare and disseminate your research findings; increase your research impact through data publication; and, learn about services available to you to achieve this. Book here
Data Analysis with Jupyter Notebooks

Jupyter Notebooks are an open source web application that you can use to create and share documents that contain live code, equations, visualizations, and text. This session will give an overview of how and why these notebooks can be useful for research and analysis, and how you can unlock the power of the functionality they offer. Book here
Data Science
Working with social media data?

Social media data can enable insightful research into areas like social behaviour and current events. Join this session to connect with and learn from others working with social media data within the Aotearoa research community. Designed as a community building session, attendees will have the opportunity to share their research topics, methods, and challenges. We’ll also hear from those developing social media and related collections. Book here
Data Science
Introduction to OpenRefine

OpenRefine is a free, open-source powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data. This introductory, follow-along workshop will demonstrate how it can help you: Get an overview of a data set and resolve inconsistencies; split data up into more granular parts; match local data up to other data sets; and enhance a data set with data from other sources.

This session is now full, please add yourself to the waiting list here to receive a post-session recording.

Data Science
How can Python help your research

A holistic overview of the Python programming language aimed at those who are new to Python and interested in how it can help with their research. No prior knowledge of Python required, no hands-on coding involved, just sit back with your favourite beverage and find out about: key concepts in Python, how Python is used around the world, and how Python can help you organise, analyse, and visualise your research data. Book here
Data Science
Research Portfolio website (using GitHub)

Learn how to create a attractive, functional website to showcase your research career and outputs using GitHub and wowchemy. Some familiarity with git, HTML and CSS will be beneficial, but not necessary.

This session is now full, please add yourself to the waiting list here to receive a post-session recording.

Research data collection & surveys with REDCap - an overview

A brief overview of REDCap, a software tool which can help you create and manage research databases and participant surveys with sensitive data. Book here
Creating Professional LaTeX Reports Without Losing Hair

Go beyond the basics in this workshop. You will learn how LaTeX documents can be split up into styles, pages, appendices, etc. so that you can work in manageable chunks. This workshop will demonstrate several useful LaTeX packages and show you how to create documents without Overleaf. Prior knowledge in Bash and LaTeX is helpful, but not required. A template will be provided for participants.

This session is now full, please sign-up to the waiting list here to receive a post-session recording.

Publication Ready Figures (with Python, Matplotlib and Seaborn) 9am start

Python is a powerful plotting tool but, with so many options and settings, it can be time consuming to figure out how to make effective and attractive plots. This workshop is your cheat sheet for using the Python packages matplotlib and Seaborn to make static plots. It's an interactive session and we assume some basic Python skills. If you’re looking for a way to level-up your visual communication of data and increase engagement with your research, then this is for you.

Session note: This workshop starts at 9am. You will be able to do this workshop if you have imported a module, printed a statement, and made a basic plot. If new to Python, please attend the 'Python: an introduction' session before doing this workshop.

Requirements: Detailed setup instructions will be provided prior to the workshop, along with a link to download the course material before the workshop.

This session is now full, please add yourself to the waiting list here and we will send you a post-session recording.

Open Source in Research

What is open source in the context of research and why to contribute to it? This is a pannel discussion session that addresses these questions and provides a practical guide to getting started. The pannel includes Irene Wallis (University of Auckland, convener), Lindsey Heagy (University of British Colombia), Leonardo Uieda (University of Liverpool), and Matt Hall (Agile* Scientific). If you’re interested in research repeatability, creating oppertunites to colaborate and build community, and increasing the impact of your research, then this workshop is for you. Book here
Data Science
How to Make Your Publications Open Access

Open Access to publications and other research outputs ensures you get maximum exposure and recognition for your work. Open publications are viewed, downloaded, and cited at higher rates than closed publications. There are free ways to make your work open regardless of where you publish, so you don't have to publish in OA journals or pay steep publication fees to enjoy the benefits of OA. In this one hour workshop you'll learn how to make your publications open for free while respecting copyright and publisher agreements. Book here
Data Science
Managing References with Zotero

Academic references are the bread and butter of research life. We spend a lot of time capturing, organising, and consulting references, so it makes sense to use the right tool for the job. Zotero is a free open-source reference manager built by researchers for researchers. It is simple to learn, yet powerful and feature-rich, and will save you countless hours at university and beyond. In this two hour workshop you'll learn how to use Zotero to capture, organise, and cite your references when you need them. Monday session now full!

Due to the high volume of interest in Managing References with Zotero, an additional session will now run on Friday.

Both sessions are now full please add yourself to the waiting list here to receive a post-session recording.

Building a Website with WordPress

A personal website is an impressive way to share your skills and experience with potential employers and colleagues. WordPress is the most popular website Content Management System in the world because it is powerful, flexible, and requires no coding experience. In this two hour workshop you'll learn how to get up and running with a free website in no time using WordPress. You'll learn how to build a simple personal website, add pages, start a blog and add posts, and some basic styling. We'll also touch on the pros and cons of self-hosted websites for those who are looking for more flexibility. Thursday session now full!

Due to the high volume of interest in Building a Website with WordPress, an additional session will now run on Tuesday.

Both sessions are now full, please add yourself to the waiting list here to receive a post-session recording.

An introduction to processing remote sensing data with Google Earth Engine

Google Earth Engine (GEE) can be considered a one-stop-shop for your raster-based geospatial needs without the hassle of preprocessing. This practical workshop provides a comprehensive introduction to using GEE through the javascript based code editor and aims to enable provide you with the necessary knowledge to leverage Earth Engine for you own geospatial research. This workshop will be delivered in 3 parts focused around accessing satellite imagery, performing analysis and image classification.

This session is now full please add yourself to the waiting list here to reveive a post-session recording.

Data Science
Design 101: Presentations, Posters, and PowerPoints for Researchers

Why are you here? What are you presenting? Who are you presenting to? No, this is not the abstract for “Existentialism with Nietzsche”, it’s “Design for Dummies”! Have you ever seen a research poster or a PowerPoint presentation that was truly terrible and thought, “Wow, I wonder how I could salvage that? I wonder how I can make research approachable through attractive design?”

In this session, we will give you tips on what makes good visual design for research. We will walk you through the do’s (and some don’ts) and what to consider when putting together a visual research presentation, whether a poster, a PowerPoint slideshow, or another type of medium. After that, we’ll do a step-by-step practical exercise to put what we’ve just gone over into action. Book here

Machine Learning 101

The NeSI team will introduce you to the wonderful world of machine learning via the user-friendly Jupyter on NeSI platform. Come along to acquaint yourself with amazing algorithms and conquer your fear of obscure machine learning jargon.

This whirlwind tour of the Scikit-learn Python library will introduce the usual machine learning suspects (aka things that are easy to google). Specifically, attendees will learn about model fitting, evaluation and model selection. At the end of this session you should be more familiar with:

- what problems machine learning can help solve

- the definitions of key machine learning terms

- the main phases of a machine learning project

- the types of ML tasks and associated classes of models

This session provides a taster for a full day workshop provided by NeSI. Book here

Data Science
Introduction to R and RStudio

R is a programming language for data analysis and statistics. It is free, and very widely used in various application areas, such as bioinformatics. The goal of this workshop is to help you familiarize yourself with RStudio, basic R terminology and routine workflows. We will showcase some of the available tools to tackle a wide variety of data science challenges, including data management and visualization. In addition, there will be live hands-on exercises for you to practice R coding and we will share tips-and-tricks to help you start your confident R journey! Monday session full .

Due to overwhelming interest in an Introduction to R and Rstudio an additional session is being run on Tuesday at 13:00.

Both Introduction to R sessions are now full, please add yourself to the waiting list here and we will send you a post-session recording .

Data Science
Introduction to geospatial tools and manipulations in R

Geospatial data is being more and more commonly used in scientific research. From modelling distributions or movements of animals, the connectivity of spatial networks, mapping/modelling physical features of our environment or predicting the occurrence of events through space and time. In this workshop we will introduce the fundamental types of geospatial data (points, lines, polygons and gridded) that are commonly used for analysis and mapping. By the end of the workshop you will have had hands on practice with the basics of importing and preparing these kinds of data for a range of analyses and creating publication ready graphs and maps!

This session is now full, please add yourself to the waiting list here and we will send you a post-session recording.

Data Science
Introduction to command line

Learning the command line is the first step before you are able to utilise other digital tools like Python, R, and OpenRefine. It allows you to automate repetitive tasks. It can be intimidating to get started but once you’ve mastered bash commands, it becomes relatively easy to write scripts. This enables you to build all sorts of data pipelines and workflows much more easily.

In this interactive session you will be learning command line using the terminal interface. We will cover a range of basic commands that will help you navigate and explore, create files and directories, write, read and concatenate, how to use command arguments/options and combine existing commands, as well as copy, move and remove files. If you are using Windows, please install Git for Windows.

This session is now full, please add yourself to the waiting list and we will send you a post-session recording here.

Introduction to Julia

Julia is a relatively new, multi-purpose programming language, with increasing adoption among scientific researchers. Interaction with Julia closely resembles that of scripting languages, such as R, MATLAB and python, and a growing number of Julia libraries provide similar functionality for scientific computation. However, extending modifying, or creating new software in these languages is complicated as all performance critical code must be written in a second, low-level language, like C or FORTRAN, which are more technically demanding, and are slower to test, debug, etc. Julia's careful and elegant design solves this two language problem.

In this session, learn more about this exciting new language, and whether it might be a good match for your research project. Participants will be walked through a basic Julia installation and will have the opportunity to carry out some basic data manipulation and visualization tasks.

this session is now full, please add yourself to the waiting list here to receive a post-session recording.

Data Science
Machine learning in Julia

This session teaches participants how to use the open source softare MLJ (Machine Learning in Julia) to quickly select, optimize and compare a large number of machine learning models. While some machine learning courses focus on deep learning methods, emphasis here will be on quickly comparing models from multiple paradigms.

This is a tutorial on how to use the MLJ software, and not a course on machine learning itself. Some experience in another scripting laguage is required for this session.

This session is now full, please add yourself to the waiting list here to receive session marerial.

Data Science
NVivo Showcase

There’s a lot more to NVivo than initially meets the eye! In this webinar we’ll be showcasing our favourite features of NVivo including matrix coding queries, explore and comparison diagrams, and mind-maps. This session is perfect for researchers who are new to NVivo, as well as those who are familiar with the basics and curious to know what else is possible. Zoom link
Research computing with the Rust programming language

What is Rust, and how might you use it for research? Tim McNamara, author of Rust in Action, will give a quick primer of the programming language, and explain how it might be used to speed up, and scale up, your research. Register here
Data Science
Python for image manipulation and repeatable research pipelines

You know how to crop an image, but what if you need to crop 65000 images in one go? This applied tutorial will introduce how the Python programming language can be used to create powerful, scalable and repeatable workflows, using image manipulation as an example. The session will include a live demo with commentary, project showcase and questions and answers. Having an entry level understanding of Python or a similar programming language will be helpful, but not essential. Book here
Data Science
Genomics community: What skills do we need?

This session is for anyone in the genomics research community. Join colleagues and representatives from Auckland Genomics, NeSI, Auckland Grafton Genomics, Genomics Aotearoa, and Te Ira Kāwai – Auckland Regional Biobank, to make connections as we discuss what skills need to be developed, and what can be offered. Come along to share your ideas for how this Aotearoa-wide community can develop. Book here
Introduction to High Performance Computing with NeSI

This is a two hour, hands-on introduction to high performance computing (HPC). Members of NeSI’s apps support team will guide attendees through HPC fundamentals including:

- How to access the NeSI HPC clusters.

- Basics of high performance computing.

- Working with a scheduler.

- Accessing software via modules.

- Using resources effectively and responsibly.

The goal of this workshop is to get you using the NeSI platform, so come ready to participate!

We will be working from the NeSI fork of Introduction to High-Performance Computing.

Requirements: NeSI account, details on registration. Book here

Data Science
Tidy data: an introduction

Good data organisation is the foundation of any research project. We often organise data in spreadsheets in ways that we as humans want to work with it, but computers require data be organised in particular ways. In order to use tools that make computation more efficient such as programming languages like R or Python, we need to structure our data the way that computers can make sense of it. Since this is where most research projects start, this is where we want to start too! Preparing data for analysis is an important part of the research workflow and some have estimated that this data preparation may take 4x as long as the "analysis" itself. Some of this involves data cleaning, where errors in the data are identifed and corrected or formatting made consistent, but the foundation is to start with a machine readable datasheet. In this workshop we will cover the basics of good data hygiene and the core principles of the tidy data framework which ensures that your data are machine readable and ready for manipulation/analysis. We encourage you to bring along a device that has access to some kind of spreadsheet software (e.g. google sheets, excel, etc.), so you can spot the problems and work towards putting tidy data into practice. Book here
Data Science
Research Compute - overview of University of Auckland options

Need more computer power to do your analysis? Is your laptop/desktop struggling to run your analysis? Come along to hear about virtual machines and High Performance Computing options available to University of Auckland researchers and research postgraduate students. Book here
Infographics and storytelling

Tips and tricks to help you communicate your data more effectively. Book here
Data Science
Stop paying for free software: Creating a LaTeX pipeline for collaboration

Overleaf is a great tool to get a LaTeX project up and running, but has many limitations, including paywalling collaboration features. We'll empower you to create your own local setup for writing LaTeX documents so that you can fine tune your environment to suit your needs. In the first hour, you will learn to create a local LaTeX set up, keep it tidy, and automated. The second hour will give you the confidence to create your own customisations and content will be driven by participant interest.

This session is for you if you're a LaTeX user and need to collaborate with others, want to keep an up-to-date electronic notebook, or want the freedom of creating a distraction-free environment to focus on your writing.

Participants should have attended an introduction to Bash. Some Python background would be helpful, but not required. A LaTeX project template will be provided.

This session is now full, please add yourself to the waiting list here to recieve session material after ResBaz.

Genomic data management: tips and tricks

Join this genomic data community session to learn and share tips and tricks on geneomic research data management. Book here
Data Science
Version control for documents and code

Version Control (aka Revision Control aka Source Control) lets you track your files over time. Why do you care? So when you mess up you can easily get back to a previous working version. In this session you will learn about the principles and practices for version control of documents and code/software, including:

- how to get started with Git and why learning this tool is worth the effort

- what do things like push, pull, clone, local, and remote mean

- how to setup and maintain a git repository

- how to use GitHub for collaboration.

This session is now full, please add yourself to the waiting list here and we will send you a post-session recording.

Data Science
Tidyverse: Key Tips for Existing R Users

Over the last years the tidyverse has changed R programming for data scientists tremendously: cleaning and analysing rectangular data, loops, and parallelization can now be performed through a number of convenience functions. The session offers some recipes and translations for existing R users who want to include more of the tidyverse in their everyday data analysis tasks. Book here
Data Science
Collecting sensitive survey data with Qualtrics

Are you looking to collect sensitive data, such as personal information, in your research? This session will cover different methods you can use to protect this data in Qualtrics, including creating screener surveys, using pre-assigned participant Ids, and anonymising responses. Book here
Introduction to Qualtrics for Research Surveys

This session will introduce you to Qualtrics, a powerful survey tool useful for collecting a range of research data. Book here
Find, replace and manipulate big datasets

Do you want to get better acquainted with the command line and use the tools that you did not know were in your arsenal? This practical workshop will introduce you to regular expression and how to implement it using sed and grep to manipulate big (or small) datasets so that they become fit for purpose. Think of this as find and replace/subset, but with functionality and usability that you did not know was possible. The knowledge gained can be used with applications such as Notepad++ and R. This session is interactive and examples will include handling, preparing, manipulating and/or formatting DNA databases, but these tools are so versatile that it is applicable to other datasets.

This workshop follows on from bash/introduction to command line session, and attendees need to have working knowledge of the basic commands that will allow you to navigate in the terminal and read, create and write directories/files (for example: cd, mkdir, ls, cat, nano, etc…).

This session is now full, please add yourself to the waiting list here and we will send you a post-session recording.

Data Science
High performance computations with multithreading

A C-based workshop on using multiple threads to improve performance of your code. In shared-memory parallelism applications achieve parallelism by executing more than one thread at a time across cores within one node. Each of the threads see and manipulate the same memory that the initial process allocated. The workshop explains how parallelism is achieved in HPC applications, what considerations are to be given to the code, what are the benefits and drawbacks of multithreading. Book here
Data Science
Parallel programming with MPI

A C-based workshop targeting distributed programming in high performance environment. In distributed-memory parallelism an application achieves parallelism by running multiple instances of itself across multiple nodes to solve the problem. Each instance is allocated its own chunk of virtual memory and communicates to other instances via a message passing interface such as MPI. Distributed memory type jobs have many advantages, among which are more cores to tackle the problem and a far greater amount of memory. The workshop explains details of MPI environment, types of operations MPI employs and considerations given to various implementation models. Book here
Data Science
GLAM workbench

A cross-over event with Digital Humanities Australasia - DHA2021, hosted at the University of Canterbury.

More and more institutions in the GLAM sector (Galleries, Libraries, Archives, and Museums) are sharing their collection data online, but what is it, and how do you use it? Associate Professor Tim Sherratt will survey the types of data available and explore possible research topics using tools and examples from the GLAM Workbench, including Aotearoa/NZ collections. Tim will show how GLAM data can be harvested, aggregated, analysed, and visualised, and share his enthusiasm for what GLAM data tell us about history, society, and culture. Book here

Māori and Pacific researchers: Reimagining relationality with digital tools

Kia ora and Talofa, Māori and Pacific researchers and students from any discipline are invited to this kōrero. We will explore what it means to use digital research tools, including WordPress, how these can impact research, and how we can develop these tools within our mahi. Book here
How to plan your research for real world impact

Economic, societal and environmental impact, or the ‘non-academic’ impact of research, is becoming an increasingly important part of the research ecosystem. It is standard practice for researchers to be asked by funders to describe the benefits of their research and how they might enable that benefit to be achieved. This session offers a high-level step-by-step guide on how to incorporate impact into your research planning. Book here
Becoming a Data Scientist 101

Andrew will share his journey from musician to data scientist and give insights into the skills he has found most useful. Andrew now works in the commercial sector after working in a University environment. There will be opportunity to ask Andrew and others questions regarding pursuing a career in data science. Zoom link
Data Science
Digital storytelling with KnightLab

Interested in learning how to use a suite of open-source tools to create interactive narratives and visualisations for your research? This session provides an overview of a range of free, easy-to-use tools from KnightLab useful for time or location-based narratives. Learn the basics and see how easy and fun it is to create a compelling StoryMap. Book here
ResBaz drop-in clinic

Open drop-in session to help with trouble shooting, geting help with installing session requirements, and any ResBaz questions Zoom link