Tutorials to learn how to use STAN
Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics.
Keywords: Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB
Tutorials to learn how to use STAN
https://mc-stan.org/users/documentation/tutorials.html
https://dresa.org.au/materials/tutorials-to-learn-how-to-use-stan
Stan tutorials offer links to exceptional tutorial papers, videos and statistics to learn Bayesian statistical methods and applied statistics.
https://mc-stan.org/about/team/
Statistics, applied statistics, Bayesian statistics, R software, Python, MATLAB
Species Distribution Modelling in R
This set of scripts and videos provide an introduction to running SDMs in R and include some steps to consider that go beyond what's available in the EcoCommons SDM point-and-click tools.
Five videos include: 1. An introduction to SDM in R, 2. occurrence data, 3. environmental data, 4. fitting...
Keywords: Species Distribution Modelling, Ecology, R software, EcoCommons
Species Distribution Modelling in R
https://www.ecocommons.org.au/educational-material4-mastering-species-distribution-modelling-in-r/
https://dresa.org.au/materials/species-distribution-modelling-in-r
This set of scripts and videos provide an introduction to running SDMs in R and include some steps to consider that go beyond what's available in the EcoCommons SDM point-and-click tools.
Five videos include: 1. An introduction to SDM in R, 2. occurrence data, 3. environmental data, 4. fitting your model, 5. model evaluation
Scripts and files are available here:
https://github.com/EcoCommons-Australia/educational_material/tree/main/SDMs_in_R/Scripts
Scripts for all four modules are here: https://www.ecocommons.org.au/wp-content/uploads/EcoCommons_steps_1_to_4.html
https://www.ecocommons.org.au/contact/
https://orcid.org/0000-0002-1359-5133
Species Distribution Modelling, Ecology, R software, EcoCommons
ugrad
mbr
phd
Astronomy Data And Computing Services - Upskilling the Australian astronomy community
The Astronomy Data And Computing Services (ADACS) initiative has been working with the Australian astronomy community for just over 3 years now. Our vision is to deliver astronomy-focused training, support and expertise to maximise the scientific return on investments in astronomical data &...
Keywords: astronomy, data skills, eresearch skills, skills, computational skills, training, skills gaps, astronomy-focused training, training material
Astronomy Data And Computing Services - Upskilling the Australian astronomy community
https://zenodo.org/records/4287748
https://dresa.org.au/materials/astronomy-data-and-computing-services-upskilling-the-australian-astronomy-community-57afa0b9-77da-4dc1-ad29-25089f19363d
The Astronomy Data And Computing Services (ADACS) initiative has been working with the Australian astronomy community for just over 3 years now. Our vision is to deliver astronomy-focused training, support and expertise to maximise the scientific return on investments in astronomical data & computing infrastructure.
During these last 3 years, we have delivered dozens of face-to-face, hands-on workshops and created several hours worth of online tutorial materials. This talk will focus on our journey to deliver this computational skills training to the community, exploring how we chose different delivery pathways and content, based both on community input as well as our professional expertise and understanding of existing skill gaps. Most importantly we will discuss our plans for the future and how we are working on actively including the community in developing new training material beyond the usual skills survey.
Come along to this talk if you would like to hear about a national effort to deliver computational skills training and would like to know more about potential new avenues to provide just-in-time training and how to collaborate with ADACS.
contact@ardc.edu.au
Lange, Rebecca (orcid: 0000-0002-9449-4384)
astronomy, data skills, eresearch skills, skills, computational skills, training, skills gaps, astronomy-focused training, training material
WORKSHOP: Single cell RNAseq analysis in R
This record includes training materials associated with the Australian BioCommons workshop ‘Single cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022.
Event description
Analysis and interpretation of single cell RNAseq (scRNAseq) data...
Keywords: Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq
WORKSHOP: Single cell RNAseq analysis in R
https://zenodo.org/records/7072910
https://dresa.org.au/materials/workshop-single-cell-rnaseq-analysis-in-r-4f60b82d-2f1e-4021-9569-6955878dd945
This record includes training materials associated with the Australian BioCommons workshop ‘Single cell RNAseq analysis in R’. This workshop took place over two, 3.5 hour sessions on 22 and 3 August 2022.
Event description
Analysis and interpretation of single cell RNAseq (scRNAseq) data requires dedicated workflows. In this hands-on workshop we will show you how to perform single cell analysis using Seurat - an R package for QC, analysis, and exploration of single-cell RNAseq data.
We will discuss the ‘why’ behind each step and cover reading in the count data, quality control, filtering, normalisation, clustering, UMAP layout and identification of cluster markers. We will also explore various ways of visualising single cell expression data.
This workshop is presented by the Australian BioCommons and Queensland Cyber Infrastructure Foundation (QCIF) with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative.
Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.
Files and materials included in this record:
Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Index 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.
scRNAseq_Slides (PDF): Slides used to introduce topics
scRNAseq_Schedule (PDF): A breakdown of the topics and timings for the workshop
scRNAseq_Resources (PDF): A list of resources recommended by trainers and participants
scRNAseq_QandA(PDF): Archive of questions and their answers from the workshop Slack Channel.
Materials shared elsewhere:
This workshop follows the tutorial ‘scRNAseq Analysis in R with Seurat’
https://swbioinf.github.io/scRNAseqInR_Doco/index.html
This material is based on the introductory Guided Clustering Tutorial tutorial from Seurat.
It is also drawing from a similar workshop held by Monash Bioinformatics Platform Single-Cell-Workshop, with material here.
Melissa Burke (melissa@biocommons.org.au)
Williams, Sarah
Mehdi, Ahmed (orcid: 0000-0002-9300-2341)
Matigan, Nick
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Morgan, Steven (orcid: 0000-0001-6038-6126)
Whitfield, Holly (orcid: 0000-0002-7282-387X)
Bioinformatics, Analysis, Transcriptomics, R software, Single cell RNAseq, scRNAseq
WORKSHOP: R: fundamental skills for biologists
This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.
Event description
Biologists need data analysis skills to be able to...
Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WORKSHOP: R: fundamental skills for biologists
https://zenodo.org/records/6766951
https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists-81aa00db-63ad-4962-a7ac-b885bf9f676b
This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.
Event description
Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.
R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.
Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R.
Topics covered in this workshop include:
Spreadsheets, organising data and first steps with R
Manipulating and analysing data with dplyr
Data visualisation
Summarized experiments and getting started with Bioconductor
This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative.
Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.
Files and materials included in this record:
Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Index 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.
Schedule (PDF): A breakdown of the topics and timings for the workshop
Recommended resources (PDF): A list of resources recommended by trainers and participants
Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel.
Materials shared elsewhere:
This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available.
https://saskiafreytag.github.io/biocommons-r-intro/
This is derived from material produced as part of The Carpentries Incubator project
https://carpentries-incubator.github.io/bioc-intro/
Melissa Burke (melissa@biocommons.org.au)
Freytag, Saskia (orcid: 0000-0002-2185-7068)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Doyle, Maria
Ansell, Brendan (orcid: 0000-0003-0297-897X)
Varshney, Akriti
Bourke, Caitlin (orcid: 0000-0002-4466-6563)
Conradsen, Cara (orcid: 0000-0001-9797-3412)
Jung, Chol-Hee (orcid: 0000-0002-2992-3162)
Sandoval, Claudia
Chandrananda, Dineika (orcid: 0000-0002-8834-9500)
Zhang, Eden (orcid: 0000-0003-0294-3734)
Rosello, Fernando (orcid: 0000-0003-3885-8777)
Iacono, Giulia (orcid: 0000-0002-1527-0754)
Tarasova, Ilariya (orcid: 0000-0002-0895-9385)
Chung, Jessica (orcid: 0000-0002-0627-0955)
Moffet, Joel
Gustafsson, Johan (orcid: 0000-0002-2977-5032)
Ding, Ke
Feher, Kristen
Perlaza-Jimenez, Laura (orcid: 0000-0002-8511-1134)
Crowe, Mark (orcid: 0000-0002-9514-2487)
Ma, Mengyao
Kandhari, Nitika (orcid: 0000-0002-0261-727X)
Williams, Sarah
Nelson, Tiffanie (orcid: 0000-0002-5341-312X)
Schreiber, Veronika (orcid: 0000-0001-6088-7828)
Pinzon Perez, William
Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WORKSHOP: Working with genomics sequences and features in R with Bioconductor
This record includes training materials associated with the Australian BioCommons workshop ‘Working with genomics sequences and features in R with Bioconductor’. This workshop took place on 23 September 2021.
Workshop description
Explore the many useful functions that the Bioconductor...
Keywords: R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis
WORKSHOP: Working with genomics sequences and features in R with Bioconductor
https://zenodo.org/records/5781776
https://dresa.org.au/materials/workshop-working-with-genomics-sequences-and-features-in-r-with-bioconductor-8399bf0d-1e9e-48f3-a840-3f70f23254bb
This record includes training materials associated with the Australian BioCommons workshop ‘Working with genomics sequences and features in R with Bioconductor’. This workshop took place on 23 September 2021.
Workshop description
Explore the many useful functions that the Bioconductor environment offers for working with genomic data and other biological sequences.
DNA and proteins are often represented as files containing strings of nucleic acids or amino acids. They are associated with text files that provide additional contextual information such as genome annotations.
This workshop provides hands-on experience with tools, software and packages available in R via Bioconductor for manipulating, exploring and extracting information from biological sequences and annotation files. We will look at tools for working with some commonly used file formats including FASTA, GFF3, GTF, methods for identifying regions of interest, and easy methods for obtaining data packages such as genome assemblies.
This workshop is presented by the Australian BioCommons and Monash Bioinformatics Platform with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative.
Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.
Files and materials included in this record:
Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.
Index 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.
Schedule (PDF): schedule for the workshop providing a breakdown of topics and timings
Materials shared elsewhere:
This workshop follows the tutorial ‘Working with DNA sequences and features in R with Bioconductor - version 2’ developed for Monash Bioinformatics Platform and Monash Data Fluency by Paul Harrison.
https://monashdatafluency.github.io/r-bioc-2/
Melissa Burke (melissa@biocommons.org.au)
Harrison, Paul (orcid: 0000-0002-3980-268X)
Deshpande, Nandan (orcid: 0000-0002-0324-8728)
Barugahare, Adele (orcid: 0000-0002-8976-0094)
Perry, Andrew (orcid: 0000-0001-9256-6068)
Wong, Nick (orcid: 0000-0003-4393-7541)
Reames, Benjamin
R software, Bioconductor, Bioinformatics, Analysis, Genomics, Sequence analysis
An open source textbook for research software engineering
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...
Keywords: data skills, software skills, open source, research software, research software engineering, training material
An open source textbook for research software engineering
https://zenodo.org/records/4287860
https://dresa.org.au/materials/an-open-source-textbook-for-research-software-engineering-f275be2a-698e-4e8a-94a4-5b701b26eef8
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 & 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.
contact@ardc.edu.au
Irving, Damien (orcid: 0000-0003-1258-5002)
data skills, software skills, open source, research software, research software engineering, training material
Data Fluency: a community of practice supporting a digitally skilled workforce
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,...
Keywords: skills, training, eresearch skills, data skills, online learning, pedagogy, train the trainer, digitally skilled workforce, training material
Data Fluency: a community of practice supporting a digitally skilled workforce
https://zenodo.org/records/4287752
https://dresa.org.au/materials/data-fluency-a-community-of-practice-supporting-a-digitally-skilled-workforce-b911a1a8-0331-496e-95a6-0015a12acc34
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.
The 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.
contact@ardc.edu.au
Groenewegen, David (orcid: 0000-0003-2523-1676)
skills, training, eresearch skills, data skills, online learning, pedagogy, train the trainer, digitally skilled workforce, training material
ARDC Skills Landscape
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...
Keywords: skills, data skills, eresearch skills, community, skilled workforce, FAIR, research data management, data stewardship, data governance, data use, data generation, training material
ARDC Skills Landscape
https://zenodo.org/records/4287743
https://dresa.org.au/materials/ardc-skills-landscape-56b224ca-9e30-4771-8615-d028c7be86a6
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.
In 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:
- Siloed skills initiatives, and finding ways to build partnerships and improve collaboration
- Skills deficits, and working to address the gaps in data skills
- Areas of skills development for investment by skills stakeholders like universities, research organisations, skills and training service providers, ARDC, etc.
contact@ardc.edu.au
Unsworth, Kathryn (orcid: 0000-0002-5407-9987)
skills, data skills, eresearch skills, community, skilled workforce, FAIR, research data management, data stewardship, data governance, data use, data generation, training material
Developing an organisation-wide framework to transform and uplift data capabilities
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...
Keywords: data skills, research data framework, data management, data governance, data skills uplift, data capabilities, skills development, innovative technologies, stakeholder engagement, training material
Developing an organisation-wide framework to transform and uplift data capabilities
https://zenodo.org/records/4287866
https://dresa.org.au/materials/developing-an-organisation-wide-framework-to-transform-and-uplift-data-capabilities-dfc4f34d-3b4e-4d2b-88bb-7b0ca5266798
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.
The 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.
contact@ardc.edu.au
Campbell, Belinda
data skills, research data framework, data management, data governance, data skills uplift, data capabilities, skills development, innovative technologies, stakeholder engagement, training material
Monash University - University of Queensland training partnership in Data science and AI
We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning,...
Keywords: data skills, training partnerships, data science, AI, training material
Monash University - University of Queensland training partnership in Data science and AI
https://zenodo.org/records/4287864
https://dresa.org.au/materials/monash-university-university-of-queensland-training-partnership-in-data-science-and-ai-8082bf73-d20f-4214-ad8c-95123e25a36c
We describe the peer network exchange for training that has been recently created via an ARDC funded partnership between Monash University and Universities of Queensland under the umbrella of the Queensland Cyber Infrastructure Foundation (QCIF). As part of a training program in machine learning, visualisation, and computing tools, we have established a series of over 20 workshops over the year where either Monash or QCIF hosts the event for some 20-40 of their researchers and students, while some 5 places are offered to participants from the other institution. In the longer term we aim to share material developed at one institution and have trainers present it at the other. In this talk we will describe the many benefits we have found to this approach including access to a wider range of expertise in several rapidly developing fields, upskilling of trainers, faster identification of emerging training needs, and peer learning for trainers.
contact@ardc.edu.au
Tang, Titus
data skills, training partnerships, data science, AI, training material
National skills ecosystem - call to action
In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4.
Skilled trainers / facilitators
National training registry
National training event calendar
Jointly developed training
Research...
Keywords: national skills initiatives, data skills, training, skills community, training material
National skills ecosystem - call to action
https://zenodo.org/records/4289335
https://dresa.org.au/materials/national-skills-ecosystem-call-to-action-ffd9b4ed-b557-496b-ac35-72467c03c71b
In this Community Action session working groups will be formed based on the challenges/opportunities that were prioritised in Community Action session #4.
- Skilled trainers / facilitators
- National training registry
- National training event calendar
- Jointly developed training
- Research support professionals: career/progression
contact@ardc.edu.au
Padmanabhan, Komathy
Backhaus, Ann
Papaioannou, Anastasios (orcid: 0000-0002-8959-4559)
Tang, Titus
Crowe, Mark (orcid: 0000-0002-9514-2487)
Vanichkina, Darya (orcid: 0000-0002-0406-164X)
Unsworth, Kathryn (orcid: 0000-0002-5407-9987)
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
national skills initiatives, data skills, training, skills community, training material
Managing Data using Acacia @ Pawsey
Acacia is Pawsey's "warm tier" or project storage. This object store is fully integrated with Setonix, Pawsey's main supercomputer, enabling fast transfer of data for project use.
These short videos introduce this high-speed object storage for hosting research data online.
Acacia is named...
Keywords: data, data skills, Acacia, Pawsey Supercomputing Centre, object storage, File systems
Managing Data using Acacia @ Pawsey
https://www.youtube.com/playlist?list=PLmu61dgAX-aYxrbqtSYHS1ufVZ9xs1AnI
https://dresa.org.au/materials/managing-data-using-acacia-pawsey
Acacia is Pawsey's "warm tier" or project storage. This object store is fully integrated with Setonix, Pawsey's main supercomputer, enabling fast transfer of data for project use.
These short videos introduce this high-speed object storage for hosting research data online.
Acacia is named after Australia’s national floral emblem the Golden Wattle – Acacia pycnantha.
training@pawsey.org.au
Pawsey Supercomputing Research Centre
data, data skills, Acacia, Pawsey Supercomputing Centre, object storage, File systems
ugrad
masters
phd
ecr
researcher
support
professional
Introducing Computational Thinking
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.
The workshop will not teach computer programming per se. Instead...
Keywords: computational skills, data skills
Resource type: tutorial
Introducing Computational Thinking
https://griffithunilibrary.github.io/intro-computational-thinking/
https://dresa.org.au/materials/introducing-computational-thinking
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.
The workshop will not teach computer programming per se. Instead it will cover the thought processes involved should you want to learn to program.
s.stapleton@griffith.edu.au
Belinda Weaver
computational skills, data skills
Advanced Data Wrangling with OpenRefine
This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine.
Keywords: data skills, data
Resource type: tutorial
Advanced Data Wrangling with OpenRefine
https://griffithunilibrary.github.io/advanced-data-wrangle-2/
https://dresa.org.au/materials/advanced-data-wrangling-with-openrefine
This online self-paced workshop teaches advanced data wrangling skills including combining datasets, geolocating data, and “what if” exploration using OpenRefine.
s.stapleton@griffith.edu.au
Sharron Stapleton
data skills, data
mbr
phd
ecr
researcher
support
professional
Introduction to Data Cleaning with OpenRefine
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...
Keywords: data skills, Data analysis
Resource type: tutorial
Introduction to Data Cleaning with OpenRefine
https://griffithunilibrary.github.io/data-cleaning-intro/
https://dresa.org.au/materials/introduction-to-data-cleaning-with-openrefine
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.
s.stapleton@griffith.edu.au;
Sharron Stapleton
data skills, Data analysis
mbr
phd
ecr
researcher
support
professional
VOSON Lab Code Blog
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.
Keywords: visualisation, Data analysis, data collections, R software, Social network analysis, social media data, Computational Social Science, quantitative, Text Analytics
Resource type: tutorial, other
VOSON Lab Code Blog
https://vosonlab.github.io/
https://dresa.org.au/materials/voson-lab-code-blog
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.
robert.ackland@anu.edu.au
visualisation, Data analysis, data collections, R software, Social network analysis, social media data, Computational Social Science, quantitative, Text Analytics
researcher
support
phd
masters