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Authors: Dow, Ellen (orcid: 0000-000...  or Liffers, Matthias (orcid: 0...  or Brian Ballsun-Stanton 

WEBINAR: KBase - A knowledge base for systems biology

This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.

Event description 

Developed for bench biologists and bioinformaticians, The Department of Energy Systems...

Keywords: Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology

WEBINAR: KBase - A knowledge base for systems biology https://dresa.org.au/materials/webinar-kbase-a-knowledge-base-for-systems-biology-653d9753-989d-4194-9230-6e2d90652955 This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021. Event description  Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a free, open source, software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function. This webinar will provide an overview of the KBase mission and user community, as well as a tour of the online platform and basic functionality. You’ll learn how KBase can support your research: Upload data, run analysis tools (Apps), share your analysis with collaborators, and publish your data and reproducible workflows. We’ll highlight a brand new feature that enables users to link environment and measurement data to sequencing data. You’ll also find out how KBase supports findable, accessible, interoperable, and reusable (FAIR) research by providing open, reproducible, shareable bioinformatics workflows. 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. Q&A for Australian BioCommons KBase Webinar [PDF]: Document containing answers to questions asked during the webinar and links to additional resources Introduction to KBase: Australian BioCommons Webinar [PDF]: Slides presented during the webinar Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/tJ94i9gOJfU The slides are also available as Google slides:  https://tinyurl.com/KBase-webinar-slides Melissa Burke (melissa@biocommons.org.au) Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
23 (research data) Things

23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:

  • Getting started
  • Learn more
  • Challenge me

All resources used in the program are online...

Keywords: research data management, training material

23 (research data) Things https://dresa.org.au/materials/23-research-data-things-793872d2-c221-4cd6-91be-11a313c74b78 23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity: * Getting started * Learn more * Challenge me All resources used in the program are online and free to use and reuse under a Creative Commons Attribution 4.0 International licence. You could use all of them as a self-paced course, or choose components to integrate into your own course. The 23 things are designed to build knowledge as the program progresses, so if you’re new to the world of research data management, we suggest you start with things 1-3 and then decide where you want to go from there. These materials supported an international community-based training program delivered in 2016 by the Australian National Data Service. This release migrates these materials to a GitHub repository for continued maintenance. Some updates were made to material that was outdated. We welcome contributions and suggestions via GitHub Issue or Pull Request. contact@ardc.edu.au research data management, training material
Software publishing, licensing and citation

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...

Keywords: software, code, Repositories, code sharing, training material

Software publishing, licensing and citation https://dresa.org.au/materials/software-publishing-licensing-and-citation-49097378-f296-44aa-b724-a57d22214d99 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. This session explained why and how to publish, licence and cite software. A video recording of this session can also be found on ARDC's YouTube channel: https://youtu.be/l2acLeuF_QE contact@ardc.edu.au software, code, Repositories, code sharing, 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://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 national skills initiatives, data skills, training, skills community, training material
Software publishing, licensing, and citation

A short presentation for reuse includes speaker notes.

Making software citable using a code repository, an ORCID and a licence.

Keywords: Software citation, Software publishing, Software registries, Software Repositories, research Software, training material

Software publishing, licensing, and citation https://dresa.org.au/materials/software-publishing-licensing-and-citation-d222144f-380a-455d-b4aa-c56283afc23e A short presentation for reuse includes speaker notes. Making software citable using a code repository, an ORCID and a licence. contact@ardc.edu.au Martinez, Paula Andrea (type: ProjectLeader) Software citation, Software publishing, Software registries, Software Repositories, research Software, training material
ARDC FAIR Data 101 self-guided

FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles

The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.

The course structure was based on 'FAIR Data in the...

Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097 FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course. The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub. contact@ardc.edu.au training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
ARDC Guide to making software citable

A short guide to making software citable using a code repository, an ORCID and a licence.

Keywords: Software citation, Software publishing, Software registries, Software repositories, Research software, training material

ARDC Guide to making software citable https://dresa.org.au/materials/ardc-guide-to-making-software-citable-46d0f9e4-ef55-43b9-b237-3e52a9d1e141 A short guide to making software citable using a code repository, an ORCID and a licence. contact@ardc.edu.au Martinez, Paula Andrea (type: ProjectLeader) Software citation, Software publishing, Software registries, Software repositories, Research software, training material
A hands on introduction to Large Language Models like Bing Chat and ChatGPT

Event run 7 June at the MQ Incubator. Event description:

A two-hour hands-on workshop giving a brief history of the last 4 months of development of "Generative AI."

These tools, these Large Language Models, offer present promise and peril -- disruption -- to ways of working and of...

Keywords: Large Language Model, ChatGPT

A hands on introduction to Large Language Models like Bing Chat and ChatGPT https://dresa.org.au/materials/a-hands-on-introduction-to-large-language-models-like-bing-chat-and-chatgpt Event run 7 June at the MQ Incubator. Event description: A two-hour hands-on workshop giving a brief history of the last 4 months of development of "Generative AI." These tools, these Large Language Models, offer present promise and peril -- disruption -- to ways of working and of learning. Outside the "hype," these tools are "calculators for words" and allow the same manipulation and reflection of a user's words as a calculator offers for a user's numbers. The workshop will guide users into using various free and paid tools, and the effective use of Large Language Models through chain of thought prompting. Remember: a LLM is "Always confident and usually correct." OSF Description (LLM generated): This two-hour workshop provides a comprehensive introduction to the world of Large Language Models (LLMs), focusing on the recent advancements in Generative AI. Participants will gain insights into the development and functionality of prominent LLMs such as Bing Chat and ChatGPT. The workshop will delve into the concept of LLMs as "calculators for words," highlighting their potential to revolutionize ways of working and learning. The session will explore the principles of Prompt Engineering and Transactional Prompting, demonstrating how consistent prompts can yield reliable and reproducible results. Participants will also learn about the practical applications of LLMs, including editing and proofreading papers, generating technical documentation, recipe ideation, and more. The workshop emphasizes the importance of understanding the terms of use and the responsibilities that come with using these powerful AI tools. By the end of the session, participants will be equipped with the knowledge and skills to effectively use LLMs in various contexts, guided by the mantra that a LLM is "Always confident and usually correct." Brian Ballsun-Stanton (brian.ballsun-stanton@mq.edu.au) Large Language Model, ChatGPT researcher
Managing Active Research Data

In this train-the-trainer workshop, we will be exploring and discussing methods for active data management.

Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data,...

Keywords: RDM Training, CloudStor, cloud

Resource type: lesson

Managing Active Research Data https://dresa.org.au/materials/managing-active-research-data In this train-the-trainer workshop, we will be exploring and discussing methods for active data management. Participants will become familiar with cloud storage and associated tools and services for managing active research data. Learn how to organise, maintain, store and analyse active data, and understand safe and secure ways of sharing and storing data. Topics such as cloud storage, collaborative editing, versioning and data sharing will be discussed and demonstrated. Sara King RDM Training, CloudStor, cloud phd support masters ecr researcher
ARDC Datacite API Jupyter notebook

This Jupyter notebook presents a low-barrier entry to using the DataCite REST API to mint, update, publish, and deleted DOIs and their associated metadata.

It was designed specifically to not use any third-party libraries so that it can be reused in almost any Jupyter notebook environment

Code...

Keywords: jupyter, notebook, DataCite, api, python, metadata, DOI, training material

ARDC Datacite API Jupyter notebook https://dresa.org.au/materials/ardc-datacite-api-jupyter-notebook This Jupyter notebook presents a low-barrier entry to using the DataCite REST API to mint, update, publish, and deleted DOIs and their associated metadata. It was designed specifically to not use any third-party libraries so that it can be reused in almost any Jupyter notebook environment Code is presented alongside human readable comments that explain the use of each component of the notebook. contact@ardc.edu.au jupyter, notebook, DataCite, api, python, metadata, DOI, training material
Research Data Management (RDM) Online Orientation Module (Macquarie University)

This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify.
The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata,...

Keywords: research data, data management, FAIR data, training

Resource type: quiz, activity, other

Research Data Management (RDM) Online Orientation Module (Macquarie University) https://dresa.org.au/materials/macquarie-university-research-data-management-rdm-online This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify. The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata, benefits of data sharing, licensing, repositories, and best practice including the FAIR principles. Embedded activities and examples help extend learner experience and awareness. The course was designed to assist research students and early career researchers in complying with policies and legislative requirements, understand safe data practices, raise awareness of the benefits of data curation and data sharing (efficiency and impact) and equip them with the required knowledge to plan their data management early in their projects. This course is divided into four sections 1. Crawl - What is Research Data and why care for it? Policy and legislative requirements. The Research Data Life-cycle. Data Management Planning (~30 mins) 2. Walk - Data sensitivity, identifiability, storage, and security (~60 mins) 3. Run - Record keeping, data retention, file naming, folder structures, version control, metadata, data sharing, open data, licences, data repositories, data citation, and ethics (~75 mins) 4. Jump - Best practice FAIR data principles (~45 mins) 5. Fight - Review - a quiz designed to review and reinforce knowledge (~15 mins) https://rise.articulate.com/share/-AWqSPaEI_jTbHwzQHdmQ43R50edrCl0 * *Password: "FAIR" *Password: "FAIR" Any queries or suggestions for course improvement can be directed to the Macquarie University Research Integrity Team: Dr Paul Sou (paul.sou@mq.edu.au) or Dr Shannon Smith (shannon.smith@mq.edu.au). Scorm files can be made available upon request. research data, data management, FAIR data, training