Role profiles for the Bureau's Stewardship Model
This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which...
Keywords: role profiles, data stewardship, data governance, data management, skills, training, training material
Role profiles for the Bureau's Stewardship Model
https://zenodo.org/records/5711869
https://dresa.org.au/materials/role-profiles-for-the-bureau-s-stewardship-model-19ee77b4-d15e-42da-96b4-9e3056d1b3e7
This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which provide the role description, assignment and key responsibilities.
You can watch the YouTube video here: https://youtu.be/RLf6B-NIffU
contact@ardc.edu.au
Lowenstein, Sally
role profiles, data stewardship, data governance, data management, skills, training, training material
Accelerating skills development in Data science and AI at scale
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...
Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Accelerating skills development in Data science and AI at scale
https://zenodo.org/records/4287746
https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale-2d8a65fa-f96e-44ad-a026-cfae3f38d128
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally.
The talk will also cover our approach as outlined below
• Combined survey of gaps in skills and trainings for Data science and AI
• Provide seats to partners
• Share associate instructors/helpers/volunteers
• Develop combined training materials
• Publish a repository of open source trainings
• Train the trainer activities
• Establish a network of volunteers to deliver trainings at their local regions
Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community.
Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together.
contact@ardc.edu.au
Tang, Titus
AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Research Data Governance
This video contains key information for those who make research data-related decisions. It will help project leaders to start investigating ways to develop their own data governance policy, roles and responsibilities and procedures with the input of appropriate stakeholders.
If you want to share...
Keywords: data governance, data, research, FAIR, data management, authority, share, reuse, access, provenance, policy, responsibilities, ARDC_AU, training material
Research Data Governance
https://zenodo.org/records/5044585
https://dresa.org.au/materials/research-data-governance-6ad9ab90-1a29-41db-b4aa-f1988501530d
This video contains key information for those who make research data-related decisions. It will help project leaders to start investigating ways to develop their own data governance policy, roles and responsibilities and procedures with the input of appropriate stakeholders.
If you want to share the video please use this:
Australian Research Data Commons, 2021. Research Data Governance. [video] Available at: https://youtu.be/K_xVQRdgCIc DOI: http://doi.org/10.5281/zenodo.5044585 [Accessed dd Month YYYY].
contact@ardc.edu.au
Australian Research Data Commons
Martinez, Paula Andrea (type: ProjectLeader)
Wilkinson, Max (type: Editor)
Callaghan,Shannon (type: Editor)
Savill, Jo (type: Editor)
Kang, Kristan (type: Editor)
Levett, Kerry (type: Editor)
Russell, Keith (type: Editor)
Simons, Natasha (type: Editor)
data governance, data, research, FAIR, data management, authority, share, reuse, access, provenance, policy, responsibilities, ARDC_AU, 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
Skills initiatives at TERN
This presentation provides insight into current training efforts at TERN around data collection, data processing and data access and analytics. Highlighting various modes of training including hands-on data collection training, tutorials on deriving data, workshops, user manuals and training at...
Keywords: skills, training, infrastructure management, data management, TERN, ecosystems, training material
Skills initiatives at TERN
https://zenodo.org/records/5711879
https://dresa.org.au/materials/skills-initiatives-at-tern-e5ed5d17-a5c3-4da0-a240-82b01f7d1f25
This presentation provides insight into current training efforts at TERN around data collection, data processing and data access and analytics. Highlighting various modes of training including hands-on data collection training, tutorials on deriving data, workshops, user manuals and training at domain conferences. A list of resources and tools has also been provided for those interested in wanting to know more.
You can watch the video on YouTube here: https://youtu.be/mgGuKUGCu2g
contact@ardc.edu.au
Guru, Siddeswara (orcid: 0000-0002-3903-254X)
skills, training, infrastructure management, data management, TERN, ecosystems, training material
Research Data Governance
This video contains key information for those who make research data-related decisions. It will help project leaders to start investigating ways to develop their own data governance policy, roles and responsibilities and procedures with the input of appropriate stakeholders.
If you want to share...
Keywords: data governance, data, research, FAIR, data management, authority, share, reuse, access, provenance, policy, responsibilities, ARDC_AU, training material
Research Data Governance
https://zenodo.org/record/5044585
https://dresa.org.au/materials/research-data-governance-cab2ebba-4e56-418d-b52f-197619e542f8
This video contains key information for those who make research data-related decisions. It will help project leaders to start investigating ways to develop their own data governance policy, roles and responsibilities and procedures with the input of appropriate stakeholders.
If you want to share the video please use this:
Australian Research Data Commons, 2021. Research Data Governance. [video] Available at: https://youtu.be/K_xVQRdgCIc DOI: http://doi.org/10.5281/zenodo.5044585 [Accessed dd Month YYYY].
contact@ardc.edu.au
Australian Research Data Commons
Martinez, Paula Andrea (type: ProjectLeader)
Wilkinson, Max (type: Editor)
Callaghan,Shannon (type: Editor)
Savill, Jo (type: Editor)
Kang, Kristan (type: Editor)
Levett, Kerry (type: Editor)
Russell, Keith (type: Editor)
Simons, Natasha (type: Editor)
data governance, data, research, FAIR, data management, authority, share, reuse, access, provenance, policy, responsibilities, ARDC_AU, 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/record/4287866
https://dresa.org.au/materials/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 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
Skills initiatives at TERN
This presentation provides insight into current training efforts at TERN around data collection, data processing and data access and analytics. Highlighting various modes of training including hands-on data collection training, tutorials on deriving data, workshops, user manuals and training at...
Keywords: skills, training, infrastructure management, data management, TERN, ecosystems, training material
Skills initiatives at TERN
https://zenodo.org/record/5711879
https://dresa.org.au/materials/skills-initiatives-at-tern
This presentation provides insight into current training efforts at TERN around data collection, data processing and data access and analytics. Highlighting various modes of training including hands-on data collection training, tutorials on deriving data, workshops, user manuals and training at domain conferences. A list of resources and tools has also been provided for those interested in wanting to know more.
You can watch the video on YouTube here: https://youtu.be/mgGuKUGCu2g
contact@ardc.edu.au
Guru, Siddeswara (orcid: 0000-0002-3903-254X)
skills, training, infrastructure management, data management, TERN, ecosystems, training material
Role profiles for the Bureau's Stewardship Model
This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which...
Keywords: role profiles, data stewardship, data governance, data management, skills, training, training material
Role profiles for the Bureau's Stewardship Model
https://zenodo.org/record/5711869
https://dresa.org.au/materials/role-profiles-for-the-bureau-s-stewardship-model
This presentation provides an overview of the approach being taken in the creation of a Data Stewardship framework that looks at the tools, guidance, skills and clarity of data stewardship roles at the Bureau of Meteorology. A major focus of the framework is the creation of role profiles which provide the role description, assignment and key responsibilities.
You can watch the YouTube video here: https://youtu.be/RLf6B-NIffU
contact@ardc.edu.au
Lowenstein, Sally
role profiles, data stewardship, data governance, data management, skills, training, training material
Accelerating skills development in Data science and AI at scale
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities...
Keywords: AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, training material
Accelerating skills development in Data science and AI at scale
https://zenodo.org/record/4287746
https://dresa.org.au/materials/accelerating-skills-development-in-data-science-and-ai-at-scale
At the Monash Data Science and AI platform, we believe that upskilling our research community and building a workforce with data science skills are key to accelerating the application of data science in research. To achieve this, we create and leverage new and existing training capabilities within and outside Monash University. In this talk, we will discuss the principles and purpose of establishing collaborative models to accelerate skills development at scale. We will talk about our approach to identifying gaps in the existing skills and training available in data science, key areas of interest as identified by the research community and various sources of training available in the marketplace. We will provide insights into the collaborations we currently have and intend to develop in the future within the university and also nationally.
The talk will also cover our approach as outlined below
• Combined survey of gaps in skills and trainings for Data science and AI
• Provide seats to partners
• Share associate instructors/helpers/volunteers
• Develop combined training materials
• Publish a repository of open source trainings
• Train the trainer activities
• Establish a network of volunteers to deliver trainings at their local regions
Industry plays a significant role in making some invaluable training available to the research community either through self learning platforms like AWS Machine Learning University or Instructor led courses like NVIDIA Deep Learning Institute. We will discuss how we leverage our partnerships with Industry to bring these trainings to our research community.
Finally, we will discuss how we map our training to the ARDC skills roadmap and how the ARDC platforms project “Environments to accelerate Machine Learning based Discovery” has enabled collaboration between Monash University and University of Queensland to develop and deliver training together.
contact@ardc.edu.au
Tang, Titus
AI, machine learning, eresearch skills, training, train the trainer, volunteer instructors, training partnerships, 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/record/4287864
https://dresa.org.au/materials/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, 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
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.
Keywords: training material, FAIR data, research data, data management, FAIR
Resource type: presentation, quiz, activity
ARDC FAIR Data 101 self-guided
https://zenodo.org/record/5094034#.YQyLbY4zaUk
https://dresa.org.au/materials/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.
ARDC Contact us: https://ardc.edu.au/contact-us/
Liz Stokes
Matthias Liffers
Nichola Burton
Paula A. Martinez
Natasha Simons
Keith Russell
Siobhann McCafferty
Richard Ferrers
Steve McEachern
Melanie Barlow
Tom Honeyman
Maria del Mar Quiroga
training material, FAIR data, research data, data management, FAIR
phd
ecr
researcher
support