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
Data Policy
Increasing the availability of research data for reuse is in part being driven by research data policies. While the number of research funders, journals and institutions with some form of research data policy is growing, the landscape is complex and therefore the implementation and implications...
Keywords: policy, data policy, publishers, training material
Data Policy
https://zenodo.org/records/4922756
https://dresa.org.au/materials/data-policy-c8bc856f-0afa-49dc-b100-36e9a8375327
Increasing the availability of research data for reuse is in part being driven by research data policies. While the number of research funders, journals and institutions with some form of research data policy is growing, the landscape is complex and therefore the implementation and implications of policies for researchers can be unclear, confusing and sometimes even contradictory. The RDA Data Policy Standardisation and Implementation IG was established to help address these challenges.
Initially the Group focussed on Developing a Research Data Policy Framework for All Journals and Publishers and with journal adoptions of the framework growing, the Group is now focussing on alignment between publishers and funders. This session provided an overview of the joint session held at RDA P17 of the Research Funders and Stakeholders on Open Research and Data Management and Practices IG, the Data Policy Standardisation and Implementation IG and the FAIRsharing WG.
The focus of this RDA VP17 session was to provide an overview of a joint project to examine funder-publisher policy alignment and provide recommendations on how to improve alignment.
contact@ardc.edu.au
Simons, Natasha (orcid: 0000-0003-0635-1998)
policy, data policy, publishers, 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
ARDC Research Data Rights Management Guide
A practical guide for people and organisations working with data, about rights information and licences, and to raise awareness of the implications of not having licences on data.
Who is this for? This guide is primarily directed toward members of the research sector, particularly data rights...
Keywords: data, rights, management, licence, licensing, research, policy, guide, training material
ARDC Research Data Rights Management Guide
https://zenodo.org/records/5091580
https://dresa.org.au/materials/ardc-research-data-rights-management-guide-149e27b4-fd5e-4739-8e40-be2c5ca6709c
A practical guide for people and organisations working with data, about rights information and licences, and to raise awareness of the implications of not having licences on data.
Who is this for? This guide is primarily directed toward members of the research sector, particularly data rights holders users and suppliers. Some general reference is made to characteristics and management of government data, acknowledging that this kind of data can be input to the research process. Government readers should consult their agency’s data management policies, in addition to reading this guide.
contact@ardc.edu.au
Australian Research Data Commons
Laughlin, Greg (type: Editor)
Appleyard, Baden (type: Editor)
data, rights, management, licence, licensing, research, policy, guide, 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
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
Data Policy
Increasing the availability of research data for reuse is in part being driven by research data policies. While the number of research funders, journals and institutions with some form of research data policy is growing, the landscape is complex and therefore the implementation and implications...
Keywords: policy, data policy, publishers, training material
Data Policy
https://zenodo.org/record/4922756
https://dresa.org.au/materials/data-policy
Increasing the availability of research data for reuse is in part being driven by research data policies. While the number of research funders, journals and institutions with some form of research data policy is growing, the landscape is complex and therefore the implementation and implications of policies for researchers can be unclear, confusing and sometimes even contradictory. The RDA Data Policy Standardisation and Implementation IG was established to help address these challenges.
Initially the Group focussed on Developing a Research Data Policy Framework for All Journals and Publishers and with journal adoptions of the framework growing, the Group is now focussing on alignment between publishers and funders. This session provided an overview of the joint session held at RDA P17 of the Research Funders and Stakeholders on Open Research and Data Management and Practices IG, the Data Policy Standardisation and Implementation IG and the FAIRsharing WG.
The focus of this RDA VP17 session was to provide an overview of a joint project to examine funder-publisher policy alignment and provide recommendations on how to improve alignment.
contact@ardc.edu.au
Simons, Natasha (orcid: 0000-0003-0635-1998)
policy, data policy, publishers, training material
ARDC Research Data Rights Management Guide
A practical guide for people and organisations working with data, about rights information and licences, and to raise awareness of the implications of not having licences on data.
Who is this for? This guide is primarily directed toward members of the research sector, particularly data rights...
Keywords: data, rights, management, licence, licensing, research, policy, guide, training material
ARDC Research Data Rights Management Guide
https://zenodo.org/record/5091580
https://dresa.org.au/materials/ardc-research-data-rights-management-guide-a5c12e9a-672b-4a42-b9d1-e1315d733aae
A practical guide for people and organisations working with data, about rights information and licences, and to raise awareness of the implications of not having licences on data.
Who is this for? This guide is primarily directed toward members of the research sector, particularly data rights holders users and suppliers. Some general reference is made to characteristics and management of government data, acknowledging that this kind of data can be input to the research process. Government readers should consult their agency’s data management policies, in addition to reading this guide.
contact@ardc.edu.au
Australian Research Data Commons
Laughlin, Greg (type: Editor)
Appleyard, Baden (type: Editor)
data, rights, management, licence, licensing, research, policy, guide, training material
