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Keywords: training material 

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Authors: Dow, Ellen (orcid: 0000-000...  or Bonu, Tarun (orcid: 0000-00...  or Simons, Natasha (orcid: 000... 

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://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 policy, data policy, publishers, training material
ML4AU: Trainings, trainers and building an ML community

This lightning talk provides an update on the current state of machine lerning training activities. Additionally, the talk will introduce the training portal on the ML4AU website, which has been created to address some of the challenges faced by the trainer community.

You can watch the YouTube...

Keywords: machine learning, training, skills, community of practice, trainers, training material

ML4AU: Trainings, trainers and building an ML community https://dresa.org.au/materials/ml4au-trainings-trainers-and-building-an-ml-community-891b095f-91c2-461d-8039-1c25f50f5857 This lightning talk provides an update on the current state of machine lerning training activities. Additionally, the talk will introduce the training portal on the ML4AU website, which has been created to address some of the challenges faced by the trainer community. You can watch the YouTube video here: https://youtu.be/cQS0guC5_Cg contact@ardc.edu.au machine learning, training, skills, community of practice, trainers, 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
ML4AU: Trainings, trainers and building an ML community

This lightning talk provides an update on the current state of machine lerning training activities. Additionally, the talk will introduce the training portal on the ML4AU website, which has been created to address some of the challenges faced by the trainer community.

You can watch the YouTube...

Keywords: machine learning, training, skills, community of practice, trainers, training material

ML4AU: Trainings, trainers and building an ML community https://dresa.org.au/materials/ml4au-trainings-trainers-and-building-an-ml-community This lightning talk provides an update on the current state of machine lerning training activities. Additionally, the talk will introduce the training portal on the ML4AU website, which has been created to address some of the challenges faced by the trainer community. You can watch the YouTube video here: https://youtu.be/cQS0guC5_Cg contact@ardc.edu.au machine learning, training, skills, community of practice, trainers, 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-bba41a59-8479-4f4f-b9ee-337b9eb294bf 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
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://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 policy, data policy, publishers, training material