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Keywords: data management 


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://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 Kathryn Unsworth (kathryn.unsworth@ardc.edu.au) skills, training, infrastructure management, data management, TERN, ecosystems, 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://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. Kathryn Unsworth (kathryn.unsworth@ardc.edu.au) data skills, research data framework, data management, data governance, data skills uplift, data capabilities, skills development, innovative technologies, stakeholder engagement, 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://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 Kathryn Unsworth (kathryn.unsworth@ardc.edu.au) role profiles, data stewardship, data governance, data management, skills, training, 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.

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Keywords: data governance, data, research, FAIR, data management, authority, share, reuse, access, provenance, policy, responsibilities, ARDC_AU, training material

Research Data Governance 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]. Kathryn Unsworth (kathryn.unsworth@ardc.edu.au) 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
9 Reproducible Research things - Building Business Continuity

The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are...

Keywords: reproducibility, data management

Resource type: tutorial, video

9 Reproducible Research things - Building Business Continuity https://dresa.org.au/materials/9-reproducible-research-things-building-business-continuity The idea that you can duplicate an experiment and get the same conclusion is the basis for all scientific discoveries. Reproducible research is data analysis that starts with the raw data and offers a transparent workflow to arrive at the same results and conclusions. However not all studies are replicable due to lack of information on the process. Therefore, reproducibility in research is extremely important. Researchers genuinely want to make their research more reproducible, but sometimes don’t know where to start and often don’t have the available time to investigate or establish methods on how reproducible research can speed up every day work. We aim for the philosophy “Be better than you were yesterday”. Reproducibility is a process, and we highlight there is no expectation to go from beginner to expert in a single workshop. Instead, we offer some steps you can take towards the reproducibility path following our Steps to Reproducible Research self paced program. Video: https://www.youtube.com/watch?v=bANTr9RvnGg Tutorial: https://guereslib.github.io/Reproducible-Research-Things/ a.miotto@griffith.edu.au reproducibility, data management support masters phd researcher
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
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://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/ training material, FAIR data, research data, data management, FAIR phd ecr researcher support