[{"id":347,"title":"ARDC Digital Research Capabilities and Skills Framework: The Framework and Its Components","url":"https://staging.dresa.org.au/materials/ardc-digital-research-capabilities-and-skills-framework-the-framework-and-its-components.json","description":"The ARDC's Digital Research Capabilities and Skills Framework, released in 2022, provides a structure for training programs to develop essential and advanced digital research skills. It aims to help researchers and professionals identify the necessary skills they need to leverage emerging opportunities in data management, data analysis, data linking, AI, and machine learning. The framework aligns with technological advancements and encourages ongoing discussion and contributions to evolve the coverage of digital research skills. \nThe framework focuses on digital research skills, excluding broader professional skills, and is intended for a wide range of stakeholders. It provides a structured approach for project teams and organisations to develop and enhance their digital research skills through six main components: a skills taxonomy, a skills glossary, a list of generalised roles, roles and skills-related profiles, learning paths, and a skills and roles matrix. The skills taxonomy classifies digital research skills into four capability families: Governance, Data, Software, and Digital Research Infrastructure Management. It provides a standard terminology for identifying and describing these skills.","doi":"10.5281/zenodo.14188836","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":339,"title":"ARDC Skills Landscape","url":"https://staging.dresa.org.au/materials/ardc-skills-landscape-dd7401f0-702a-4813-b651-28d7cedf5c40.json","description":"The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its purpose of providing Australian researchers with a competitive advantage through data.  \n\nIn this presentation, Kathryn Unsworth introduces the ARDC Skills Landscape. The Landscape is a first step in developing a national skills framework to enable a coordinated and cohesive approach to skills development across the Australian eResearch sector. It is also a first step towards helping to analyse current approaches in data training to identify:\n- Siloed skills initiatives, and finding ways to build partnerships and improve collaboration\n- Skills deficits, and working to address the gaps in data skills\n- Areas of skills development for investment by skills stakeholders like universities, research organisations, skills and training service providers, ARDC, etc.\n\n ","doi":"10.5281/zenodo.4287743","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":338,"title":"Developing an organisation-wide framework to transform and uplift data capabilities","url":"https://staging.dresa.org.au/materials/developing-an-organisation-wide-framework-to-transform-and-uplift-data-capabilities-58f678ce-fbae-4b74-818d-49116a6a8eb8.json","description":"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.\n\nThe 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.","doi":"10.5281/zenodo.4287866","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":333,"title":"Research Data Governance","url":"https://staging.dresa.org.au/materials/research-data-governance-1b84a9f4-8c7f-40c2-9658-dd2ee4b50d9d.json","description":"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.\n\nIf you want to share the video please use this:\n\nAustralian 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].","doi":"10.5281/zenodo.5044585","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":319,"title":"Role profiles for the Bureau's Stewardship Model","url":"https://staging.dresa.org.au/materials/role-profiles-for-the-bureau-s-stewardship-model-a93be8ba-4ca4-4d5b-8eef-d853c77c42f8.json","description":"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.\n\nYou can watch the YouTube video here: https://youtu.be/RLf6B-NIffU","doi":"10.5281/zenodo.5711869","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":173,"title":"Research Data Governance","url":"https://staging.dresa.org.au/materials/research-data-governance.json","description":"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.\n\nIf you want to share the video please use this:\n\nAustralian 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].","doi":"10.5281/zenodo.5044585","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":186,"title":"Developing an organisation-wide framework to transform and uplift data capabilities","url":"https://staging.dresa.org.au/materials/developing-an-organisation-wide-framework-to-transform-and-uplift-data-capabilities.json","description":"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.\n\nThe 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.","doi":"10.5281/zenodo.4287866","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":188,"title":"ARDC Skills Landscape","url":"https://staging.dresa.org.au/materials/ardc-skills-landscape.json","description":"The Australian Research Data Commons is driving transformational change in the research data ecosystem, enabling researchers to conduct world class data-intensive research. One interconnected component of this ecosystem is skills development/uplift, which is critical to the Commons and its purpose of providing Australian researchers with a competitive advantage through data.  \n\nIn this presentation, Kathryn Unsworth introduces the ARDC Skills Landscape. The Landscape is a first step in developing a national skills framework to enable a coordinated and cohesive approach to skills development across the Australian eResearch sector. It is also a first step towards helping to analyse current approaches in data training to identify:\n- Siloed skills initiatives, and finding ways to build partnerships and improve collaboration\n- Skills deficits, and working to address the gaps in data skills\n- Areas of skills development for investment by skills stakeholders like universities, research organisations, skills and training service providers, ARDC, etc.\n\n ","doi":"10.5281/zenodo.4287743","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":204,"title":"Role profiles for the Bureau's Stewardship Model","url":"https://staging.dresa.org.au/materials/role-profiles-for-the-bureau-s-stewardship-model.json","description":"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.\n\nYou can watch the YouTube video here: https://youtu.be/RLf6B-NIffU","doi":"10.5281/zenodo.5711869","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]}]