Metadata | SSH Training Discovery Toolkit

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ARDC Training Materials Metadata Checklist v1.1	The ARDC Training Materials Metadata Checklist aims to support learning designers, training materials creators, trainers and national training infrastructure providers to capture key information and apply appropriate mechanisms to enable sharing and reuse of their training materials.
Controlled Vocabularies and SKOS training at DARIAH Campus	Training module about controlled vocabularies and SKOS. Presentation of how controlled vocabularies can be used for organizing and classifying data and how the resources can be queried, retrieved, analysed and linked to other relevant information objects.
Research Data Management and Sharing	This course will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories.
Organise and Document	Chapter on how to properly organise and document data and metadata, discussing good practices in designing an appropriate data file structure, file naming and organising data within suitable folder structures; how organising data facilitates orientation in the data file, contributes to the understanding of the information contained and helps to prevent errors and misinterpretations. Also what counts as appropriate documentation of data, development of rich metadata to make data FAIR and standards to promote data sharing. Focus on: elements which are important in setting up an appropriate structure for organising data for intended research work and data sharing overview of best practices in file naming and organising data files in a well-structured and unambiguous folder structure how comprehensive data documentation and metadata increases the chance data are correctly understood and discovered common metadata standards and their value relevant DMP questions on this topic.

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Australian Research Data Commons Training Materials	The ARDC is a transformational initiative that enables Australian research community and industry access to nationally significant, leading edge data intensive eInfrastructure, platforms, skills and collections of high-quality data. The purpose of the ARDC is to provide Australian researchers with competitive advantage through data, providing access to leading edge eResearch collections, tools, infrastructure and services. Its mission is to accelerate research and innovation by driving excellence in the creation, analysis and retention of high-quality data assets.
Research Data Mantra	Free online course for those who manage digital data as part of the research process. It has been created for the use of post-graduate students, early career researchers, and also information professionals. There are eight online units in this course and four data handling tutorials that will help you: Understand the nature of research data in a variety of disciplinary settings Create a data management plan and apply it from the start to the finish of your research project Name, organise, and version your data files effectively Gain familiarity with different kinds of data formats and know how and when to transform your data Document your data well for yourself and others, learn about metadata standards and cite data properly Know how to store and transport your data safely and securely (backup and encryption) Understand legal and ethical requirements for managing data about human subjects; manage intellectual property rights Understand the benefits of sharing, preserving and licensing data for re-use Improve your data handling skills in one of four software environments: R, SPSS, NVivo, or ArcGIS Each unit takes up to one hour, plus time for further reading and carrying out the data handling exercises. In the units you will find explanations, descriptions, examples, exercises, and video clips in which academics, PhD students and others talk about the challenges of managing research data.