FAIR Data Principles
Introduction to Scientific Visualization
Scientific Visualization transforms numerical data sets obtained through measurements or computations into graphical representations. Interactive visualization systems allow scientists, engineers, and biomedical researchers to explore and analyze a variety of phenomena in an intuitive and effective way. The course provides an introduction to the principles and techniques of Scientific Visualization. It covers methods corresponding to the visualization of the most common data types, as well as higher-dimensional, so-called multi-field problems. It combines a description of visualization algorithms with a presentation of their practical application. Basic notions of computer graphics and human visual perception are introduced early on for completeness. Simple but very instructive programming assignments offer a hands-on exposure to the most widely used visualization techniques.
Note that the lectures, demonstration, and tutorial content require a Purdue Credentials,Hydroshare, or CILogon account.
Access the CCSM Portal/ESG/ESGC Integration slide presentation at https://mygeohub.org/resources/50/download/ccsm.pdf. The CCSM/ESG/ESGC collaboration provides a semantically enabled environment that includes modeling, simulated and observed data, visualization, and analysis.
- CCSM Overview
- CCSM on the TeraGrid
- Steps in a typical CCSM Simulation
- Climate Modeling Portal: Community Climate System Model (CCSM) to simulate climate change on Earth
- CCSM Self-Describing Workflows
- Provenance metadata collection
23 (research data) Things
23 (research data) Things is self-directed learning for anybody who wants to know more about research data. Anyone can do 23 (research data) Things at any time. Do them all, do some, cherry-pick the Things you need or want to know about. Do them on your own, or get together a Group and share the learning. The program is intended to be flexible, adaptable and fun!
Each of the 23 Things offers a variety of learning opportunities with activities at three levels of complexity: ‘Getting started’, ‘Learn more’ and ‘Challenge me’. All resources used in the program are online and free to use.
Introduction: FAIR Principles and Management Plans
This presentation introducing the FAIR (Findable Accessible Interoperable Re-usable) data principles and management plans is one of 9 webinars on topics related to FAIR Data and Software that was offered at a Carpentries-based Workshop in Hannover, Germany, Jul 9-13 2018. Presentation slides are also available in addition to the recorded presentation.
Other topics included in the series include:
- Findability of Research Data and Software through PIDs and FAIR
- Accessibility through Git, Python Funcations and Their Documentation
- Interoperability through Python Modules, Unit-Testing and Continuous Integration
- Reusability through Community Standards, Tidy Data Formats and R Functions, their Documentation, Packaging, and Unit-Testing
- Reusability: Data Licensing
- Reusability: Software Licensing
- Reusability: Software Publication
- FAIR Data and Software - Summary
URL locations for the other modules in the webinar can be found at the URL above.
Research Data Management and Open Data
This was a presentation during the Julius Symposium 2017 on Open Science and in particular on Open data and/or FAIR data. Examples are given of medical and health research data.