Why Validate? VIS design space is huge, and mostly ineffective. it is valuable to think how to validate from the very beginning of the design process. Nested Model → Guidance on when to ...

Why abstract Task? domain-specific 한 방법보다는 abstract 하게 task를 고려해야한다. → 그렇지 않으면, 도메인마다 너무 task가 달라짐. Actions High-level: Analyze Mid-level: Search Low-level: Query hierarchical하게 나눠짐. 각...

What? Why do data semantics and types matter? Data attributes define real-world meaning. (e.g. Basil, 7, S, Pear) Type of the data: Structural interpretation Data Level: Data Types item, at...

I. intro. AI Venn Diagram AI: Create a machine that can think like humans. (Contains) Machine learning (Contains) Representation lear...

SciVis vs. InfoVis SciVis Spatial representations are given or have to be designed. Big Picture VIS is suitable when there is a need to augment human capabilities Design visual represe...

InfoVis vs. SciVis Scientific Visualization Visualization that deals with physical data. Ex: MRI scans, climate models has smaller design space (bound to physical space) Information Visu...

Quantitative vs Qualitative Quantitative Objectively measure human performance more narrow focus internal validity Qualitative Observe and develop understanding of human experience ...

Flynn’s Taxonomy   Single Inst. Multiple Inst. Single Data SISD: Vanilla Processor.   Single processor work on...

RAID 0 Block-level striping (without parity or mirroring) → Space efficiency: 1 → No fault tolerance. Block 하나 망가지면 망함 → High bandwidth RAID 1: Mirroring & Duplexing Mirroring (without ...