Glossary

The concepts behind information monitoring, curation and knowledge management, defined plainly and without needless jargon.

• audio-to-text transcriptionHow automatic speech recognition works, the error rate you can expect, and the five factors that wreck a transcript before the model gets a chance.
• automatic summarizationExtractive versus abstractive, how summary quality is measured, where AI summaries still fail, and the conditions that make them trustworthy at work.
• content curationSelecting, framing, publishing: what curation adds to plain link-sharing, and the habits that separate a trusted curator from an automated feed.
• information monitoringCollecting, filtering and using the information that matters without losing your week to it: method, sources, and where the process actually breaks.
• information overloadWhere the term came from, what the research measures on attention and decision quality, and which strategies cut the load instead of just moving it around.
• knowledge basePublic, internal or personal: what makes a knowledge base something people actually use instead of abandon, and why search decides its entire value.
• knowledge graphEntities, relations, ontologies: what a knowledge graph really adds over a conventional database, from Google's Knowledge Graph to note-taking graph views.
• personal knowledge management (PKM)Where PKM came from, what separates it from plain note-taking, the four systems people build practices on, and the failure mode nobody plans for.
• second brainTiago Forte's CODE method, what it promises, what it costs to maintain, and the reason most second brains quietly fall out of use within a year.
• Zettelkasten methodNiklas Luhmann’s 90,000 slips, the rules the method actually imposes, and what separates a living Zettelkasten from a folder full of forgotten notes.