This document discusses creating knowledge from interlinked data. It notes that while reasoning over large datasets does not currently scale well, linked data approaches are more feasible as they allow for incremental improvement. The document outlines the linked data lifecycle including extraction, storage and querying, authoring, linking, and enrichment of semantic data. It provides examples of projects that extract, store, author and link diverse datasets including DBpedia, LinkedGeoData, and statistical data. Challenges discussed include improving query performance, developing standardized interfaces, and increasing the amount of interlinking between datasets.