Michele Pasin / Quotes

Model for data capture vs data interpretation

We make the hypothesis that much of the diversity of data and metadata structures is due to the fact, that they are designed for data capturing – as guide for good practice of what should be documented, and to optimise coding and storage costs for a specific application, by far more than for interpreting data.

Necessarily, these data structures are relatively flat (in order to suggest a workflow of entering data to the user) and full of application specific hidden constants and simplifications.

Saved 26 February 2013 / www.aaai.org ↗

#data-structure

On structuring data

Functions delay binding: data structures induce binding. Moral: Structure data late in the programming process.

Epigrams On Programming #function #structure #data-structure #process

RDF describes containers, it doesn't build them

When using RDF containers, it is important to understand that the statements are not constructing containers, as in a programming language data structure…

Rdf Primer #data-structure #structure #resources #description