Name: Describing Data Patterns: A general deconstruction of metadata standards (en Inglés)
SKU: 59789749
Price: 73.88 PEN
Availability: InStock
Author: Voss, Jakob
ISBN: 9781490931869

portada Describing Data Patterns: A general deconstruction of metadata standards (en Inglés)

Describing Data Patterns: A general deconstruction of metadata standards (en Inglés)

Formato

Libro Físico

Autor

Jakob Voss

Editorial

Createspace

Idioma

Inglés

N° páginas

286

Encuadernación

Tapa Blanda

Dimensiones

24.4x17x1.5 cm

Peso

0.46 kg.

ISBN13

9781490931869

Categorías

Teoría de la información
Arquitectura de la información

Describing Data Patterns: A general deconstruction of metadata standards (en Inglés)

Jakob Voss (Autor) · Createspace · Tapa Blanda

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Reseña del libro "Describing Data Patterns: A general deconstruction of metadata standards (en Inglés)"

This book analyzes the methods, technologies, standards, and languages to structure and describe data in their entirety. It reveals common features, hidden assumptions, and ubiquitous patterns among these methods and shows how data are actually structured and described independently from particular trends and technologies. Examples of data structuring methods analyzed critically include: Encodings (e.g. Unicode) Identifiers and Identifier systems (e.g. ISBN) File systems Database Systems (record databases, relational databases, NoSQL...) Data structuring languages (JSON, XML, CSV, RDF...) markup languages (SGML, HTML, TEI, Markdown...) Schema languages (BNF, XSD, RDFS, OWL, SQL...) Conceptual modeling languages (ERM, ORM, UML, DSL...) Conceptual diagrams It is shown how particular method of data structuring and description can best be categorized by their primary purpose. The study further exposes five basic paradigms that deeply shape how data is structured and described in practice. The third results is a pattern language of data structuring. Patterns show problems and solutions which occur over and over again in data. Each pattern is described with its benefits, consequences, pitfalls, and relations to other patterns. The results can help to better understand data and its actual forms, both for consumption and creation of data. Possible applications include data analysis, data modeling, data archaeology, and data literacy.