Glossary

IIIF

The International Image Interoperability Framework (IIIF) defines several application programming interfaces that provide a standardised method of describing and delivering images over the web, as well as “presentation based metadata” (that is, structural metadata) about structured sequences of images.

If institutions holding artworks, books, newspapers, manuscripts, maps, scrolls, single sheet collections, and archival materials provide IIIF endpoints for their content, any IIIF-compliant viewer or application can consume and display both the images and their structural and presentation metadata.

There are many digitisation programmes that have resulted in a particular collection’s content exposed on the web in a particular viewer application, but these various collections have not typically been interoperable with one another, and end users or institutions cannot substitute a viewer of their choice to consume the digitised material. The IIIF aims to cultivate shared technologies for both client and server to enable interoperability across repositories, and to foster a market in compatible servers and viewing applications.



You may also be interested in the following terms :

ALTO

The Analyzed Layout and Text Object (ALTO) is an open XML standard to represent information of OCR recognized texts.

IIIF

The International Image Interoperability Framework (IIIF) defines several application programming interfaces that provide a standardised method of describing and delivering images over the web, as well as “presentation based metadata” (that is, structural metadata) about structured sequences of images.

OCR

OCR (optical character recognition) is the recognition of printed or written text characters by a computer. This involves photoscanning of the text character-by-character, analysis of the scanned-in image, and then translation of the character image into character codes, such as ASCII, commonly used in data processing.

OLR

In computer vision, document layout analysis is the process of identifying and categorizing the regions of interest in the scanned image of a text document.

Topic model

In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract “topics” that occur in a collection of documents. Topic modelling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body.