Digitising books as objects: The invisible made visible

Digitising books as objects: The invisible made visible

  • March 14, 2018
Table of Contents

Digitising books as objects: The invisible made visible

Technology has improved immensely since then and a lot of ‘ink’ has been spread across physical and virtual pages about the remit, the limitations and the advantages of what is offered to the public through the surrogates uploaded onto countless web portals. This piece is just another little drop into this ocean of ink to share some considerations built upon experience and from the perspective of a book conservator who sees, because of his professional background, the limitations of this, but also the exciting challenges to overcome them.

Source: bl.uk

Share :
comments powered by Disqus

Related Posts

Building Windows: 4 million commits, 10 million work items

Building Windows: 4 million commits, 10 million work items

Microsoft’s switch to using Git as the version control system for Windows’ development has resulted in many challenges. Git wasn’t really built for a 300GB repository with 3.5 million files, and the engineering effort to make Git scale in this way continues.

Read More
Profilo: Understanding app performance in the wild

Profilo: Understanding app performance in the wild

The Facebook apps for Android and iOS are used by billions of people across the world. We have ambitious goals around delivering a delightful experience for people using Facebook and a strong belief that responsiveness and smoothness are keystones of a high-quality product experience. Together, these mean that, among other things, we need to quickly and efficiently investigate performance problems.

Read More
The Nexus Linking IBM, California Wine, and Climate Modeling

The Nexus Linking IBM, California Wine, and Climate Modeling

By 2015, Hamann says, the technology—which uses machine learning to extract insights from multiple layers of information—proved itself. Gallo improved yields on the test site while reducing water use. The partnership quickly found another use for IBM’s AI: analyzing a number of variablessuch as proximity to the winery, weather patterns, elevation, days of sunshine, and other factors toidentify suitable locations for new vineyards.

Read More