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Digital histories Workshop 1: introduction K. Navickas

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Digital histories. Workshop 1: introduction K. Navickas. Searching for information and making notes before digitised sources. Dewey catalogue. County record office; Library; National Archives. My notes, organised by where I read the information, and their cataloguing system. - PowerPoint PPT Presentation

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Digital histories

Workshop 1: introduction

K. Navickas

Searching for information and making notes before digitised sources

Dewey catalogue

Card catalogue

My notes, organised by where I read the information, and their cataloguing system

A bit of a gamble if I get what I want/looking for

Boxes of books & archives

County record office;Library;National Archives

Searching for information and making notes after digitisation – googlerisation?

Digitised archives and newspapers from all over the world

Download them to my own computerWrite notes on computer – or annotate files

Still a gamble to find what I want…

Catalogue system – online- could be determined by original order of the repository- could be completely new system- no system? – e.g. flickr collections – crowdsource tagging

What archives available dependent on what is digitised – dependent on funding, conservation; volunteers

Pay to access?

Metadata old style: Leonard Bloomfield, Language (New York: Holt, Rhinehart & Wilson,

1933)Document type Book

Last name of author Bloomfield

First name of author Leonard

Year of publication 1933

Title Language

City New York

Publisher Holt, Rhinehart & Wilson

http://exchanges.history-compass.com/2010/03/30/doing-local-history-card-catalogues-manual-searches-and-historiography/

Metadata now: View page source and see the html or the xml schema

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OCR text from the Burney newspaper collection – what on earth is it saying?

OCR is rubbish with tables and old fonts

Big data?• From ‘computing and history’ to data and text

mining, corpus linguistics, topic modelling• Are we moving from ‘close reading’ to ‘distant

reading’?Methods:• N-grams – finding the proportion of occurrence of

a word in a corpus of texts• Topic-modelling - assessing probability of

occurrence of a group of words within a textStudy:• ‘culturomics’

Google n-gram viewer

Topic- modelling in Mining the Dispatch