Transcript
Page 1: SCAPE Information Day at BL - Characterising content in web archives with Nanite

Characterising content in web archives with Nanite

William Palmer

SCAPE Information Day

British Library, UK, 14th July 2014

Page 2: SCAPE Information Day at BL - Characterising content in web archives with Nanite

• When web sites are harvested they are stored in a container format

• The main web archive container formats are ARC and WARC (an ISO standard)

• They are effectively analogous to a zip file

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Web Archives

This work was partially supported by the SCAPE Project. The SCAPE project is co‐funded by the European Union under FP7 ICT‐2009.4.1 (Grant Agreement number 270137).

WARC Container

Page 3: SCAPE Information Day at BL - Characterising content in web archives with Nanite

• Web archives can hold billions of individual records

• To answer deeper questions you have to determine what data is held

• Not the same as a homogenous collection of images

• Can contain everything and anything

• Correctly formed files

• Malformed files

• Viruses

• Unknown files?

• You name it

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Characterisation

This work was partially supported by the SCAPE Project. The SCAPE project is co‐funded by the European Union under FP7 ICT‐2009.4.1 (Grant Agreement number 270137).

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JPG GIF

TXT XLS

Page 4: SCAPE Information Day at BL - Characterising content in web archives with Nanite

Nanite

• Nanite is formed of two main modules

• nanite-core: a Java API for the UK National Archives’ Droid

• nanite-hadoop: WARC content characterisation using Hadoop

• Apache Tika (Detector), Nanite-core & libmagic-jni (‘file’)

• Optionally use Tika (Parsers); data output to sequence files

• Also list server content type & file extension

• Reuses: warc-hadoop-recordreaders (partially SCAPE)

Page 5: SCAPE Information Day at BL - Characterising content in web archives with Nanite

Speed

• Fast: for 1TB, 14k warcs, 93m files; mimetypes detected in 17 hours

• Nanite has also been used at the Danish State and University Library

• 7.3TB data, 80k ARC files, 261m files

• Identification using Droid and Tika

• Characterisation using Tika

• …in 32 hours

• Same platform but using FITS (not using Hadoop, but parallelised):

• 12TB data, 100k ARC files, 400m files

• An entire year of processing (8760 hours)

Map

Tika Identify

Nanite/Droid

Libmagic

Tika Parser

Page 6: SCAPE Information Day at BL - Characterising content in web archives with Nanite

Stats

• 1370 different MIME types reported by the original servers

• Tika detected 342

• DROID detected 319

• Additional information in this blog post: http://www.openplanetsfoundation.org/blogs/2014-05-28-weekend-nanite

Page 7: SCAPE Information Day at BL - Characterising content in web archives with Nanite

Visualising Characterisation Information

• Nanite has an option to output C3PO compatible outputs

• They can be directly loaded into C3PO for visualisation


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