PANDORA Australia’s Web Archive Library Science Talks SNL/CERN, September 2004 Paul Koerbin...

PANDORAAustralia’s Web Archive

Library Science TalksSNL/CERN, September 2004

Paul KoerbinDigital Archiving Branch

National Library of [email protected]


1. Background and approach to web archiving2. The management system (PANDAS)3. Workflows and procedures4. Issues and future directions


1. Background and approach to web archiving in Australia - PANDORA


Beginnings

• Name originally an acronym for: ‘Preserving and Accessing Networked Documentary Resources of Australia’

• Now: ‘Australia’s Web Archive’• Began in mid-1996 (selecting)• Began archiving in late 1996-early 1997


Approach

• Practical and pragmatic • Began as: Proof-of-concept project• Now: Routine National Library activity• Achieving outcomes while continuing to develop and extend

processes and systems• Best use of available resources and infrastructure


Resources

• Existing technical services staff - librarians• Digital Archiving Branch has the business responsibility • Information technology staff from within the Library for

development and support• PANDORA partner institutions (10 including the NLA)


Mandate and responsibilities

• National Library of Australia’s statutory responsibilities• National Library Act, 1960• Maintain and develop a national collection of ‘library material’• Comprehensive collection relating to Australia and the

Australian people


Mandate and responsibilities

• National Library has a leadership role for the Australian library community

Legal deposit

• Legal deposit in the federal jurisdiction in Australia does not cover electronic resources


Some key characteristics

• Selective approach to archiving online resources• Scalable to available resources and do-able• Negotiate permission to archive• Apply manual quality assurance processes to harvested resources• Provide access to the archived resources


Shortcomings of selective approach

• Can’t collect everything that future researchers may want

• Labour intensive tasks• Does not retain the full complexity of the linking

structure of the Internet


Indicative statistics as at August 2004

• 6,500+ titles• 13,000+ archived instances• 21 million files*• 680 gigabytes*

*These figures are for the display copy only. Two more preservation copies plus preservation metadata are maintained.


2. The management system: PANDAS


• PANDAS – PANDORA Digital Archiving System• Integrated web based system • Workflow management system• Developed specifically to manage the web archiving

processes at the National Library of Australia• Used by PANDORA’s partners located throughout

Australia


• Developed in-house at the NLA• Replaced multiple non-integrated systems used between 1996 and

2001 • Written in Java on Apple WebObjects application development

platform• First version released in June 2001• Second version released August 2002• Ongoing enhancement and development program



PANDAS system architecture consists of 4 layers

• 1) Presentation layer – client applications for visual presentation to the end user

• 2) Application layer – the core application functionality such as PANDAS and PANDORA


PANDAS system architecture consists of 4 layers

• 3) Business layer – application access to the data storage and communication infrastructure

• 4) Data layer – third party infrastructure products, e.g. Oracle database and WebDAV accessible files servers


Nomenclature

• PANDORA – the whole enterprise • PANDAS – the whole management system• PANDAS – the system component providing a web-based user

application to manage workflows• PANDORA – the system component that creates the public

interface



PANDAS is used to:

• Record administrative metadata about titles selected (or rejected or monitored) for archiving

• Schedule and initiate harvesting• Manage quality assurance checking and problem

fixing


PANDAS is used to:

• Prepare items for public display through the PANDORA home page

• Manage access restrictions• Generate management reports


PANDAS is a workflow system that:

• Connects with and utilises other software and protocols for specific functions

• Provides an interface to the harvesting software – currently this is HTTrack (http://www.httrack.com)

http://www.httrack.com/


PANDAS is a workflow system that:

• Uses WebDAV protocol to provide content managers with remote access to the harvested files

• Uses Z39.50 protocol to access the National Bibliographic Database to extract metadata from the MARC record


PANDORA public interface component

• Title and subject listings and title entry pages are generated ‘on-the-fly’ from PANDAS metadata

• Some static web pages (documents, information)• Search engine


Persistent identifiers and URLs

• Running number generated by PANDAS• Persistent URL applied to title entry page

http://nla.gov.au/nla.arc-21220

• Logically extended to any resource in the Archivehttp://nla.gov.au/nla.arc-21220-20030822-www.ipjp.org/september2002/schweitzer-ed.html

• Citation generator on public interface

http://nla.gov.au/nla.arc-21220

http://nla.gov.au/nla.arc-21220-20030822-www.ipjp.org/september2002/schweitzer-ed.html


3. Workflows and procedures


• Identifying and selecting• Recording administrative metadata• Harvesting• Quality assurance processing• Archiving• Preparing for public display• Creating resource discovery metadata• Reporting


Identifying and selecting

• Selection guidelines – each partner has their own guidelines• Just guidelines … not rules nor ideology• Selection priorities in guidelines (NLA)• Notification networks – indexing agencies, staff, publishers,

public• NLA selection guidelines available at:

http://pandora.nla.gov.au/selectionguidelines.html


Selection – what sort of publications?

• Titles – the entities to be archived• Defined during the selection process• Document-like publications, e.g. PDF• Whole web sites• Parts of web sites


Selection – what sort of publications?

• Focus on content – substantial, unique• Special events or issues• Format or potential technical problems are not, in

principle, a selection consideration• One-off archiving• Scheduled archiving – whole entity, not an update


Recording administrative metadata

• Four types of records– Title– Publisher– Indexer– Collection

• Selection status• Additional details associated with status (standing)


Administrative metadata

• Publisher details• Archiving permission status• Access restrictions • Notes• Assigning ownership of titles• Transfer titles between agencies


Harvesting

• Mostly harvesting from the Web• Also able to upload from local drives (WebDAV

protocol)• Third party software – HTTrack• PANDAS interface to set up harvesting rules


Harvesting

• Define extent of selected resource to be archived

• Set gather filters and gather settings• Set gather schedule• Initiate harvesting


Scheduling harvesting

• Significant function of PANDAS• Regular schedules, e.g. weekly, monthly, annual• Specific dates• Harvest now• Combination of scheduling options


Harvesting - filters and settings

• Default settings• Ignore robot.txt rules because permission to archive has been

obtained from publisher• Gather sub-directories• Gather ‘near files’, e.g. linked images• Limit on depth – sufficient for any web site but to prevent

abuse of host server


Harvesting - filters and settings

• Gather filters are critical• Selection based on specific content• Archiving permission for specific content• Efficient use of resources (bandwidth,

storage)


Quality assurance

• Important process for PANDORA• Owner of title notified when harvest is complete• Visual, manual checking process • Check for completeness and functionality• Check that content is new (if previously archived)• Check that there is no extraneous material


Quality assurance

• Harvested files in a working area – not ‘archived’ at this stage• WebDAV (protocol) access to the working area• Problem analysis and fixing• Missing files, broken links• Complex problems referred to IT support through PANDAS

error reporting module


Quality assurance

• Problems due to limitations of harvesting software• Excessive use of JavaScript• Deep web resources• Traps such as metafiles, absolute links• Other methods of acquisition (CD, FTP)• Business decision whether or not to accept the harvested instance


Archiving

• Harvested instance is accepted• One-click process for PANDAS user• Transfers instance from working area to Digital Object

Storage System• Creates preservation and display copies• Perl scripts – e.g. re-write external links


Archiving – preservation master copies

• Preservation master – incl. harvest log files• Display master – includes changes made to the harvested instance

(manual and scripts)• Metadata master – http header responses• Gzip compressed TARball (Tape Archive format) on Digital Object

Storage System (DOSS)• Access (display) copy on web server


Preparing for public access – title entry pages

• Generated ‘on-the-fly’ from content of PANDAS database• Partner branding• Link to publisher’s site• Links to dated archived instances• Manual additions – notes, links to serial issues, copyright statement


Preparing for public access – listings and collections

• Subject listings• Title listings• Partner views• Collections – events, sampling over specific time period


Public access – restrictions

• Period• Date• Authentication• IP addresses/subnet mask (i.e. physical locations such as a single PC

in the NLA main reading room)• PANDAS manages automatically – can be manually enabled/disabled


Creating resource discovery metadata

• MARC record for each title• National Library of Australia OPAC• National Bibliographic Database• Metadata derived from the catalogue record is embedded in

the title entry pages• Indexing/abstracting services’ citations


Reporting

• Pre-defined reports from PANDAS UI• Statistical and data reports• SQL query on Oracle database (not through PANDAS interface) • ProClarity for user defined data cube reporting and analysis• LinkScan for broken publisher URL links


4. Issues and future directions


Current issues

• Commitment to selective, quality assessed, accessible web archiving

• Efficient identification – automated selection• Legal deposit (when?)• Blanket permission – government agencies


Current issues

• Ongoing development and enhancement of PANDAS• Improve robustness of system• Re-engineer PANDAS software• Need to achieve greater efficiencies and increase scale

of web archiving activity


Future directions

• Automatically ingest and process larger volume of online publications and associated metadata – batches

• Comply with international standards and adopt standard tools – IIPC

• Incorporate other collection methods – domain harvesting, deep web, deposit


Future directions

• Automate collection of more preservation metadata and develop metadata management interface

• Improve access and discovery paths to the Archive’s resources as it continues to grow


More information

• PANDORA home pagehttp://pandora.nla.gov.au/

• Key documents (background, technical, PIs)http://pandora.nla.gov.au/documents.html

• PANDAS manual http://pandora.nla.gov.au/manual/pandas

• Papers and presentationshttp://pandora.nla.gov.au/papers.html

http://pandora.nla.gov.au/

http://pandora.nla.gov.au/documents.html

http://pandora.nla.gov.au/manual/pandas

http://pandora.nla.gov.au/papers.html


Questions?


http://pandora.nla.gov.au

http://pandora.nla.gov.au/

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