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Crowdsourcing the Past with AddressingHistory

Presented by Stuart Macdonald at IASSIST 2012.

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Crowdsourcing the Past with AddressingHistory

  1. 1. Crowdsourcing the Past with AddressingHistory Stuart Macdonald Project Manager EDINA & Data Library University of Edinburgh, Washington DC, June 6-8, 2012
  2. 2. Phase 1JISC-funded Community Contentproject6 months (April 2010 – September2010)Partner with National Library ofScotlandAdvisory Board
  3. 3. To create an online crowdsourcing tool which will combinedata from digitised historical Scottish Post OfficeDirectories (PODs) with contemporaneous historical mapsSimilar to Australian Historic Newspapers projectprovided by National Library of Australia where membersof the public correct and improve OCR’d text of oldnewspapers -
  4. 4. PODs offer a fine-grained spatialand temporal view on social,economic and demographiccircumstancesThey also provide residentialnames, occupations, andaddresses.Each contain 3 directories:general, street, and trades
  5. 5. Phase 1 focussed on 3 vols. ofEdinburgh PODs: 1784-5; 1865;1905-6Historic Scottish maps geo-referenced by NLSPODs digitised by NLS inconjunction with the InternetArchive694 PODs (1773 to 1911) covering28 of Scotlands towns andcounties now onlinePublic domain (CC BY-NC-SA 2.5)
  6. 6. Using Open Layers as web-based mapping clientTool allows ‘the crowd’ togeoreference a POD entry bymoving a ‘map pin’ on adigitised map thus facilitatingthe addition of an gridreference to the OCR’d PODheld as XML in PostGreSQLdatabaseAPI available allowing webdevelopers access to the rawdata in multiple output formats(JSON, XML, CSV)Geo-coding of POD addressesparsed against Googlegeocoder
  7. 7. Interface had to be easy-to-use for a range of users Robust and scalable to accommodate c.700 digitised Scottish PODs Mechanism to check user-generated content such as geo-references, name or address edits/annotations View original scanned directory page Amplification of tool and API via Social Media Channels – Facebook, Twitter, Blog, Flickr, YouTubeImage by yelnoc - - CC BY-NC-SA 2.0
  8. 8. Phase 2 sought to develop functionality to resonate with JISC’svision to build sustainable and durable deliverables and tocompliment phase 1 by broadening both geographic and temporalcoverageFeb. – Sept. 2011 (EDINASustainability Funding)New content (Aberdeen,Glasgow, Edinburgh for 1881 &1891Re-evaluate (and enhance)parsing tool performance
  9. 9. Phase 2Other additional features include: • Spatial searching (bounding box) • Associate map pin with search results • Search across multiple address • Aid searching by applying Standard Industrial Classification (SIC) codes to Professions • Augmented Reality - an AH layer has been created and published for use with the ‘Layar’ Application for either iPhone or Android
  10. 10. Augmented Reality ApplicationUsing the BuildAR CMS tool anAddressingHistory layer hasbeen created and published foruse with the ‘Layar’ Applicationfor a range of mobile platformsincluding iPhone or AndroidRaw ASCII Points of Interest(POIs) and associated metadataare uploaded as a set of GoogleMap co-ordinatesPOIs (e.g. each profession orSIC Code) have an imageassociated with itThe AddressingHistory layer works with the Layar App to compareinformation about your current location (from your phone) and the geo-referenced entries in AddressingHistory to work out which historicalresidents and businesses used to be located near where you arestanding at that moment
  11. 11. Crowdsourcing on 3 levels4. Individual record level – georeference, address, name, occupation• Configuration file level - edit and augment OCR errors / inconsistencies to run in conjunction with parsing process for future PODs• POD level - User can request POD of interest and can be potentially be given access to parser (2 & 3 require modest technical understanding and are ‘policed’ by EDINA)
  12. 12. Lessons LearnedCritical mass – does geographic & temporalcoverage attract and engage the crowd?Separate out parsing from interface andback end storage - to allow any refinements tobe implemented without impacting on tool and APIExternalise ‘configuration’ files – editableXML-based files that identify repeated OCR andcontent inconsistencies – these are run inconjunction with the POD parser to refine theparsed content hence improved searchingParsing and refining process is almostunending - Identify what is realistically achievablewith available resources and time constraints- i.e. perform proper requirements analysis
  13. 13. SustainabilityGiven the broad applicability of theresource a range of communities may beinterested in the longer term curation ofthe project tools e.g. the Open Street Mapcommunity, NLSEvaluation of possible business modelsfor sustainability:revenue generation via online donationssubscription model (e.g. per annum, permonth, per use)‘freemium model’ (e.g. free API downloadof a certain number of records withpayment for further downloads)academic advertising.
  14. 14. Second last slide…Gauging the success of the project goes beyond thedelivery of engaging and innovative online tools. It willbe ultimately be measured by continual and extendeduse within the wider community.
  15. 15. Website: THANKING YOU! Credits: Image by aroid - - CC BY 2.0 Image by konqui - - CC BY-NC 2.0 Image by mosilager - - CC BY-NC-SA 2.0 Image by racoles - - CC BY-NC 2.0 Image by James Bowe - (CC BY 2.0) Image by yelnoc - - CC BY-NC-SA 2.0 Image by - - CC BY 2.0 Image by bek30 - - CC BY-NC 2.0 Image by karen horton - - CC BY-NC 2.0 Image by lofaesofa - - CC BY 2.0 Image by Psycho Delia - - CC BY-NC 2.0 Image by wdj(0) - .com/photos/davidjoyner/534893725/ - CC BY-SA 2.0 Image by Symic - - CC BY-SA 2.0 Image by ~milj - - CC BY-NC-SA 2.0 Acknowledgements: JISC - NLS Geo-referenced maps and applications - Visualising Urban Geographies (VUG) project – Edinburgh City Libraries –