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Rapid Data Entry Supporting high-throughput digitisation workflows in EMu

Rapid Data Entry Supporting high-throughput digitisation workflows in EMu. Laurence Livermore 1 Alex Fell 2 , Muhammad Nadat 2 , Andrew Brown 2 and Ben Sullivan 2 1 The Natural History Museum, London 2 KE Software, an Axiell Group Company. The Digitisation Challenge.

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Rapid Data Entry Supporting high-throughput digitisation workflows in EMu

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  1. Rapid Data Entry Supporting high-throughput digitisation workflows in EMu Laurence Livermore1 Alex Fell2, Muhammad Nadat2, Andrew Brown2 and Ben Sullivan2 1 The Natural History Museum, London 2 KE Software, an Axiell Group Company

  2. The Digitisation Challenge • Increased government and public expectation • Aim to digitise 20 million specimens in 5 years • Current CMS little provision for rapid data entry • Need new tools to support digitisation

  3. Solving the problem – Rapid Data Entry (RDE) • Browser-based interface for KE EMu • Customisable “apps” • Support rapid data entry • Bulk record creation • Field validation • Normalise and atomise data • Project-based approach

  4. Project-based Digitisation • Managed by one or more “leads” • People may be members of more than one project • Project information stored in the collections database • Most projects will have multiple project-specific “apps”

  5. Project Dashboard • Permission dependent • Three “app” categories: • Forms • Editors • Statistics • Multiple apps support various stages/components of digitisation

  6. Forms • Creates new records, including label transcription • Record sets can be filtered • Filtered records are offered to editors/transcribers randomly • Bulk editing and customised operations through scripts

  7. Editors • Global updater • Resolve attachments • Apply consistency • More targeted than EMu global editor • Also created by project lead

  8. Statistics • Simple reporting mechanism • Based on record status • Visualisation tool • Bar chart • Pie chart

  9. Project Creation & Administration • Browser-based configuration • Can reference any backend field • Permissions can be set per users on both projects and apps

  10. Example Project Workflow – Botanical Sheets Form 1 - Stub record creation from barcoded sheets Form 2 - Transcription of localities and collectors Editor 1 - Normalisation of localities Editor 2 - Normalisation of collectors

  11. Future RDE Development • UX/UI improvements (desktop/tablets) • Record navigation and management • Ongoing improvements for NHM’s digital collections programme • Support for non-digitisation activities • Statistics and reporting

  12. Advantages & Disadvantages + Apps are very flexible + No clientside installation required + Display and customisation does not (necessarily) require core client modifications + Steamlined field selection allows for rapid data entry + Digitisation occurs directly into collections database means all data are in one place from creation through to + Normalisation tools within collections database + Support for mobile/tablet devices allows novel/unanticipated workflows +/- Apps and record sets need to be configured by a Data Manager/super user +/- Complex normalisation (of complex data) requires desktop client - Requires WiFi in collections areas - Mobile/tablets less suitable for typing - Another system and interface to support and maintain

  13. New Workflows • Applications outside of rapid digitisation • Specimen relocation & loans • Condition checking & collections audit • Data capture from visiting scientists • Crowdsourcing Original photograph taken by John Cummings http://bit.ly/1vTrzvk

  14. Acknowledgements Management and testing: Darrell Siebert, Annette Ure and testing staff (curators and data managers) Software development: Alex Fell, Muhammad Nadat, Andrew Brown and Ben Sullivan (KE Software)

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