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Australian Museum EMu Project

Australian Museum EMu Project. Or how to make 11=1 Dr Penny Berents. Background. databasing of collections began in early 1980s with vertebrate collections TITAN first databases were identical but as the years went by Collection Managers modified their database(s)

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Australian Museum EMu Project

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  1. Australian Museum EMu Project Or how to make 11=1 Dr Penny Berents

  2. Background • databasing of collections began in early 1980s with vertebrate collections • TITAN • first databases were identical but as the years went by Collection Managers modified their database(s) • in 2000 the AM had 11 collection databases in Texpress on 4 servers

  3. Birds Fishes Herpetology Mammals Marine Invertebrates Tissue Insects Minerals Molluscs Palaeontology Spiders AM collection databases

  4. Step one • Choice of software • KE EMu or something else? • how much could we combine with AM Anthropology EMu database ?

  5. Difficulty • whose version of EMu ? • American versions – AMNH, NMNH ? • Australian natural history users ? • AM Anthropology ?

  6. Difficulty • our limited knowledge of product architecture and functionality before commencing customisation • data free software

  7. . Success • We analysed all collections for individual needs before customising Catalogue and before migrating any data

  8. Difficulty • which modules? • Catalogue, Taxonomy, Sites, Collecting Events, Parties, Loans, Movements, Bibliography, Multimedia, Locations

  9. Difficulty • Latitude and Longitude

  10. Difficulty • Registration numbers and IRNs

  11. Success . • Salinity data not displayed with float data

  12. Success . • EMu logins • Registry settings

  13. Success . • EMu logins • Registry settings • standard environments for EMu

  14. Success . • EMu logins • Registry settings • standard environments for EMu • mapping fields from Texpress to EMu

  15. Success . • EMu logins • Registry settings • standard environments for EMu • mapping fields from Texpress to EMu • data mapping benchmarks

  16. Difficulty • establishing load benchmarks for testing each collection after the load

  17. Difficulty • establishing load benchmarks for testing each collection after the load • range queries

  18. Difficulty • establishing load benchmarks for testing each collection after the load • range queries • SQS (simple query screen)

  19. Difficulty • establishing load benchmarks for testing each collection after the load • range queries • SQS (simple query screen) • keeping track of different datasets at varying stages of implementation

  20. Success . • storage locations

  21. Success . • storage locations • issue registration

  22. Difficulty • histories

  23. Difficulty • histories • taxon/ type of

  24. Difficulty • histories • taxon/ type of • Help/Manuals/Training

  25. Where are we up to? • 4 datasets loaded and operational • Marine Invertebrates, Herpetology, Birds & Spiders • Mammals loaded to ‘test’ database • Mapping underway for next datasets • due to finish migrating all datasets by end 2004

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