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EMu and the Natural Sciences at Museum Victoria Dermot A. Henry Manager, Natural Science Collections Museum Victoria, Melbourne.

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Presentation on theme: "EMu and the Natural Sciences at Museum Victoria Dermot A. Henry Manager, Natural Science Collections Museum Victoria, Melbourne."— Presentation transcript:

1 EMu and the Natural Sciences at Museum Victoria Dermot A. Henry Manager, Natural Science Collections Museum Victoria, Melbourne

2 Thanks yous! Entomology: Ken Walker, Kristy Hoath, Sarah McCaffrey, Peter Lillywhite, Catriona McPhee. Terrestrial Vertebrates: Wayne Longmore & Rory O’Brien EMu team: Nancy Ladas & Alex Chubaty

3 Museum Victoria Museum of Natural Sciences, Indigenous Studies, Social History, and History of Science & Technology

4 Museum Victoria 1854 National Museum of Victoria 1986 Amalgamation of the Science Museum of Victoria and the National Museum of Victoria 2000 Melbourne Museum opened Immigration Museum and Scienceworks

5 This talk… Introduction to MV Natural Science collections & EMu Some recent EMu projects Web outputs

6 The collections: The real thing!

7 Collections Diverse collections of zoological and geological specimens which underpin MV Research Research conducted by MV Research Curators, CMs, associates, students etc Providing access to collections to facilitate other researchers (from within Australia and overseas) Distilling the stories from research for the general public, eg exhibitions, public programs Promoting science

8 Natural Science collections Over 15 million specimens 3.2 million collection management units 1,061,706 units on database

9 Natural Science collections Reference e.g. Types Systematics Diversity reflecting morphological differences, geographic distributions etc

10 History of EMu 1982 Museum obtains Titan/Texpress 1996 Commence development of EMu 2000 Commencement of transfer of Texpress to EMu 2007 Completion 48 individual Texpress databases transferred!

11 History of EMu Natural Sciences had some resistance to Emu − preference for flat screen approach of Texpress Over time, changing mindset − viewing EMu as data management tool not solely a collection management tool

12 Registration Project ≈ 2004 an explosion in the need to electronically register data at specimen level for research-based and other biodiversity mapping initiatives Examples include: MV’s Bioinformatics and Pest and Diseases Images Library web projects International Global Biodiversity Information Resource and Australian Zoological Collections Online. Atlas of Living Australia Specific external research initiatives which have provided funding for MV to register collections MV needed to reassess baseline registration methodologies to meet this need

13 Registration project Overcome the mindset that the collections were too big to register Over 15 million specimens 3.2 million collection management units Acknowledge the ‘risk management’ value of registrations.

14 Registration project Commenced 2004-2005 Acknowledgement that increased registration rates are not possible with current staffing resources in collections Purpose: to register the majority of the State Collections, including a substantial backlog of unregistered collection material ‘Backlog’ considered to be material acquired before 2004

15 Registration project Tackle smallest collections first Define a tight minimum dataset Do not attempted to exhaustively capture all information Enhance data appropriately (eg latitudes and longitudes to facilitate mapping projects

16 Registration Project 2004/5 Recruited 3 ‘specialist’ registration officers Additional funding acquired from Entomology grant funds − employed 3 additional staff Tackle smallest collections first and specific subsets of Entomology First year approximately 98,000 records

17 Zoology: Fish Approximately 430,100 specimens Stored as 44,000 lots 2004/5 completed approx 11,000 records captured

18 Zoology: Herpetology Vertebrate 77,000 specimens 3,000 records captured

19 Zoology: Birds 73,000 specimens Skins, mounts, skeletons, eggs and nests Approximately 5,000 captured. Egg collection excluded

20 Zoology: Mammals Approximately 40,000 specimens Skeletons, skins and display mounts 8,000 captured

21 Trichoptera data Google mapping 70 000 records

22 Trichoptera data. Google mapping

23

24 Registration Project Approximately 1/3 of NS Collections data captured. Individual disciplines completed: Birds, Mammals and Herpetology Ichthyology Natural Science art Mineralogy, Meteorites, Tektites Subsets of large collections of Marine invertebrates and Entomology collections

25 Registration Project Averaging 74,000 NS records per year to June 2010. Cost of approximately $2.35 per record Increased data set from 615,638 to 1,061,706 Demonstrated that, with appropriate funding, major inroads to the backlog could be achieved

26 Palaeontology collections Approximately 4 million samples 250,000 vertebrates 100,000 plants 3.5 million invertebrates 14,000 Type specimens Palynology slides from Victorian oil wells

27 Palaeontology registration Setting priorities Capture all paper registered specimens

28 Tissue Bank Registration and barcoding of samples

29 Entomology Type project 2.5 million specimens 20,000 Type specimens (approx 3,500 ‘dry’ primary types) Largest aquatic insect collection in Australia

30 Entomology Type project 3-year project to image capture approximately 3,500 primary types Reduce the need to transport fragile specimens for loans

31 Entomology Type project Employed specialist staff to take high resolution images using multilayering techniques and computer combination of images Up to 60 images per a final view. Detailed depth of view Next iteration will allow use of ‘zoomify’ on Web to see detail

32 Entomology Type project

33

34 2952 types completed into Emu

35 Entomology Type project Available on Web

36 Entomology Type project Has increased requests for info on Types but often high res images are suffice

37 Bird egg registration and image capture project. Set priorities for staff – free them up! Set targets Include image capture of all specimens

38 Egg registration

39 20,000 clutches Data entry completed in 2 years Data set suitable for development of egg identification website

40 McCann image collection Acquired November 2009 Ian McCann was a keen wildlife and botanical photographer Amassed a collection in excess of 20,000 35 mm Kodachrome slides Many published images

41 McCann image collection Ian McCann passed away in July 2003. His family were keen for his collection to go to appropriate institutions for not-for-profit use July 2009, Museum acquired zoological image component – 5,400 images mainly Victorian fauna, approx 300 to 400 families

42 McCann image collection 1450: Reptiles and amphibians 980: Mammals

43 McCann image collection 1860: Birds 400: Insect, Crustaceans, Molluscs, worms and Butterflies 690: Spiders

44 McCann image collection All slides catalogued in EMu All slides digitised (high resolution) All images attached to slide catalogue record and to taxonomic records Red-capped Robin (male)

45 McCann image collection

46

47 Catalogue and taxonomy modules

48 McCann image taxonomy module Coral snake

49 McCann image collection Available on the web via the taxonomic module Fantastic on line resource!

50 Collections on-line Redevelopment of Science and Life Galleries completed in Oct 2010 Collections on-line priority for 2010 / 2011 for Natural Sciences

51 Promoting access Data available via other search engines. OZCAM GBIF Atlas of living Australia Atlas of Life

52 Bioinformatics Distribution – space and time Authenticated data

53 Bioinformatics Distribution – vegetation

54 Bioinformatics Leasing of data to other Agencies Ability to provide data in a format required

55 Promoting access: Online 68 4 3 13 36 221 17 24 6 16 98 11 41 17 8

56 Promoting access : Online 68 4 3 13 36 221 17 24 6 16 98 11 41 17 8

57 Promoting access 17

58 Promoting access

59 Data enhancement

60 Narratives for target websites

61 Conclusions Providing access is core business Pressure to make collections more accessible via on line processes Acknowledge the importance of datasets and fund appropriately Set registration priorities Effective and efficient means of data enhancement Make available on-line through raw and filtered data methods for a range of users.


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