Slides from 4th Global Online Biodiversity Informatics Seminar https://plus.google.com/events/clvk6nd14d9fhh7e4a6oe5mt9s0

1. Building the
Biodiversity Knowledge Graph
@rdmpage
http://iphylo.blogspot.com

2. • There are known knowns, things we know
that we know
• There are known unknowns, things we
now know we don’t know
• But there are also unknown unknowns,
things we do not know we don’t know

3. known
unknown

4. Things we don’t know
that we know

5. Melissotarsus insularis

6. Melissotarsus insularis no hit
CASENT0107663-D01 DQ176312
Melissotarsus sp. BLF m1DQ176312
CASENT0107663-D01Melissotarsus insularis
1
Melissotarsus insularisMelissotarsus sp. BLF m1
=

7. We have a vast amount of
“old stuff”

8. Numbers of new animal names
1923
WWI
WWII

9. We are learning new stuff

11. “New” and “old” are
disconnected

12. Dark taxa
http://iphylo.blogspot.co.uk/2011/04/dark-taxa-genbank-in-post-taxonomic.html

13. Mammals in GenBank
Proper Linnaean names
Aus sp.

14. Mammals
Proper Linnaean names
Aus sp.

15. “Invertebrates”
BOLD

16. Challenge:
linking things together
(sticky data)

17. Data is good

18. More data is better…

19. …but this data is not sticky

20. Location

23. name
name
Tags

24. Namenname

25. Identifiers

27. Shared identifiers are sticky

28. Identifiers
• Globally unique
• Resolvable (for humans and machines)
• Use other people’s identifiers to link
things together

29. Human and machine readable
machine
human

31. {
"author": [
{
"family": "Page",
"given": "Roderic D.M."
}
],
"container-title": "PeerJ",
"reference-count": 60,
"page": "e190",
"deposited": {
"date-parts": [
[
2013,
11,
18
]
],
"timestamp": 1384732800000
},
"title": "BioNames: linking taxonomy, texts, and trees",
"type": "journal-article",
"DOI": "10.7717/peerj.190",
"ISSN": [
"2167-8359"
],
"URL": "http://dx.doi.org/10.7717/peerj.190”
}

32. Using other people’s identifiers
is hard work and scary
• Hard work - you have to find their identifiers
• Scary - what happens if other person breaks
their identifiers?
• Solution: make it easy to find them, and make
them robust (e.g., CrossRef and DOIs)

33. http://dx.doi.org/10.7717/peerj.190
DOI (Digital Object Identifier)

36. Biodiversity Knowledge Graph
(linking things together)

38. Our questions are
“paths” in this network

40. Phylogeography

41. Taxonomy

43. GenBank records from Spain

44. MESH term

45. PMID:948206

46. http://biostor.org/reference/102054

48. http://data.gbif.org/occurrences/215921922/

49. BHL and GBIF as biomedical databases
http://iphylo.blogspot.co.uk/2012/03/bhl-and-gbif-as-biomedical-databases.html

50. Metrics
(counting links in the knowledge graph)

51. In an attempt to live up to that increasing
demand for documentation, the leadership of
the Natural History Museum of Denmark has
issued an order to its curatorial staff - The
staff members are requested to document
which publications from 2011, written
entirely by external scientists, that in one way
or another are based on material in the
collections of the Museum.
http://markmail.org/message/opv2we7fkmro2nen@TAXACOM

52. https://twitter.com/#!/search/10.1371%252Fjournal.pone.0036881

53. https://twitter.com/edwbaker/status
/205595933159858176
https://twitter.com/edwbaker/status/205595933159858176

54. http://www.museum-analytics.org/

55. Cited, linkable specimens
NMNH Vertebrate Zoology
Herpetology Collections
11194
CAS Herpetology Collection Catalog
MCZ Herpetology Collection
Herpetology Collection (University
of Kansas Biodiversity Research
Center)
9619
6720
5818
http://iphylo.blogspot.co.uk/2012/02/gbif-specimens-in-biostor-who-are-top.html

56. Annotation
(everyone can make
the knowledge graph)

59. http://bionames.org/labs/bookmarklet/

66. How many people view annotation
Data
Fix me!

67. Annotation as fixing errors

68. Annotation as building
the knowledge graph
paper specimen
paper
sequence
taxonomic name
specimen
cites
publishes
has voucher

70. OK, but if the
biodiversity knowledge graph is so cool,
why haven’t we made it already?

75. Open question:
Who will build the
biodiversity knowledge graph?