TDW2017 Keynote

1. Rod Page @rdmpage
http://iphylo.blogspot.com

2. Knowledge graphs

3. Holly Bik @hollybik
Let’s rise up to unite taxonomy and technology
10.1371/journal.pbio.2002231

4. http://ispecies.org
Simple Javascript mashup
DBpedia
GBIF
CrossRef
EOL
Open Tree of Life
TreeBASE

5. https://doi.org/10.7717/peerj.190

6. The Semantic web:
“The future of the web…
and always will be” –
Peter Norvig (Google)

7. Obstacles to building knowledge graphs
•Technical
•Social

8. Obstacles to building knowledge graphs
• Need globally unique, persistent identifiers
(how to label the nodes of the graph)
• Need to create and agree on vocabularies
(how to label the edges of the graph)
• Need to agree how to transmit the graph
• Who stores the global graph?

9. A new hope
• The identifier wars are (nearly) over (DOIs FTW)
• Lots of domain-specific vocabularies, but
schema.org is “good enough” for most things
• XML becoming a bedtime story to frighten the
children, JSON is everywhere (JSON-LD FTW).
• Wikidata

10. Obstacles to building knowledge graphs
•Technical
•Social Economic

11. Identifiers, identifiers, identifiers, identifiers

12. How do we measure progress?
before
now
now
before
Linear growth (easy) Connectivity (hard)

13. Need network effects
One is useless Two is “meh” Many is better

14. The Semantic web:
“The future of the web…
and always will be” –
Peter Norvig (Google)

15. The knowledge graph is
already here (it’s just
not evenly distributed)
William Gibson @GreatDismal

16. Google’s Knowledge Graph

18. PREFIX wdt: http://www.wikidata.org/prop/direct/
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?root_name ?parent_name ?child_name WHERE
{
VALUES ?root_name {"Hominini"}
?root wdt:P225 ?root_name .
?child wdt:P171+ ?root .
?child wdt:P171 ?parent .
?child wdt:P225 ?child_name .
?parent wdt:P225 ?parent_name .
}
http://biohackathon.org/d3sparql/
Toshiaki Katayama @tktym
http://iphylo.blogspot.ca/2017/01/displaying-taxonomic-classifications.html

19. “Citations for the sum of
human knowledge”
WikiCite @WikiCite
Goal 1: Every citation in the Wikipedias should be in Wikidata
Goal 2: Every citation should be in Wikidata (!?)

20. Small knowledge graphs (hexastores)

21. Very simple
ontology
Tom Scott @derivadow
Leigh Dodds @ldodds

24. Hexastore
• A triple is [s, p, o]
• Find all statements [s, ?, ?] is simple array lookup (all elements with key “s”)
• Find all statements [?, ?, o] is slow (scan all triples)…
• …unless we add array of [o, s, p] triples, then simple array lookup (all elements with
key “o”)
• Six variations cover all queries: [s,p,o], [s,o,p], [p, s, o], [p, o, s], [o, s, p], [o, p, s]
(hence “hexastore”)
• In-memory graph database in Javascript (think offline apps)
http://crubier.github.io/Hexastore/

28. Xanadu,
the web that wasn’t

29. Ted Nelson Hyperlinks and
hypermedia
Two-way links and
“transclusion”
= Xanadu
Tim Berners-Lee
HTTP, URL, HTML
One-way links
= world wide web

30. Web page Other web
page
Web linking, one way, document-level, “target”
doesn’t know that it is linked to (“cited”),
link can break (404)

31. text
Work Source
text
Xanadu linking, two way, fragment-level,
“source” knows it is linked to, source content
is embedded, links don’t break

32. Xanadu

33. A New Account of the Genus
Horsfieldia (Myristicaceae), Pt 2
W J J O De Wilde
The Gardens' bulletin, Singapore 38(1): 55-144 (1985)
http://biostor.org/reference/175018
Horsfieldia lancifolia
BioStor @biostor_org
Biodiversity Heritage Library @biodivlibrary

34. Flora Malesiana. Series I - Seed Plants,
Volume 14. Myristicaceae
https://doi.org/10.3897/ab.e1141

35. DescriptionDescriptio
n
Flora Article

36. Embedded markup (bad)…
Crocidura absconditus, new species
<i>Crocidura absconditus</i>, new species
0 20
{ [0,20], “italics” }
…versus annotation (good)
(think NLM JATS XML markup
versus Substance JSON used
by Lens viewer
https://lens.elifesciences.org/
about/)
Crocidura absconditus, new species

37. @hypothes_is

38. Annotating a
scientific paper

39. Aggregating annotations (iPhylo)
http://iphylo.blogspot.co.uk/2016/06/aggregating-annotations-on-scientific_30.html
Taxonomic
names,
specimen
codes,
geographic
localities,
references are
all
annotations

40. Taxonomic databases
are not lists of names…
…they are lists of annotations
(“this name occurs on this page”)

41. Annotations are retrospective nanopublications
Annotating existing content
(extracting “facts”)
Today
Publishing “facts” as nanopublications
Stream of “facts”

42. Social design and the
knowledge graph

43. Obstacles to building knowledge graphs
•Technical
•Social Economic

44. Nico Franz @taxonbytes

45. ORCID
(person)
DOI
(publication)
LSID
(plant name)
Find my papers that
published new species
@SandyKnapp

47. ORCID
(person)
DOI
(publication)
LSID
(plant name)
#Iamataxonomist
(claim/demonstrate expertise)

48. specimen plant name
What Sandy really wants
collected type for
publication
person
“What specimens that I collected that have been
described as new species by other people?”
Published in
author
other person
not the same person

50. Knowledge graphs
considered harmful
(remember Impact Factors?)

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

52. 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

54. We will need to ensure our knowledge graph is
free, open, and used for good