WEBVTT

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(chairman) So, let's welcome Egon,

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who will describe how he is trying

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to improve the coverage 
of chemical compounds in Wikidata.

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(Egon) Yeah, thank you.

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So, let's see...

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Oh, this is not right.

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Sorry.

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They put the wrong slide deck.

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(person 1) The one was better than--
(person 2) [inaudible]

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(person 1) (laughs)

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How about this?

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This one actually says WikidataCon.

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Slightly different slides.

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Okay, so yeah, coverage and correctness,

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accuracy, quality, if you like.

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And the other thing here

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is what makes it different 
from some of the other things

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that we've seen at the WikidataCon

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is how I do this quality,

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and the coverage, actually.

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So I'm actually taking advantage here
of my background,

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which is in cheminformatics,

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which is something 
that we use in our research.

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And cheminformatics

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is a way to understanding 
the chemical structures,

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what we will see in a moment.

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We can do things that we cannot do 
with the regular toolsets

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that we have, like Shape Expressions,
quality constraints and sorts.

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Now, one of the interesting
things of chemistry

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is that chemical structures,

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are sometimes the same,
sometimes not the same,

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depending on what you want to know.

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And this slide reflects that a bit,

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and what we see here 
is biologically the same compounds

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but chemically two different compounds.

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But at biological levels 
with the [inaudible],

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they are in equilibrium,

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and you will not be able 
to really distinguish between them,

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unless you're looking 
for a particular type of biology

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like reaction mechanisms.

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Another interesting thing 
about Wikidata and Wikipedia

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is that we have things 
like long-chain fatty acids,

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chemical concepts
which are not a specific compound

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but actually a class of compounds.

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Now, this class can be based 
on similar features in the molecules,

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so like in the case 
of the long-chain fatty acids--

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they all have a long-chain fatty
and an acid group.

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In other cases, there are the classes

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based more
on the biological functionality,

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like a certain type of inhibitor,
like an ACE inhibitor.

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And this introduces 
a lot of interesting things,

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partly because of this close link 
with Wikipedias.

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And one of the things that we see

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is that Wikipedia may have a chembox 
for a particular compound

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bur actually be about a compound class,

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resulting to a slightly different concept

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of what the two things 
are actually meaning

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and the sitelink being more complicated.

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We need this 
for understanding the biology.

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So the research in our group 
is understanding the living cell.

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The system's biology here 
described in the biological process

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is we have a pathway database 
for that--WikiPathways,

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and if we look at the chemistry in there
of the small molecules,

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the chemistry is sometimes 
described in a lot of details,

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sometimes in less detail,

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pretty much like this Wikipedia
Wikidata link that we just had

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resulting in basically links
to a lot of different databases

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with slightly different focuses.

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Some databases like LIPID MAPS
and the Human Metabolome Database,

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they are very much focused on the biology,

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whereas a database like ChEBI,

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that's very much focused 
on the chemical entities.

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So we try to breach that,

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and that two-three years ago gave us
a very interesting insight

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that if you look at the lines here

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where in blue we have the total number 
of the small molecules

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we have in these Pathways

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and the numbers in red 
that we can match to that,

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there is this gap, and this gap 
is complicated chemistry.

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Also, poignantly, things
missing in Wikidata.

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So therefore the need 
for date completeness

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and the data quality.

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And here we have an example.

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This is actually 
a curation report of yesterday,

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and these are still things 
that we have in Pathways

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but that we do not know 
what the equivalent thing is in Wikidata.

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And one of the things here
that I'm picking out here

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is strigolactone.

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And this is a class of compounds.

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So we have that in one of our Pathways,
this particular Pathway over there.

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So you start matching this 
to Wikidata and Wikipedia,

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and to actually use
for this compound Wikipedia page

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with these six structures--

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images, name, no links, nothing.

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Nothing in Wikipedia,

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just this information, 
not machine-readable.

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So based on the name, 
I can actually find three out of the six

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of these compounds in Wikidata,

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not linked, not classified.

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So if we look at the class 
of strigolactones,

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of which these six are examples,

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Wikidata did not give us anything.

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So that's the kind of curation
that I'm interested in.

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On the right here--
that page is actually pretty much empty,

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but it's exactly what Scholia is showing
for this class of chemical compounds.

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So Scholia is one of the tools 
that I've been using to do this curation.

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This missing classification
is a bit of information

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missing in Wikidata,

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but we can add this classification,

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and we can retrieve that 
from some sources.

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We will see with LIPID MAPS later,

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we can automate 
adding these missing links,

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if we understand the chemistry.

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So this diagram over here--
we have fatty acid over there again

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and the long-chain fatty acid over here

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that we saw on one
of the previous slides--

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very long-chain fatty acids 
and a number of other fatty acids.

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This kind of information helps us see

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a [inaudible] of the chemistry 
in Wikidata.

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Scholia can visualize the 2D structure,

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and this thing is actually 
automatically generated

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from the chemical structure in Wikidata

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on the fly creating 
in the Scalable Vector Graphics.

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(coughing)

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Sorry.

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With the stereochemistry annotation there

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to help the chemist see 
the completeness of the data

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because also the stereochemistry 
might be missing.

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We also get an overview on Scholia 
of related compounds

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based on the InChIKey,

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where the first block basically indicates
how the atoms are connected

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and the second column 
indicates things like stereochemistry

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and things like 
which isotopes are in there,

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for example C11 instead of C12

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or C13 instead of C12.

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The last number 
of the last letter over here

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actually indicates the charge,

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so that's the example that we saw earlier
between the citric acid and the citrate,

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or was it the acetic acid and the acetate?

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By putting in a bit of the main knowledge,

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we can do a lot more... making sense 
of what we have in Wikidata.

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A bit more about Scholia

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is that about data completeness 
with the physical and chemical properties,

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the literature, those are whole things 
that we want to have access to.

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But it only works if we can find 
the right chemical in Wikidata.

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We started using Wikidata 
in a number of our projects,

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so WikiPathways was one of them.

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This is another project

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in the area of the nanosafety, 
risk assessment,

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where they use OECD testing guidelines

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and using Wikidata here 
to make an overview of the experiments.

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And this means that we can now
actually start annotating articles

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where these protocols have been used.

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And in this way, we get a better insight 
in the quality of literature as well.

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We get to see which DDTs

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are well tested, established 
experimental methods

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and an indication of how good the data is 
that came out of that.

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Another example--this is nanomaterials,

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specific nanomaterials,

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where there is a unique code-- 
we've added that--

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with the same purpose of being able

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to track down literature 
about these nanomaterials.

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But, again, we need exact descriptions.

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Now, this is 
the LIPID MAPS classification,

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and here we see an interesting thing,

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and this has shown up 
in some of the presentations,

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elsewhere as well.

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This idea that some of the things 
that we have in Wikidata

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is not always matching the sources.

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So different ontological models,

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different ideas 
of what a particular thing means.

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And so, if we look at the LIPID MAPS,
we have a lipid in the middle

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and then a number of classes,

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and many of these are in Wikidata.

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But here, around actually 
fatty acids or fatty acyls,

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that's where there is a mismatch

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causing something that should be 
actually purely hierarchical,

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actually it started to show 
some loops over there,

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the mismatch of two representations 
of a lipid chemistry.

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Now, the goal of this work
is not so much to reconcile this

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but to visualize it

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so that we can understand 
what is going on

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and correct things 
that are actually clearly wrong.

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The interesting about LIPID MAPS 
is actually that the classification

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is indicated in the external identifier.

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So one of the things 
that we've been using

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is these external numbers
to make this automatic classification

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because everything 
that starts with an LMFA05

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is actually a fatty alcohol.

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So I can translate that 
into Quickstatements,

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push that into Quickstatements

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and get that annotated in Wikidata.

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This slide is just reflecting 
the advantage for LIPID MAPS here

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which been collaborating with them

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because they get a lot of data
out of Wikidata as well,

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which we can cross-reference, 
which we can compare if it's correct.

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LIPID MAPS is a quite curated database

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but like everyone actually having trouble

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with access to literature,

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the demand of literature 
and filtering the literature,

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getting to the right articles.

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Shape Expressions is probably 
something that you've seen.

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We have a few of them for chemistry now.

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This is the example for racemic mixture.

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In a case of racemic mixture,
you want to have two parts in there.

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It's a mixture,

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so at least two chemical entities 
need to be in there.

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Moreover, each of the [inaudible] parts
has to be a chemical compound.

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This is another level of a way
we can curate the content.

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There have to be more of them.

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We have quite a few 
different concepts in Wikidata

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like groups of co-compounds.

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There is a class that is 
of structurally similar compounds, etc.

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If you run a query like this,
this case for the other one,

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other schema that we have
for chemical elements,

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you can do the same thing-- 
you can run it on a single item

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or you can run that on everything 
that is a chemical element.

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This is something 
that I can very much recommend

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having a look at 
if you have not done so already.

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Now, if we go to the automation of things,

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here I'm using a tool called Bioclipse.

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This is something that we worked on
some time ten years ago.

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It's a platform 
for chemistry and biology,

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or cheminformatics and bioinformatics.

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aimed at automating things,

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including visualizations and sorts.

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But I've taken that now 
and developed a number of scripts

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that I can actually run 
on the command line,

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which makes it easier to automate things,
as we will see in a moment,

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and doing all sort of things,

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for example, the classification 
according to the LIPID MAP identifiers,

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that's the scripts all available 
from the GitHub repository here.

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And typically, I have them
create Quickstatements

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because that gets me 
an additional check step

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after I created the Quickstatements 
and see what does data actually look like.

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Annotation of main subjects.

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This one is my script too, 
starting from SMILES

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to actually add chemical compounds
that are not in Wikidata yet,

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which happens a lot.

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So three or four weeks ago 
I added something like 500 compounds

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which our project was looking into

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because these are 
volatile compounds in oils.

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This script adds the compounds.

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They will later on add the annotation 
of which pieces that compound comes from

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and what the properties are.

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Bioclipse itself is based 
on the Chemistry Development Kit

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and a few other libraries.

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This allows me to do the chemistry.

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And this is a very well-validated toolkit.

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The SMILES part has been done 
by John Mayfield.

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I have done a lot of validation 
against other tools.

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And the quality 
is actually really high now,

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comparable or in some cases even better 
of commercial cheminformatics tools.

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It has given me a lot of reassurance

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that the quality checking that we do 
with this tool on Wikidata

00:15:34.923 --> 00:15:37.312
is giving interesting results.

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This is the Quickstatements.

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Quickstatements
is Magnus' work, of course.

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What happens if we take the SMILES,
it calculates the InChI,

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and the InChIKey, it even looks up 
based on the InChIKey,

00:15:52.239 --> 00:15:54.199
if there is a PubChem identifier

00:15:54.199 --> 00:15:58.609
that uses the InChIKey, 
the PubChem identifier,

00:15:58.609 --> 00:16:01.255
to see if this compound 
already is in Wikidata.

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And only if it's not already there,

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then it will actually create
a CREATE statement.

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A bit of automatic classification
here is an option.

00:16:12.822 --> 00:16:15.162
So if I'm adding a class of compounds,

00:16:15.162 --> 00:16:17.980
I can automatically indicate 
what these are all...

00:16:17.980 --> 00:16:19.970
this type of compounds,

00:16:19.970 --> 00:16:22.599
and I can also indicate, if needed,

00:16:22.599 --> 00:16:25.214
if there is a particular article
where I got this information

00:16:25.214 --> 00:16:27.709
from automatically adding references.

00:16:29.836 --> 00:16:32.796
Well, this is what 
the Quickstatements output looks like

00:16:32.796 --> 00:16:35.508
for the annotation of main subjects.

00:16:36.277 --> 00:16:38.149
You've probably seen that as well.

00:16:40.650 --> 00:16:42.820
A newer thing that I started doing

00:16:42.820 --> 00:16:46.003
is actually doing reasoning 
on the data in Wikidata.

00:16:46.003 --> 00:16:51.457
So if I have the SMILES, then I can check 
the molecular formula, for example.

00:16:51.457 --> 00:16:53.427
I can check the InChIKey.

00:16:55.242 --> 00:17:00.498
At some point, what we are going to do
is calculate physicochemical properties

00:17:00.498 --> 00:17:03.865
and see if that matches 
what is in Wikidata.

00:17:04.520 --> 00:17:07.151
This will highlight typos

00:17:07.846 --> 00:17:10.386
or wrong units, for example.

00:17:11.301 --> 00:17:14.591
At this moment... 
so this is a run of this morning.

00:17:14.591 --> 00:17:17.989
What we see here 
is two tests actually failing,

00:17:17.989 --> 00:17:19.539
and this is an example of it.

00:17:19.539 --> 00:17:23.300
This is the InChIKey
that is computed from the isomeric SMILES

00:17:23.300 --> 00:17:26.957
is different from the InChIKey
given in the entry.

00:17:27.700 --> 00:17:32.198
This can result from data 
being pulled in from different resources.

00:17:33.011 --> 00:17:35.889
So these are entries, about 300 of them,

00:17:35.889 --> 00:17:39.479
in the 160,000 chemicals 
that we have in Wikidata.

00:17:39.479 --> 00:17:41.632
So it's a very small amount, really,

00:17:42.392 --> 00:17:45.672
where there is information, 
and someone needs to look at it.

00:17:47.315 --> 00:17:51.008
Now, these are all organic compounds

00:17:51.008 --> 00:17:54.168
and also quite a few inorganic compounds

00:17:54.168 --> 00:17:57.281
where these things just work less well.

00:17:57.618 --> 00:18:01.105
But I found in the other test 
that is failing

00:18:01.105 --> 00:18:04.105
immediately a couple of things 
that are very clearly wrong.

00:18:09.186 --> 00:18:11.759
PubChem is a huge database.

00:18:11.996 --> 00:18:13.846
They do validation as well.

00:18:13.846 --> 00:18:16.622
We are in the process 
of submitting Wikidata there,

00:18:16.622 --> 00:18:18.812
which I'm really happy about.

00:18:19.350 --> 00:18:22.530
It's in the last validation step 
at this moment.

00:18:23.323 --> 00:18:25.643
And this will also mean that PubChem,

00:18:25.643 --> 00:18:29.143
which has something 
like 100 million compounds

00:18:29.143 --> 00:18:31.149
will actually link back to Wikidata.

00:18:31.488 --> 00:18:35.117
It already does this, but via Wikipedia.

00:18:35.387 --> 00:18:36.947
(laughing)

00:18:36.947 --> 00:18:38.434
Do you recognize it?

00:18:38.434 --> 00:18:43.067
With the aforementioned issues there 
of concept mismatches.

00:18:43.591 --> 00:18:45.691
So this will give us a second thing.

00:18:45.691 --> 00:18:49.679
And there, also, 
using the same Bioclipse scripts

00:18:49.679 --> 00:18:51.681
or similar Bioclipse scripts,

00:18:51.681 --> 00:18:53.493
we get validation reports,

00:18:53.493 --> 00:18:57.111
again indicating things 
that chemists should look at.

00:18:59.813 --> 00:19:01.540
That basically wraps it up.

00:19:01.803 --> 00:19:04.955
This is still a work in progress,
the article is in preparation.

00:19:04.955 --> 00:19:08.048
I've been working 
with Finn here in Scholia

00:19:08.048 --> 00:19:10.705
to support this validation.

00:19:11.058 --> 00:19:15.538
We're writing up the full work, 
but for now you can look up this poster.

00:19:15.538 --> 00:19:19.352
The slides are on the program
of this session,

00:19:19.352 --> 00:19:21.825
so you can look at the slides
and look at the details.

00:19:22.560 --> 00:19:24.939
And a quick acknowledgment:

00:19:24.939 --> 00:19:28.370
some of this work has been done 
by a number of grants that I received.

00:19:28.370 --> 00:19:29.836
And thank you very much.

00:19:30.282 --> 00:19:32.475
(applause)

00:19:35.922 --> 00:19:37.902
(chairman) Are there any questions?

00:19:41.142 --> 00:19:42.669
(person 3) Thank you so much for this.

00:19:42.669 --> 00:19:44.196
I am [inaudible],

00:19:44.196 --> 00:19:47.142
and so far, I've been reading articles

00:19:47.142 --> 00:19:49.722
on the [inaudible] Quickipedia 
on different compounds.

00:19:49.722 --> 00:19:53.770
I have a little bit more than 70 articles 
with different compounds--

00:19:53.770 --> 00:19:55.464
just things I come across.

00:19:56.000 --> 00:19:58.021
And my question to you is

00:19:58.021 --> 00:20:02.371
if I want to move my chemistry activity 
from Wikipedia to Wikidata,

00:20:02.371 --> 00:20:05.300
how can I help
in a way that is very friendly

00:20:05.300 --> 00:20:10.031
to somebody who is a beginner 
in that field on Wikidata?

00:20:12.262 --> 00:20:15.832
So, if that compound is in Wikipedia and..

00:20:15.832 --> 00:20:18.092
Sometimes there is 
actually a Wikidata page.

00:20:18.092 --> 00:20:19.972
I occasionally run into this as well,

00:20:19.972 --> 00:20:21.902
in the last couple of months 
not so much anymore

00:20:21.902 --> 00:20:23.791
but this morning, actually.

00:20:25.522 --> 00:20:27.433
And what I typically do then

00:20:27.433 --> 00:20:31.097
is I take the SMILES
from [inaudible] infobox

00:20:31.097 --> 00:20:32.262
from that compound

00:20:32.262 --> 00:20:37.182
or use PubChem to look up the SMILES,
check if the information is complete,

00:20:37.182 --> 00:20:38.817
particularly the stereochemistry,

00:20:39.282 --> 00:20:43.422
and then I use that 
that creates Wikidata item scripts

00:20:43.422 --> 00:20:46.320
to create Quickstatements 
for that compound.

00:20:47.506 --> 00:20:50.016
If there already is a Wikidata item,

00:20:50.016 --> 00:20:55.916
I basically just update these scripts,

00:20:55.916 --> 00:21:00.065
but rather than say, "Create Last,"
I replace the last with the Q-codes

00:21:00.065 --> 00:21:01.710
that that item already has.

00:21:01.710 --> 00:21:04.650
And then it complements 
or it adds this information

00:21:04.650 --> 00:21:06.986
based on the information we had.

00:21:07.922 --> 00:21:10.422
This is [manuable],

00:21:10.422 --> 00:21:13.677
so you can copy-paste 
a number of SMILES, put it in a file,

00:21:13.677 --> 00:21:15.999
and take that.

00:21:18.351 --> 00:21:21.671
Extracting that information to Wikidata 
is not something I've automated yet,

00:21:21.671 --> 00:21:25.088
but this helps me... 
it's a pretty fast process.

00:21:25.782 --> 00:21:28.427
I can show you later 
how to use that software.

00:21:30.728 --> 00:21:32.478
(chairman) Are there other questions?

00:21:33.515 --> 00:21:34.784
So, I have one.

00:21:35.097 --> 00:21:39.825
Do you make an effort 
to, in fact, make this more visible

00:21:39.825 --> 00:21:42.445
in this bioinformatics community

00:21:42.445 --> 00:21:46.671
so that they can start using
this structured data?

00:21:47.566 --> 00:21:49.326
Yeah, I'm actively doing that.

00:21:49.326 --> 00:21:52.256
So what I did not mention 
in this presentation so much,

00:21:52.256 --> 00:21:58.456
but we saw that in...
I'd have somewhere to start here--

00:21:58.456 --> 00:22:00.669
this is an overview 
of different databases.

00:22:01.106 --> 00:22:04.706
A similar plot, which actually 
I do not have on this slide deck

00:22:04.706 --> 00:22:09.387
is the number of different identifiers
that chemical compounds have,

00:22:09.387 --> 00:22:11.347
and I've been working 
with a number of databases,

00:22:11.347 --> 00:22:15.622
like MassBank, 
the Environmental Protection Agency,

00:22:17.184 --> 00:22:18.987
CompTox Dashboard.

00:22:19.507 --> 00:22:21.704
I've added links to the BDB database.

00:22:21.704 --> 00:22:24.159
So I'm working with a number of projects

00:22:24.159 --> 00:22:27.469
for pulling in additional information,

00:22:27.739 --> 00:22:30.030
identifies our links out
to other databases.

00:22:31.192 --> 00:22:33.371
Regarding outreach, yes,

00:22:33.371 --> 00:22:36.961
so that wrong slide deck
that I was showing at the start,

00:22:36.961 --> 00:22:39.283
there was actually 
a presentation two weeks ago

00:22:39.283 --> 00:22:42.148
at an Open Science Meeting 
around chemistry.

00:22:42.503 --> 00:22:45.843
I'm very much pushing this and...

00:22:47.410 --> 00:22:48.951
I see a big future here.

00:22:48.951 --> 00:22:50.780
There's a lot of interest.

00:22:50.780 --> 00:22:54.590
And making people aware 
of the CC0 license,

00:22:54.590 --> 00:22:57.616
that's typically the larger problem.

00:22:58.200 --> 00:23:02.967
So we have to pull in
the information carefully.

00:23:05.303 --> 00:23:06.713
(chairman) Other questions?

00:23:08.643 --> 00:23:10.373
- Okay. 
- Thank you very much.

00:23:10.373 --> 00:23:12.036
(chairman) Can we thank the speaker.

00:23:12.036 --> 00:23:15.257
(applause)