Co-creation

The project is still running another few months, but the launch last week gives us the opportunity to include feedback from the stakeholders from the Dutch society, many of which have been involved in the project via designathons and hackathons (see doi:10.14573/altex.2407211).

The VHP4Safety platform is a co-creation created by most of the people working on the VHP4Safety grant. Some people focused on innovation and education (RL3), others on the regulatory questions (RL2), and some on the development of the platform (RL1). The research line 1 (RL1) included a work package on the technological development, work package 1.1, and that was led by Maastricht University (Ozan and me) and the Applied University of Utrecht (Dr. Marc Teunis). This project would not be together without the leadership by Prof. dr. ir. Juliette Legler, Dr. Cyrille Krul, and Prof. dr. Anne Kienhuis (see this video).

Not just technology

I have to give a huge shout out to Ozan whom had the daunting task to set up something like OpenRiskNet (doi:10.1016/j.toxlet.2018.06.617), a project with at least twice as much funding for operating and documenting just the technical platform, but also help other partners getting their work on the platform. Also shout outs to Luc who in our group first explored how to translate the OpenRiskNet platform to VHP4Safety with kubernetes from which we concluded that that was not an option for us. And to Sean in our group who introduced us to Docker Swarm.

But that is just one aspect of the technological layers. The design outlined in the original proposal is based on earlier projects, including OpenRiskNet, eNanoMapper, OpenRiskNet, Open PHACTS, NanoCommons, SbD4Nano and many others. It is based on open standards developed and/or adopted by ELIXIR Europe projects and many other organisations.

And then we have not even covered the content on the platform.

A virtual human

Building full virtual human is an ambition. Many digital twins capture just one part of human biology. For safety assessment we need many models, data from experiments, and knowledge bases. And we need a clear narrative that describes how those isolated solutions are integrated so that regulatory questions can be answered. That co-created combination is the launched virtual human platform.

Underlying the VHP is a good bit of open science, though it also integrated proprietary solutions, currently needed to be able to replace animal testing. And our modular co-creation resulted in many separate git repositories. This allows distributed development models and all contributors to take ownership of the development of their contributions. Marc and Frank introduced a agile computing approach that we adopted to guide the development of the full platform.

There is so much to write up about the platform (and we will), but for now I want to highlight a few essential git repositories underlying the 1.0 version of the platform we launched last week (along with the number of contributors in the past two years):

• virtual-human-platform (10 contributors): software that provide the platform UX
• cloud (11 contributors): collects the meta data about (computational) services
• ui-casestudy-config (7 contributors): collects the details of the narratives of the case studies

This includes Aniek, Fabian, Isaac, Ivo, Javier, Jente, Linde, Marvin, Myrthe, Saad, Shakira, and Youp, in addition to the earlier named Ozan and Marc.

This excludes the many contributions via the designathons and hackathons that are behind many of the commits to these repositories. And this also excludes the many other source code repositories for tools and services developed and made available on this VHP, with even more researchers.

Very much aware of all the work that is still ahead of us, I am happy with the important milestone of this release. Thank you to everyone who contributed to this co-creation, all the involved institutes, NWO for the funding, and the Dutch public for the important NWA question.

The project delivered!

Now, about the fediverse…

Mastodon (service by SURF)

Mastodon is one of the more well-known corners of the fediverse, and I blogged about it before. It is intrinsically open, while it has extensive options to make things more private. It is like Twitter but then without the central control. It is unlike Slack, Zulip, and LinkedIn which has clear walls around communities. It also is unlike past efforts like Google Wave and FriendFeed which created much more structured discourse.

But I enjoy Mastodon. It has all the good science, the friendly, helpful people, and I have many options to block people, fediverse servers, and even individual keywords (you can remove anything “PFAS”, for example, something hard in the real world). But you also have linear timeline, with just content of the people you follow.

And, with the SURF social.edu.nl server, every researcher from a SURF-linked research insitute can get an account there via SURFconext (the Mastodon solution may need to be activited by your institute first; if so, ask your institute ICT to enable it). The list of accounts on this SURF Mastodon server shows a veried list of people and organisations, but you can also check this list of 80 Ways to follow Research, Science and Education on Mastodon. Or this list of Wikidata queries.

I think every organization that communicates their research should have at least one open world communication channel, and if they then like to keep their wall-garden LinkedIn account too, that is fine. But societal impact for just a select group of people feels a bit awkward to me.

PeerTube (service by SURF)

But SURF operates a second fediverse server, one using the PeerTube software, also extended with the SURFconext interoperability. PeerTube is a platform to share videos, like YouTube. Just before the winter holiday, I got the opportunity to create two project accounts on SURF’s video.edu.nl, one for the VHP4Safety project and one for the FAIR4ChemNL project.

The cool thing actually is that SURFconext has group accounts via SURFconext Invite (it was earlier called SURFconext Teams), so these two PeerTube channels are operated by two or more people from the project, and the two videos that are now available, have not actually been uploaded by me.

But I am very excited we now have channels to share our video communication, here for VHP4Safety:

And here for FAIR4ChemNL:

The history tells me that our society may sound woke and leftish, in reality it is a continous fight for basic human rights. (Something that plenty have been saying for years.) In this case, a healtht life is the human right.

So, what can I do to make this report more FAIR?

Findable in Wikidata

Since this report has been mentioned in the news, it clearly is notable. The simplest thing to do is thus to just add it Wikidata. Because the DOI of the report had not been recorded yet, I could not let Scholia do it for me. But doing it manually is only a bit more work: Q135222054. The provided metadata on the RIVM website is minimal.

But we can do more. Particularly, because I want people to find this report when they look info knowledge about the 28 studied chemicals, I added main subject annotation using the information in Table 1 in the report. Using Scholia and the CAS registry number in the table, I crosscheck the information in Wikidata is consistent with the report (and visa versa). It was. I then added the Dutch name and acronym for most of them. Some already had the name as in the Table. That gives us a nice “Topic scores” plot for the Scholia page of the report:

The central PFAS bubble is also only one main subject but larger because many the specific PFAS compounds are subclassing PFAS. And you may also note many smaller bubbles. These actually come from main subject annotations of articles cited from the report. Because I added a few of them too. Not all, because many are not in Wikidata (yet).

Findable in WikiPathways

But since 16 of these compounds are readily found in human blood samples, that is handy knowledge when doing metabolomics (on blood samples). Or (and I leave that to later blog post), we can map the experimental data for Dordrecht versus the rest of The Netherlands to the PFAS compounds. That is relevant to research by VHP4Safety. There are many ways to see if you have PFAS in your dataset, but since we have many controlled lists of genes in metabolites, I added one for common PFAS in human blood samples. Well, the 16 common in Dutch blood samples:

Each metabolite here is annotated with their Wikidata identifier, allowing us to map experimental data on top of it. And we get links out to other databases almost for free:

And the link to Wikidata actually links to Scholia, so for the PFOA in the above example, we can quickly see the boiling point, decomposition point, and melting point of this PFAS. And literature with undoubtedly even more knowledge about this PFAS:

Now, these two steps were mostly manual: drawing WP5579 in WikiPathways and adding the report annotations (main subject and cites) in Wikidata.

Findable in the VHP4Safety Compound Wiki

As part of the VHP4Safety project, I am collecting information on chemicals studied in the context of toxicology, safety, and risk assessment. Often specific collections of compounds studied as a whole. This report is such a collection and provides experimental data on these compounds. So, I want this report to be findable for the VHP4Safety Compound Wiki too. Creating the collection is a manual step: Q5145.

Now, because both Wikidata and our VHP4Safety Compound Wiki (a Wikibase instance) are semantic and support, I can use SPARQL to create instructions to link the 28 compounds to the new collection. Now, arguably, that can be done manually too, and maybe faster, for larger collections this is harder. So, I dug up my earlier notes and got some useful things together.

This query lists all 28 PFAS linked to the report in Wikidata:

SELECT ?pfas ?pfasLabel WHERE {
  wd:Q135222054 wdt:P921 ?pfas .
  ?pfas wdt:P31 wd:Q113145171 .
  SERVICE wikibase:label { bd:serviceParam wikibase:language "[AUTO_LANGUAGE],mul,en". }
}

Using federation powers, I can use this for a SPARQL query, and return the results in QuickStatements that say this VHP compound is part of the VHP collection:

PREFIX wb: <https://compoundcloud.wikibase.cloud/entity/>
PREFIX wbt: <https://compoundcloud.wikibase.cloud/prop/direct/>

SELECT (SUBSTR(STR(?cmp),45) AS ?qid) ?P21 WHERE {
  ?cmp wbt:P5 ?wikidata .
  SERVICE <https://query.wikidata.org/sparql> {
    wd:Q135222054 wdt:P921 ?pfas .
    ?pfas wdt:P31 wd:Q113145171 .
    BIND (substr(str(?pfas),32) AS ?wikidata)
  }
  BIND ("Q5145" AS ?P21)
}

I actually had to add 5 PFAS compounds in the VHP4Safety Compound Wiki first. That follows the same procedure for how I have been adding chemical compounds to Wikidata (see also this preprint). The input cas.smi has the (missing) SMILES, Wikidata QID, and English label:

C(CS(=O)(=O)O)C(C(C(C(C(C(F)(F)F)(F)F)(F)F)(F)F)(F)F)(F)F       Q27063662       6:2 Fluorotelomer sulfonate
CN(CC(=O)O)S(=O)(=O)C(C(C(C(C(C(F)(F)F)(F)F)(F)F)(F)F)(F)F)(F)F Q126605979      MeFHxSAA
CN(CC(=O)O)S(=O)(=O)C(C(C(C(F)(F)F)(F)F)(F)F)(F)F       Q126682412      MeFBSAA
C(=O)(C(C(F)(F)F)(F)OC(C(C(F)(F)F)(F)F)(F)F)O[H]        Q29387971       2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)propanoic acid
C(C(C(=O)O)(F)F)(OC(C(C(OC(F)(F)F)(F)F)(F)F)(F)F)F      Q81981675       4,8-Dioxa-3H-perfluorononanoic acid

For reference, this is the command line I used to create QuickStatement instructions:

groovy createWDitemsFromSMILES.groovy -w compoundcloud.wikibase.cloud -c Q2368 -d P5 -l -i wikidata -a P11

Final remark

Are these 16 the only PFAS in our body? With 28 studied out of a potential seven million, I doubt it.

But in addition to the data model for SPARQL as research output (see doi:10.32388/ZNWI7T.2), the paper also introduces the sparql-example-utils software that I was first introduced with at the recent October Scholia hackathon.

But I have/had some features I like to see added. The first is provenance. Who is the author/contributor of the SPARQL query? Is there a open license for it, or perhaps public domain? How do I give attribution if I reuse the SPARQL query? These things matter in a modern recognition and rewards world where is room for everyone’s talent. A set of good SPARQL queries may be more valuable than a ten-page Jupyter notebook (and the other way around). So, I started writing patches. And I created a custom jar so that I can see these patches in action in our growing list of SPARQL queries (here a WikiPathways query):

I started collecting SPARQL queries for ChEMBL, WikiPathways, and VHP4Safety. These queries are often part of other interfaces but we can easily extract the original SPARQL from the Turtle files behind these pages.

One such material is the new project paper about VHP4Safety, The Virtual Human Platform for Safety Assessment (VHP4Safety) project: Next generation chemical safety assessment based on human data (doi:10.14573/altex.2407211). It is a fun project to work in, ambitious, and in a vibrant community making steps in open science. That means that a lot of what we is core science, but the science comes from many different disciplines, and it is as much natural sciences as it is humanities.

So, we somewhere during the project we started organizing hackathons. Some of us had plenty of experience with that already, but these are hackathons from fields where this has not been as common, perhaps. But is has been fun, e.g. see this write up of the third hackathon.

There is a lot more I should be writing about VHP4Safety, and I will try, but for now I will limit it to these pointers:

• the main VHP4Safety website: https://vhp4safety.nl/
• our documentation platform: https://docs.vhp4safety.nl/
• our catalogue of cloud services: https://cloud.vhp4safety.nl/
• our common language: https://glossary.vhp4safety.nl/

And we try to register our solutions as widely as possible, e.g. with national and ELIXIR indices:

• our Taxila.nl section
• out ELIXIR TeSS section

Note the depiction of the undefined (CIP) stereochemistry on two atoms. Thanks to Adriano and John for working that out.

More about CXSMILES in Wikidata in this Dagstuhl meeting results write up.