Posted by
Labels: #ACSPhilly #skolnik2012 Bioclipse CDK opentox R RDF rrdf semantic web toxicology
0

Add a comment

Hi all, as posted about a year ago, I moved this blog to a different domain and different platform. Noting that I still have many followers on this domain (and not on my new domain, including over 300 on Feedly.com along).

This is my last post on blogger.com. At least, that is the plan. It has been a great 18 years. I like to thank the owners of blogger.com and Google later for providing this service.

Some days ago, I started added boiling points to Wikidata, referenced from Basic Laboratory and Industrial Chemicals (wikidata:Q22236188), David R. Lide's 'a CRC quick reference handbook' from 1993 (well, the edition I have).

Just a quick note: I just love the level of detail Wikidata allows us to use. One of the marvels is the practices of 'named as', which can be used in statements for subject and objects.

I am still an avid user of RSS/Atom feeds. I use Feedly daily, partly because of their easy to use app. My blog is part of Planet RDF, a blog planet. Blog planets aggregate blogs from many people around a certain topic. It's like a forum, but open, free, community driven.

This blog is almost 18 years old now. I have long wanted to migrate it to a version control system and at the same time have more control over things. Markdown would be awesome.

4

The role of a university is manifold. Being a place where people can find knowledge and the track record how that knowledge was reached is often seen as part of that. Over the past decades universities outsources this role, for example to publishers.

I am pleased to learn that the Dutch Universities start looking at rankings of a more scientific way. It is long overdue that we take scientific peer review of the indicators used in those rankings seriously, instead of hiding beyond fud around the decline of quality of research.

A bit over a year ago I got introduced to Qeios when I was asked to review an article by Michie, West, and Hasting: "Creating ontological definitions for use in science" (doi:10.32388/YGIF9B.2). I wrote up my thoughts after reading the paper, and the review was posted openly online and got a DOI.

Some years ago we started the ELIXIR Toxicology Community. It has been an interesting journey, partly covered in this whitepaper). We started with interaction we had in several projects already, but particularly the potential. I see this.

When last week in a large (and relevant) Dutch research event ChatGPT came up, and that this was going to change the world. Even the critiques came up, but were effectively disregarded with "these methods get better very quickly". This is not untrue, but not really true either.

I think that if you want to make your knowledge FAIR, you should use an open license and RDF. Simple. Now, not everything is knowledge. A lot of data is, but a lot more is not, think raw data. Using RDF to explain a protein sequence is still something that makes me feel uneasy.

When I joined the BiGCaT research group in 2012 I was particularly interested in the open science approach of WikiPathways. As a chemist by training and researcher in cheminformatics, metabolites and their metabolic reactions took my particular interest.

Some years ago we started the ELIXIR Toxicology Community. It has been an interesting journey, partly covered in this whitepaper). We started with interaction we had in several projects already, but particularly the potential. I see this.

Okay, the Pilot is over ending with 17 papers, 16 of which have CiTO annotations (and so far 4 J.Cheminform. papers after the pilot), but my interest in the Citation Typing Ontology continues and we just need more adoption.

Datasets as source of annotations

So, here's a quick Wikidata update.

I have received the request to write up the final reporting and the paid practical work has been completed (we already said goodbye to Helena almost a month ago). After the hackathon last month, we released BridgeDb Webservice 2.1.0 and actually had this online for about a week.

Ammar Ammar in my group just published the second half of his cheminformatics study into what happens with binding affinities when the proteins show amino acid changes, selected based on world-wide population statistics.

This week a colleague whom I highly respect asked me if I was already so busy (regularly close to overworked), why did I give talks and often free up my time for that. A valid question. The Drew-reaction here is to say "it is part of scientific communication and dissemination".

This week the 2nd NWO Open Science BridgeDb grant hackathon took place. In all honestly, I had hoped we could open it up to a much larger community, but in our defense, the grant team is small, and we were flooded with various viruses in The Netherlands.

It is now almost thirteen years ago that Prof. Shotton wrote their article about CiTO, the Citation Typing Ontology (doi:10.1186/2041-1480-1-S1-S6).

Sometimes I think back about how Scholia started, and then I think I remember a Twitter discussion. Twitter was a social platform that was unable to fight hate speech. I left it last year in favor of Mastodon.

Anyway, I did some digging today and found this thread from October 8-9 2016.

Triggered by the "reflections on your career" in the announcement I decide to give the Open Science Challenge by Heidi Seibold a try: "12 emails over the course of a month that are designed to help you on your Open Science journey."

I will post here my replies to the various challenges, by linking

One of the outcomes of the EpiLipidNET COST action is a paper about the data analysis of experimental lipidomics data: Guiding the choice of informatics software and tools for lipidomics research applications (doi:10.1038/s41592-022-01710-0).

So, I had a lot of teaching and that besides project deliverables and final reports, a few project meetings, it left me with little time to blog my monthly BridgeDb NWO grant update. But here goes, as a lot did happen in the background.

Identifiers are central to FAIR. Our BiGCaT research group (see also this Scholia page) studies how to answer biological questions and identifiers are then essential to integrate experimental data (e.g. omics data) with existing knowledge (e.g. biological pathway databases).

When you get asked to contribute your expertise, you do. To me, this is perfectly in line with doing open science. Sometimes it's a skill rather than knowledge. But when this helps a project that practices open science I would be insane not to.

1

Currently, I am mostly working on chemistry in Wikidata but recently also validated CAS registry numbers in Wikipedia. Previously, I added many CompTox Dashboard identifiers to Wikidata. Now, Wikipedia ChemBoxes are slowly picking up more data from Wikidata, but are hesitant for a number of reasons.

There are multiple initiatives to support the migration from Twitter to Mastodon (see also this blog post).

In August I reported about 2D depiction of (CX)SMILES in Wikidata via linkouts (going back to 2017).

Forget the journal impact factor and the H-index. You want your research being used. A first approximation of that is getting cited, sure.

While Nature calls for more action on open metadata (doi:10.1038/d41586-022-02915-1), the concept of open citations remains a central feature of our knowledge dissemination.

I actually got instructions at some point in the past too, forgot about it, and then Daniel reminded me about it:

The trick at @ZENODO_ORG is to type to type "cc0-1.0".

I keep forgetting this too and then go back to emails on the matter. Would be great if this could be made more user friendly.

After erasing some sentences of all the things on my mind, basically, two things I want to report on.

In the end it was a very simple change today (huge thanks to Nikki!), but Wikidata now escapes SMILES and CXSMILES (P10718) with the formatter URL (P1630)!

That means that the link to CDK Depict now also works for SMILES (P233 and P2017) with a triple bond in it :) And because Adriano created the s

3

Already 3 months ago I visited Dagstuhl for the second time. The weather was much better than in the January right before the start of the pandemic.

The period 2005-2010 was when chemistry world explored (and solved) data sharing on the internet, particularly in the web. The reason was simple: humans like to read a story around data (perhaps related to how we are used to learn) instead of being presented it in a unsorted box.

It has been a long winter/spring. Last year summer I was hopeful most of the pandemic was behind us, and started with fresh energy the autumn season. Well, so did many others. Septembers are always very busy because of this, but this even more than others.

This fourth post is after the NWO Open Science BridgeDb Hackathon #1 (the second will be in January) this week, but I will write a separate post about that. Instead, this post is about what happened since the third post.

In a year where "data available upon request" is a good intention at best (doi:10.1016/j.jclinepi.2022.05.019), the need for FAIR and Open data is more than ever.

The use of the number of citations to reflect quality is tempting but quite problematic. The citation count is nevertheless used abundantly and feeds our addiction to become better. It has been a while, but I didn't forget the first time I was cited.

4

There is a ton of knowledge still not disclosed in a FAIR way. I am proud to have contributed to this new paper about the new LOTUS initiative for open knowledge management in natural products research (doi:10.7554/eLife.70780).

Open Science is happening. The merits are no longer theoretical or idealistic but tangible. Research is faster than ever, more vetted than ever (think PubPeer), more cited than ever. Fairly, not just because of Open Science, but open access causes readership causes impact causes citations.

1

I joined the BiGCaT research team because of their open science work on WikiPathways (Scholia summary). To me, WikiPathways is an essential tool to move forward. It's different from Reactome and KEGG and I think for good reasons (read the articles to get some idea).

Text
Text
This blog deals with chemblaics in the broader sense. Chemblaics (pronounced chem-bla-ics) is the science that uses computers to solve problems in chemistry, biochemistry and related fields. The big difference between chemblaics and areas such as chem(o)?informatics, chemometrics, computational chemistry, etc, is that chemblaics only uses open source software, open data, and open standards, making experimental results reproducible and validatable. And this is a big difference!
About Me
About Me
Popular Posts
Popular Posts
Pageviews past week
Pageviews past week
1677
Blog Archive
Blog Archive
Labels
Labels
Loading
Dynamic Views theme. Powered by Blogger. Report Abuse.