In this paper (doi:10.1038/s41597-024-03324-x), Ammar explores this notion and compiled more than 200 maturity indicators in the category R1.3 resulting from 12 different community standards. For example, this includes minimal reporting standards. There is overlap in needs, but they often also have a different focus. The conclusion here: different (re)use cases have different needs, and data not usable to one use case can be sufficiently FAIR for another. Of course, ideally, it would be FAIR enough for all use cases.

Ammar formalizes the maturity indicators and links the comming maturity indicators to various use cases. That means that when you determine the indicator values for your data, people can immediately lookup how this data can be reused. And, the generator of the data can immediately see how the data would need to be improved to widen the reusability. How FAIR can we get?

His proposal has already been further explored in two other papers, one around data sharing (doi:10.1038/s41596-024-00993-1, see also this blog post) and one around QSAR modelling (doi:10.1016/j.impact.2023.100475, see also this blog post).

The below screenshot shows what an analysis using this approach can look like:

History

In this post, let’s look at FAIRsharing. It is “A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies” [0,1].

The ELIXIR Toxicology Community (we) maintains the toxicology corner of this database and members of our community have been adding toxicology-related databases, relevant standards. On the side of the policies we are falling a bit short: fairsharing.org/Toxicology.

Why adopt FAIRsharing

FAIRsharing is one place where metadata can be shared about your databases. It helps make your resources and research more FAIR and explains people how your work relates to other work (fairsharing.org/graph/3496):

What you can do

Get an account (with your ORCID or GitHub account) and add resources important to your research, your projects, your work generally. Particularly, (data) policies and standards you are expected to comply with are useful. Also, links between various resources. For example, if some (project) database complies with an important policy or standards, this is worth seeing show up.

Alternatively, join the ELIXIR Toxicology Community mailing list and post the missing resource there, or use our issue tracker at github.com/elixir-europe/toxicology-community/issues/.

Let’s make toxicology more FAIR.

0.https://www.nature.com/articles/s41587-019-0080-8 1.https://scholia.toolforge.org/work/Q64084285

Slice of the spreadsheet in the supplementary info.

Just some bit of cleaning I scripted today for a number of toxicology end points in a database published some time ago the zero-APC Open Access (CC_BY) journal Beilstein of Journal of Nanotechnology, NanoE-Tox (doi:10.3762/bjnano.6.183).

The curation I am doing is to redistribute the data in the eNanoMapper database (see doi:10.3762/bjnano.6.165) and thus with ontology annotation (see doi:10.1186/s13326-015-0005-5):

recognizedToxicities = [
  "EC10": "http://www.bioassayontology.org/bao#BAO_0001263",
  "EC20": "http://www.bioassayontology.org/bao#BAO_0001235",
  "EC25": "http://www.bioassayontology.org/bao#BAO_0001264",
  "EC30": "http://www.bioassayontology.org/bao#BAO_0000599",
  "EC50": "http://www.bioassayontology.org/bao#BAO_0000188",
  "EC80": "http://purl.enanomapper.org/onto/ENM_0000053",
  "EC90": "http://www.bioassayontology.org/bao#BAO_0001237",
  "IC50": "http://www.bioassayontology.org/bao#BAO_0000190",
  "LC50": "http://www.bioassayontology.org/bao#BAO_0002145",
  "MIC":  "http://www.bioassayontology.org/bao#BAO_0002146",
  "NOEC": "http://purl.enanomapper.org/onto/ENM_0000060",
  "NOEL": "http://purl.enanomapper.org/onto/ENM_0000056"
]

With 402(!) variants left. Many do not have an ontology term yet, and I filed a feature request.

Units:

recognizedUnits = [
  "g/L": "g/L",
  "g/l": "g/l",
  "mg/L": "mg/L",
  "mg/ml": "mg/ml",
  "mg/mL": "mg/mL",
  "µg/L of food": "µg/L",
  "µg/L": "µg/L",
  "µg/mL": "µg/mL",
  "mg Ag/L": "mg/L",
  "mg Cu/L": "mg/L",
  "mg Zn/L": "mg/L",
  "µg dissolved Cu/L": "µg/L",
  "µg dissolved Zn/L": "µg/L",
  "µg Ag/L": "µg/L",
  "fmol/L": "fmol/L",

  "mmol/g": "mmol/g",
  "nmol/g fresh weight": "nmol/g",
  "µg Cu/g": "µg/g",
  "mg Ag/kg": "mg/kg",
  "mg Zn/kg": "mg/kg",
  "mg Zn/kg  d.w.": "mg/kg",
  "mg/kg of dry feed": "mg/kg",
  "mg/kg": "mg/kg",
  "g/kg": "g/kg",
  "µg/g dry weight sediment": "µg/g",
  "µg/g": "µg/g"
]

Oh, and don’t get me started on actual values, with endpoint values, as ranges, errors, etc. That variety is not the problem, but the lack of FAIR-ness makes the whole really hard to process. I now have something like:

prop = prop.replace(",", ".")
if (prop.substring(1).contains("-")) {
  rdf.addTypedDataProperty(
    store, endpointIRI, "${oboNS}STATO_0000035",
    prop, "${xsdNS}string"
  )
  rdf.addDataProperty(
    store, endpointIRI, "${ssoNS}has-unit", units
  )
} else if (prop.contains("±")) {
  rdf.addTypedDataProperty(
    store, endpointIRI, "${oboNS}STATO_0000035",
    prop, "${xsdNS}string"
  )
  rdf.addDataProperty(
    store, endpointIRI, "${ssoNS}has-unit", units
  )
} else if (prop.contains("<")) {
} else {
  rdf.addTypedDataProperty(
    store, endpointIRI, "${ssoNS}has-value", prop,
    "${xsdNS}double"
  )
  rdf.addDataProperty(
    store, endpointIRI, "${ssoNS}has-unit", units
  )
}

But let me make clear: I can actually do this, add more data to the eNanoMapper database (with Nina), only because the developers of this database made their data available under an Open license (CC-BY, to be precise), allowing me to reuse, modify (change format), and redistribute it. Thanks to the authors. Data curation is expensive, whether I do it, or if the authors of the database did. They already did a lot of data curation. But only because of Open licenses, we only have to do this once.

Anyways, going to the Predictive Toxicology workshop, thanx to the bursary award I received from echeminfo (see Oxford, August 2010: eCheminfo Predictive ADME & Toxicology 2010 Workshop).

This afternoon I walked around a bit, watching all the old buildings. But I guess being here without anyone to share it with, and that it looks just like Cambridge, makes me not-so-much impressed. Moreover, it’s too busy with tourists and people randomly wearing Oxford University sweatshirts. Small and nice was the Museum of the History of Science, with some nice chemical pieces, like this one:

Buildings like the Radcliffe Camera are nice on the outside, but closed. Seems I have to become a fellow first. This is what it looked like today:

Quite interesting too was the Oxford University Press shop. I’m a sucker for books. Apparently, you can just write a book and publish it. For example, an extensive list of dictionaries on about anything… and since I have been writing several book chapters right now, perhaps this is actually an interesting route…

But the question is, of course, how long will we keep reading books… they’re the hamburgers of educational material… Kindle and alikes will soon drop in price, and cost some €30 euro. But e-book prices will have to drop too, and I still do not get why an e-book is more expensive than a paperback… (see Amazon, the Kindle edition is more expensive than the paperback??). But then again… they are rich, and I am not.

There was some recent talk about the fact that no one can be Open to the full. You either do Open Data or Open Source, and make a living from the rest. That’s where I nicely show I know bullocks of economics. I do BODR, CDK, … all Open, all for free.

OK. That’s a plus for Oxford… it makes you think about things. Perhaps there is something to morphogenetic fields…

The meeting is also bound to be fun. I have not done much in the area of toxicology other than the more general QSAR/QSPR model building with chemometrics. But I have been recently taking to Nina and other of the OpenTox community, and started to play a bit with the data and computation API they are developing.

I started a Bioclipse plugin recently (see screenshot), and placed the source code in this bioclipse-opentox Git repository on Gitorious (my GitHub account is already over the formal limit). The functionality is still quite limited, and the manager currently only provides methods to download data sets (myexperiment:1192):

// query a service using the OpenTox API 1.1
// See: http://www.opentox.org/dev/apis/api-1.1

var service = "http://apps.ideaconsult.net:8180/ambit2/";

var datasets = opentox.listDataSets(service);
for (set=0; set<datasets.size(); set++) {
  var dataset = datasets.get(set);
  js.say("Downloading set: " + dataset);
  ui.open(
    opentox.downloadDataSetAsMDLSDfile(
       service, dataset, "/OpenTox/ambit" + dataset + ".sdf"
    )
  )
}

Behind this plugin is again the RDF plugin, as OpenTox uses RDF too, a few simple SPARQL queries was all that needed to be defined. And again, the Bioclipse pluigin code base is pretty small.