The OpenScience Laboratory The Open University

iSpot Forum

UK recording systems

This may be of interest https://nbn.org.uk/news/introducing-inaturalist-for-the-uk/
It looks like NBN is now has launched an iNaturalist node. Its interesting though that they aren’t planning to incorporate the records into the NBN Atlas. Do iSpot records go into the NBN Atlas?

There are a few iSpot records on NBN but they have gone via other schemes and socs or irecord. We are currently updating our UK species dictionary and once that is done it will make it much easier for iSpot data to go onto NBN.

I have been treating iNat entries in the Record Portals with GREAT suspicion for a long time. I often EXCLUDE iNat Records from my analyses.
In iNat, Research Grade (RG) reciords are automatically loaded into GBIF when they become RG,
RG is ‘awarded’ after a single agreement. I have challenged quite a few of those, my opinion was strengthened by the replies. Admin did not like my investigation, reminding me that Citizen Science was the upheld theme, At least two Curators agreed that it did not seem a good system
I DO hope that iSpot records are not harvested just because someone is ‘As sure as I can be’ or that the likely banner is present. iSpot is crammed with wrong IDs carrying the likely Banner and agreements, though the latter are RARE in incorrect ones.
The claim that iNat is an ‘online social network’ pales against iSpot’s strong sense of social cohesion and responsibility.
Where are the long chatty, sometimes critical, comment trails in iNat?

my understanding is that “research grade” on iNaturalist just means that a record has more than one agreeing identification and some threshold of consensus. I don’t think its meant to mean 100% correct IDs all the time. I wonder if anyone has tried to quantify the accuracy of iSpot and iNaturalist records?

Re: long chatty comment trails - I glanced a the blog and there are some nice stories about interesting records highlighted there - such as this one https://www.inaturalist.org/blog/46272-a-euphorbia-observation-in-brazil-provides-tantalizing-natural-history-clues-observation-of-the-week-2-8-21 which links to this record https://www.inaturalist.org/observations/67163775 where theres a long chatty comment trail - its also interesting that one of the experts explicitly mentions not relying on “research grade” as a perfect metric as I suspected.

What percentage of misIdentifications in a dataset be it iSpot or iNat or GBIF or NBN do you think would be tolerable for use in scientific analyses? 95% accuracy? 99% accuracy? It seems like theres a quality and quantity tradeoff but it wouldn’t be hard for either system to tweak their algorithms to meet the desired threshold

Thanks James. I think we could each make a case to strengthen various theories here.

There are THOUSANDS of Likely (RG?) IDs in iSpot, some with agreements, that are wrong…
There are 40 observations over two recent days here (in iSpot) that have no comments at all and will probably never have.
My case is strong though, there are many thousands of Records in the GBIF Portal that arise from the iNat harvesting software, that are incorrect. I find them regularly.
They are commonly the FIRST ID in the Dictionary Drop-down and agreed to by ‘unqualified’ people.
A quick visit to RG Euphrasia in iNat is fairly convincing.
https://www.inaturalist.org/taxa/118893-Euphrasia-nemorosa/browse_photos

There appear to be no (stated) iSpot records (data) in either GBIF or NBN.
My only interest here (I subscribe and upload to both sites) relates to reasonable accuracy of World and National Records. I would not like to (I cannot) put a percentage of accuracy required. I really hope iSpot is never trawled for unverified Likely IDs to be added to World- or National-Recording schemes.
“,will make it much easier for iSpot data to go onto NBN” is from miked’s comment. I suspect he has a proviso in mind!
I have a few iNat RG records in the GBIF Portal
I may be the only person in iSpot who has ever tried (and failed) to grade the Probability of Accuracy in Observations. I subjectively based it on the number and ‘quality’ of agreements and the clarity and number of photos.

I don’t think it is a matter of achieving an acceptably low percentage of wrong records. False records are likely to be outliers in the dataset so will have more significance than just the proportion they comprise.

but surely we don’t presume that any source of biodiversity data has 100% identification accuracy. For example, the museum world has a significant problem in this regard https://www.forbes.com/sites/shaenamontanari/2015/11/17/half-the-worlds-museum-specimens-are-wrongly-labeled-but-who-is-to-blame

I agree, but I haven’t said anything about assuming 100% accuracy.

If you aren’t saying we need 100% accuracy then you are implying that there is some acceptable percentage of wrong records. What is this percentage if not 100%

And has anyone checked whether citizen science sources like iSpot or iNaturalist have higher errors than, for instance, museum collections. These are the 533 GBIF records of Agamid Dragons from the British Museum of Natural History


I can tell you for sure that this Lithuanian record is an error

That puts the accuracy rate for the British Museum Agamid Dragons at at least < 99.9% (probably lower) - why are we not up in arms about this error?

I think that is what is called a selective quote. You missed out the first few words which reverse the meaning.

There was an assessment a few years ago of the accuracy of the ispot identifications and it found that for certain groups of organisms such as birds or plants they were very well identified, similar error rate to that which experts have. With other groups such as fungi where often more features than are shown in a photo are needed the error rate was higher. It would be possible to repeat this analyis again now with more data.

1 Like

Aha - how interesting Mike.
BUT how do you know that IDs in iSpot are accurate?
There are very few IDs with ‘conclusive’ supportive evidence.
No ‘expert’ I know would ID from a photo alone - that would be the basis of 90% (my guess) of iSpot’s Observations.
Actually you used the usefully ‘vague’ expression “they were very well identified…”