As an active identifier, at times I find myself struggling to find valuable or interesting observations and often having to wade through a sea of low-quality observations (unclear subject, blurry, repetitive, dark lighting, etc.) to find them. It seems that over time, the problem of finding the interesting observations may become more difficult absent the development of tools to accomplish task of surfacing them. This topic is intended to come up with ideas to surface those interesting observations. If any of these ideas appear to have particular merit, Iâd be happy to try to develop it into a feature request.
Broadly, Iâd say that there are two general ways to find the interesting observations: either âdowngradeâ certain low-quality observations or âupgradeâ the interesting ones. By downgrade and upgrade, I only mean make those observations either easier or harder for the average identifier to find. All observations have value, but so does an identifierâs time. The benefit of highlighting valuable observations seems to clear to me â more people will see them & sooner than they would under a business as usual approach. The case for downgrading low quality observations is that by removing these from the pool, other identifiers wonât have to spend their time looking at them (unless they choose to, for some reason.)
Ideas for to make interesting observations easier to find:
⢠Make it easier for identifiers to find species that are newly reported or have low numbers of observations (e.g. <X; X could be 10, 20, or 50+) in a region (could be a US state, country, etc.). Many of these will be incorrectly IDed species suggested by the CV and the earlier they are caught the better. Some may be range expansions or new introductions and also deserve attention. I sometimes come across these observations and if they are obviously wrong I fix them, but many linger for a while and can contribute to wrongly IDed observations getting propagated through an entire region. I am imagining some automated process by which these observations could be searched. I think we all have taxa that we keep an eye on, but there are plenty of taxa that slip through the cracks.
One idea of implementing this idea would be to have an additional filter on the Identify page. Not sure how much server load this would entail.
⢠âUpvoteâ individual observations. Sometimes Iâll come across an observation that looks interesting but I donât know what it is. I would like to be able to flag it in a positive way so that other IDers would see it as well. I could âfavâ it or tag individual IDers but that doesnât always feel right somehow.
Ideas to make low-quality observations less visible:
⢠âdownvoteâ low quality observations. If I see a photo of just tree bark, a shot of a lawn with no obvious subject, a blurry photo, etc I mark these as reviewed and move on. But that still means that all the other IDers are going to see this observation and have to spend their valuable time on it. Iâm looking for ideas on how to relegate these kinds of observations to the bottom of the pile, so to speak.
o More options in the DQA.
ď§ an option for observations with multiple photos covering different species with no overlap (observations that need to be split)
ď§ an option for an observation with no clear focus
ď§ duplicate observations (e.g. same observer posted 5 photos of the same organism within a short time period)
o If the DQA canât be expanded, then just an option to âdownvoteâ a low-quality observation. Weâd have to come up with a list of reasons an observation could be âdownvoted.â Observations marked this way would be harder to find. Maybe if an observation accumulated 3-5 of these downvotes it would go to a separate category. Maybe this option should only be available to IDers with a certain number of observations so it doesnât get abused.
o If an observation has been âmarked as reviewedâ by a certain number of people, it goes into a separate pile. Not sure what the cutoff should be 20? 50? 500? I would want this to correlate to an observationâs quality and not just the date it was uploaded to iNat though.