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Taxacom: [EXT] Re: Basis of record terms

Mary Barkworth Mary.Barkworth at usu.edu
Wed Jul 27 05:56:17 CDT 2022


Thank you to everyone who responded, both publicly and privately.  Now I like distinguishing between human and machine observations by the method of identification, but what is identification by DNA sequence?  A term used in one of the email threads was "Evidence", which would have a subdivision "Specimen" but allow for inclusion of other kinds of evidence such as videos, smell, fragment in scat, etc. I am going to be doing some more thinking, but I appreciate having my mind pushed out of its rut.

Mary




-----Original Message-----
From: Taxacom <taxacom-bounces at lists.ku.edu> On Behalf Of Donald Hobern via Taxacom
Sent: Tuesday, July 26, 2022 5:52 PM
To: taxacom at lists.ku.edu
Subject: [EXT] Re: Taxacom: Basis of record terms

Hi Mary,

As Debbie notes, this is an area where discussion and work continues, but here are some comments that I feel should guide us.

The basis of record values should serve as useful filters for end-users and I think that provides some answers to what we should do, but we arrived at where we are today because of the history of our digital networks.

The origins of our basisOfRecord terms are from a couple of decades ago.
The first DwC/ABCD implementations (DiGIR/MaNIS and BioCASE) were largely modeled on online library catalogues, with specimens replacing books. As these solutions expanded to accommodate other biodiversity data, the perspectives of these original communities shaped the terminology.
Voucherless observations were seen as degenerate specimen records, basically ones where the specimens no longer exist. In other words, specimens==good, observations==not-so-good. It took a little while longer to consider why "observations" may for some purposes be very good (large volumes, sample events, etc) and what subcategories were hidden inside it.
As a split between human and machine observations developed, it was still largely seen as a subdivision within the voucherless category.

I believe that in fact we are just entering the third age of biodiversity recording and that we need to think first and foremost of a three-way division in our occurrence records. The human/machine division is critical, but it is really about how the identification is derived rather than whether technology (cameras, audio recorders, sequencers, etc.) was used.

Here is how I use these three top-level categories:

   1. *Specimen* - A specimen, tissues or DNA are held somewhere. *The
   reason we trust the identification is because it can be reviewed and
   verified from this material (with varying degrees of difficulty).*
   2. *Human observation* - A (hopefully knowledgeable) observer reports
   that they saw a specimen at a given time and place. Digital evidence may be
   provided (photos, audio, even a sequence). For me, a camera trap image
   would be a human observation if the identification was provided by a human
   reviewing the image and identifying whatever was detected. *The reason
   we trust the identification is because of the level of trust we give to the
   observer or the community (think iNaturalist) that provides the
   identification.*
   3. *Machine observation* - An unattended (or incompletely supervised)
   process identified an organism without a human expert directly identifying
   each example. Examples would include AI identifications based on images
   from a network of camera traps or audio recorders or even satellites, and
   species identifications from eDNA. *The reason we trust the
   identification is because of the level of trust we have in the algorithms
   used and the reference libraries on which they may depend.*

Each of these can usefully be subdivided into different categories, but this is the fundamental split I want to understand when I consume DwC data.

Donald
--

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