Life on Earth is sustained by complex interactions between organisms
and their environment. These biotic interactions can be captured in
datasets and published digitally. We present a review process of such an
openly accessible digital interactions dataset of known origin, and
discuss its outcome. The dataset under review, named
globalbioticinteractions/ucm-ucmc, is 5.69MiB in size and contains 9,592
interaction with 2 unique types of associations (e.g., interactsWith)
between 889 primary taxa (e.g., Lasioglossum) and 451 associated taxa
(e.g., Penstemon degeneri). The report includes detailed summaries of
interactions data as well as a taxonomic review from multiple
catalogs.
Introduction
Data Review
Data review can be a time consuming process, especially when done
manually. This review report aims to help facilitate data review of
species interaction claims made in datasets registered with Global
Biotic Interactions (Poelen, Simons, and Mungall 2014). The
review includes summary statistics of, and observations about, the
dataset under review:
University of Colorado Museum of Natural History Entomology
Collection
https://github.com/globalbioticinteractions/ucm-ucmc/archive/60530dcc82d33c9675a4026ad60dc40bea8f2a91.zip
2024-12-22T00:25:52.626Z
9d8d9fe4018eff3a20ab33e4dfc6495b8c5a1460c2d672b1b299fb71c7dc945a
For additional metadata related to this dataset, please visit https://github.com/globalbioticinteractions/ucm-ucmc
and inspect associated metadata files including, but not limited to,
README.md, eml.xml, and/or globi.json.
Methods
The review is performed through programmatic scripts that leverage
tools like Preston, Elton, Nomer combined with third-party tools like
grep, mlr, tail and head.
The review process can be described in the form of the script below
1.
# get versioned copy of the dataset (size approx. 5.69MiB) under review
elton pull globalbioticinteractions/ucm-ucmc
# generate review notes
elton review globalbioticinteractions/ucm-ucmc\
> review.tsv
# export indexed interaction records
elton interactions globalbioticinteractions/ucm-ucmc\
> interactions.tsv
# export names and align them with the Catalogue of Life using Nomer
elton names globalbioticinteractions/ucm-ucmc\
| nomer append col\
> name-alignment.tsv
or visually, in a process diagram.
You can find a recent copy of the full review script at check-data.sh.
Results
In the following sections, the results of the review are summarized
2. Then, links to the detailed review
reports are provided.
Biotic Interactions
In this review, biotic interactions (or biotic associations) are
modeled as a primary (aka subject, source) organism interacting with an
associate (aka object, target) organism. The dataset under review
classified the primary/associate organisms with specific taxa. The
primary and associate organisms The kind of interaction is documented as
an interaction type.
The dataset under review, named globalbioticinteractions/ucm-ucmc, is
5.69MiB in size and contains 9,592 interaction with 2 unique types of
associations (e.g., interactsWith) between 889 primary taxa (e.g.,
Lasioglossum) and 451 associated taxa (e.g., Penstemon degeneri).
An exhaustive list of indexed interaction claims can be found in csv and tsv archives. To facilitate
discovery, the first 500 claims available on the html page at indexed-interactions.html are shown
below.
The exhaustive list was used to create the following data summaries
below.
Most Frequently Mentioned Interaction Types (up to 20 most
frequent)
interactionTypeName
count
interactsWith
9540
adjacentTo
52
Most Frequently Mentioned Primary Taxa (up to 20 most
frequent)
sourceTaxonName
count
Lasioglossum
411
Andrena
387
Bombus huntii
330
Bombus centralis
253
Bombus rufocinctus
191
Bombus appositus
165
Halictus tripartitus
141
Paratiphia
137
Bombus fervidus
134
Bombus pensylvanicus
133
Bombus flavifrons
125
Dendroctonus ponderosae
124
Bombus sylvicola
108
Bombus nevadensis
103
Bombus bifarius
102
Bombus morrisoni
83
Eurygaster
74
Augochlorella aurata
74
Osmia
72
Most Frequently Mentioned Associate Taxa (up to 20 most
frequent)
targetTaxonName
count
Penstemon degeneri
566
Salix
488
Tamarix
400
Chrysothamnus
369
Melilotus
367
Asclepias
342
Helianthus
306
Pinus ponderosa
301
Solidago
300
Grindelia
174
Clematis ligusticifolia
139
Cardaria
114
Rhus trilobata
110
Erigeron
102
Cleome
101
Heterotheca villosa
98
Eriogonum effusum
93
Prunus virginiana
91
Astragalus
89
Most Frequent Interactions between Primary and Associate Taxa
(up to 20 most frequent)
sourceTaxonName
interactionTypeName
targetTaxonName
count
Andrena
interactsWith
Salix
211
Paratiphia
interactsWith
Tamarix
123
Bombus centralis
interactsWith
Penstemon degeneri
119
Lasioglossum
interactsWith
Salix
115
Bombus huntii
interactsWith
Chrysothamnus
84
Eurygaster
interactsWith
Poa
74
Bombus huntii
interactsWith
Penstemon degeneri
64
Dendroctonus ponderosae
interactsWith
Pinus ponderosa
57
Dendroctonus pseudotsugae
interactsWith
Pseudotsuga menziesii
57
Blepharida rhois
interactsWith
Rhus trilobata
55
Kleidocerys
interactsWith
Betula papyrifera
50
Smicronyx sordidus
interactsWith
Helianthus
50
Ips plastographus maritimus
interactsWith
Pinus radiata
50
Bembix pallidipicta
interactsWith
Asclepias
48
Deraeocoris
interactsWith
Pinus ponderosa
47
Gymnetron tetrum
interactsWith
Verbascum
44
Bombus appositus
interactsWith
Delphinium barbeyi
43
Dendroctonus ponderosae
interactsWith
Pinus contorta
40
Andrena
interactsWith
Prunus virginiana
39
Interaction Networks
The figures below provide a graph view on the dataset under review.
The first shows a summary network on the kingdom level, and the second
shows how interactions on the family level. It is important to note that
both network graphs were first aligned taxonomically using the Catalogue
of Life. Please refer to the original (or verbatim) taxonomic names for
a more original view on the interaction data.
Another way to discover the dataset under review is by searching for
it on the GloBI
website.
Taxonomic Alignment
As part of the review, all names are aligned against various name
catalogs (e.g., col, ncbi, discoverlife, gbif, itis, wfo, mdd, tpt,
pbdb, and worms). These alignments can help review name usage or aid in
selecting of a suitable taxonomic name resource.
Sample of Name Alignments
providedName
relationName
resolvedCatalogName
resolvedName
Agulla adnixa
HAS_ACCEPTED_NAME
col
Agulla adnixa
Agulla adnixa
SYNONYM_OF
col
Agulla adnixa
Agulla astuta
SYNONYM_OF
col
Agulla astuta
Agulla astuta
HAS_ACCEPTED_NAME
col
Agulla astuta
Distribution of Taxonomic Ranks of Aligned Names by Catalog.
Names that were not aligned with a catalog are counted as NAs. So, the
total number of unaligned names for a catalog will be listed in their NA
row.
resolvedCatalogName
resolvedRank
count
col
NA
177
col
family
13
col
genus
294
col
species
801
col
subfamily
2
col
subgenus
7
col
subspecies
60
col
variety
8
discoverlife
NA
1164
discoverlife
species
176
gbif
NA
88
gbif
family
14
gbif
genus
306
gbif
species
866
gbif
subspecies
74
gbif
variety
13
itis
NA
232
itis
family
13
itis
genus
290
itis
species
764
itis
subfamily
2
itis
subspecies
27
itis
variety
12
mdd
NA
1340
ncbi
NA
371
ncbi
family
13
ncbi
genus
295
ncbi
species
643
ncbi
subfamily
2
ncbi
subgenus
12
ncbi
subspecies
13
ncbi
tribe
1
ncbi
varietas
1
pbdb
NA
1152
pbdb
family
14
pbdb
genus
149
pbdb
species
23
pbdb
subfamily
1
pbdb
tribe
1
tpt
NA
1338
tpt
genus
2
wfo
NA
924
wfo
family
13
wfo
genus
157
wfo
species
235
wfo
subspecies
7
wfo
tribe
1
wfo
variety
8
worms
NA
1114
worms
family
13
worms
genus
132
worms
species
75
worms
subspecies
2
worms
tribe
1
worms
variety
4
Name relationship types per catalog. Name relationship type
“NONE” means that a name was not recognized by the associated catalog.
“SAME_AS” indicates either a “HAS_ACCEPTED_NAME” or “SYNONYM_OF” name
relationship type. We recognize that “SYNONYM_OF” encompasses many types
of nomenclatural synonymies (ICZN 1999) (e.g., junior synonym, senior
synonyms).
Elton, Nomer, and other tools may have difficulties interpreting
existing species interaction datasets. Or, they may misbehave, or
otherwise show unexpected behavior. As part of the review process,
detailed review notes are kept that document possibly misbehaving, or
confused, review bots. An sample of review notes associated with this
review can be found below.
In addtion, you can find the most frequently occurring notes in the
table below.
: Most frequently occurring review notes, if any.
For addition information on review notes, please have a look at the
first 500 Review Notes or the download full csv or tsv archives.
GloBI Review Badge
As part of the review, a review badge is generated. This review badge
can be included in webpages to indicate the review status of the dataset
under review.
Note that if the badge is green, no review notes were generated. If
the badge is yellow, the review bots may need some help with
interpreting the species interaction data.
GloBI Index Badge
If the dataset under review has been registered with
GloBI, and has been succesfully indexed by GloBI, the GloBI Index
Status Badge will turn green. This means that the dataset under review
was indexed by GloBI and is available through GloBI services and derived
data products.
If you’d like to keep track of reviews or index status of the dataset
under review, please visit [GloBI’s dataset index ^[At time of writing
(2024-12-23) the version of the GloBI dataset index was available at https://globalbioticinteractions.org/datasets
for badge examples.
Discussion
This review aims to provide a perspective on the dataset to aid in
understanding of species interaction claims discovered. However, it is
important to note that this review does not assess the quality
of the dataset. Instead, it serves as an indication of the open-ness5 and FAIRness (Wilkinson et
al. 2016; Trekels et al. 2023) of the dataset: to perform this
review, the data was likely openly available, Findable,
Accessible, Interoperable and
Reusable. The current Open-FAIR assessment is
qualitative, and a more quantitative approach can be implemented with
specified measurement units.
This report also showcases the reuse of machine-actionable
(meta)data, something highly recommended by the FAIR Data Principles
(Wilkinson et al.
2016). Making (meta)data machine-actionable enables more precise
procesing by computers, enabling even naive review bots like Nomer and
Elton to interpret the data effectively. This capability is crucial for
not just automating the generation of reports, but also for facilitating
seamless data exchanges, promoting interoperability.
Acknowledgements
We thank the many humans that created us and those who created and
maintained the data, software and other intellectual resources that were
used for producing this review. In addition, we are grateful for the
natural resources providing the basis for these human and bot
activities.
Author contributions
Nomer was responsible for name alignments. Elton carried out dataset
extraction, and generated the review notes.
Poelen, Jorrit H., James D. Simons, and Chris J. Mungall. 2014.
“Global Biotic Interactions: An Open Infrastructure to Share and
Analyze Species-Interaction Datasets.”Ecological
Informatics 24 (November): 148–59. https://doi.org/10.1016/j.ecoinf.2014.08.005.
Trekels, Maarten, Debora Pignatari Drucker, José Augusto Salim, Jeff
Ollerton, Jorrit Poelen, Filipi Miranda Soares, Max Rünzel, Muo Kasina,
Quentin Groom, and Mariano Devoto. 2023. “WorldFAIR Project (D10.1) Agriculture-related pollinator
data standards use cases report.” Zenodo. https://doi.org/10.5281/zenodo.8176978.
Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg,
Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, et al.
2016. “The FAIR Guiding Principles for Scientific
Data Management and Stewardship.”Scientific Data 3 (1).
https://doi.org/10.1038/sdata.2016.18.