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/msb-para, has fingerprint
hash://md5/28d95d142b371b660afba7b3384d051e, is 4.66GiB in size and
contains 57,433 interaction with 4 unique types of associations (e.g.,
parasiteOf) between 970 primary taxa (e.g., Acari) and 6,749 associated
taxon (e.g., Alopex lagopus). 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:
For additional metadata related to this dataset, please visit https://github.com/globalbioticinteractions/msb-para
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 (Elliott
et al. 2025), Elton (Kuhn, Poelen, and Leinweber 2025), Nomer
(Salim and Poelen 2025)
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. 4.66GiB) under review
elton pull globalbioticinteractions/msb-para
# generate review notes
elton review globalbioticinteractions/msb-para\
> review.tsv
# export indexed interaction records
elton interactions globalbioticinteractions/msb-para\
> interactions.tsv
# export names and align them with the Catalogue of Life using Nomer
elton names globalbioticinteractions/msb-para\
| nomer append col\
> name-alignment.tsv
or visually, in a process diagram.
Review Process Overview
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
Biotic Interaction Data
Model
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/msb-para,
has fingerprint hash://md5/28d95d142b371b660afba7b3384d051e, is 4.66GiB
in size and contains 57,433 interaction with 4 unique types of
associations (e.g., parasiteOf) between 970 primary taxa (e.g., Acari)
and 6,749 associated taxon (e.g., Alopex lagopus).
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.
Sample of Indexed Interaction Claims
sourceTaxonName
interactionTypeName
targetTaxonName
referenceCitation
Acari
parasiteOf
Peromyscus maniculatus
http://arctos.database.museum/guid/MSB:Para:39320
Siphonaptera
parasiteOf
Cynomys gunnisoni
http://arctos.database.museum/guid/MSB:Para:39328
Siphonaptera
parasiteOf
Tamias quadrivittatus
http://arctos.database.museum/guid/MSB:Para:39331
Siphonaptera
parasiteOf
Neotoma mexicana
http://arctos.database.museum/guid/MSB:Para:39354
Most Frequently Mentioned Interaction Types (up to 20 most
frequent)
interactionTypeName
count
parasiteOf
53419
coOccursWith
3939
interactsWith
48
hasParasite
27
Most Frequently Mentioned Primary Taxa (up to 20 most
frequent)
sourceTaxonName
count
Acari
6971
Siphonaptera
5926
Cestoda
2814
Nematoda
1869
Taenia
1869
Toxascaris
1750
Phthiraptera
1735
Ixodida
1680
Echinococcus multilocularis
1532
Polyplax borealis
1485
Echinococcus
857
Arthropoda
844
Mastophorus dipodomis
787
Heteromyoxyuris deserti
726
Hoplopleura acanthopus
704
Uncinaria
685
Hoplopleura arboricola
665
Hoplopleura
657
Trematoda
566
Most Frequently Mentioned Associate Taxa (up to 20 most
frequent)
targetTaxonName
count
Alopex lagopus
4328
Myodes rutilus
3135
Dipodomys merriami
2631
Peromyscus maniculatus
1994
Microtus oeconomus
1960
Aythya affinis
1200
Microtus pennsylvanicus
1045
Dipodomys ordii
1026
Sorex cinereus
968
Peromyscus truei
759
Vulpes lagopus
722
Canis lupus familiaris
638
Myodes gapperi
606
Neotoma albigula
603
Peromyscus keeni
598
Dipodomys spectabilis
559
Microtus
556
Microtus longicaudus
509
Onychomys leucogaster
500
Most Frequent Interactions between Primary and Associate Taxa
(up to 20 most frequent)
sourceTaxonName
interactionTypeName
targetTaxonName
count
Taenia
parasiteOf
Alopex lagopus
1303
Toxascaris
parasiteOf
Alopex lagopus
1049
Siphonaptera
parasiteOf
Peromyscus maniculatus
852
Polyplax borealis
parasiteOf
Myodes rutilus
663
Echinococcus multilocularis
parasiteOf
Alopex lagopus
574
Acari
parasiteOf
Sorex cinereus
528
Echinococcus multilocularis
parasiteOf
Microtus oeconomus
514
Echinococcus
parasiteOf
Alopex lagopus
471
Mastophorus dipodomis
parasiteOf
Dipodomys merriami
440
Eimeria chobotari
parasiteOf
Dipodomys merriami
429
Uncinaria
parasiteOf
Alopex lagopus
415
Acari
parasiteOf
Myodes rutilus
350
Pterygodermatites dipodomis
parasiteOf
Dipodomys merriami
332
Acari
parasiteOf
Dipodomys merriami
281
Acari
parasiteOf
Peromyscus maniculatus
279
Heteromyoxyuris deserti
parasiteOf
Dipodomys ordii
274
Ascarididae
parasiteOf
Alopex lagopus
269
Echinococcus
parasiteOf
Microtus oeconomus
267
Acari
parasiteOf
Peromyscus keeni
265
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.
Interactions on taxonomic kingdom rank as
interpreted by the Catalogue of Life download
svgInteractions on the taxonomic family rank
as interpreted by the Catalogue of Life. download
svg
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
A25KN
NONE
col
A25KN
A25KT
NONE
col
A25KT
A25KU
NONE
col
A25KU
A25KW
NONE
col
A25KW
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
1129
col
class
6
col
family
67
col
genus
282
col
infraorder
1
col
nanorder
2
col
order
18
col
parvorder
1
col
phylum
5
col
species
1124
col
subclass
1
col
subfamily
2
col
subgenus
15
col
suborder
1
col
subspecies
105
col
superfamily
9
col
unranked
1
discoverlife
NA
2749
discoverlife
species
1
gbif
NA
935
gbif
class
6
gbif
family
76
gbif
genus
344
gbif
order
14
gbif
phylum
5
gbif
species
1251
gbif
subspecies
124
itis
NA
1413
itis
class
6
itis
family
61
itis
genus
240
itis
order
23
itis
phylum
6
itis
species
899
itis
subclass
5
itis
subfamily
3
itis
subgenus
1
itis
suborder
3
itis
subspecies
92
itis
superfamily
3
mdd
NA
2749
ncbi
NA
1147
ncbi
class
5
ncbi
family
73
ncbi
genus
311
ncbi
infraorder
2
ncbi
order
18
ncbi
phylum
6
ncbi
species
1128
ncbi
subclass
5
ncbi
subfamily
2
ncbi
subgenus
2
ncbi
suborder
4
ncbi
subspecies
42
ncbi
superfamily
9
pbdb
NA
2042
pbdb
class
6
pbdb
family
24
pbdb
genus
104
pbdb
order
13
pbdb
phylum
5
pbdb
species
542
pbdb
subclass
1
pbdb
subfamily
1
pbdb
suborder
5
pbdb
subspecies
6
pbdb
subtribe
1
pbdb
superfamily
3
pbdb
superorder
1
pbdb
unranked clade
4
tpt
NA
1945
tpt
family
6
tpt
genus
70
tpt
order
1
tpt
species
727
wfo
NA
2739
wfo
genus
10
worms
NA
1693
worms
class
5
worms
family
65
worms
genus
261
worms
infraorder
1
worms
order
19
worms
phylum
5
worms
species
676
worms
subclass
4
worms
subfamily
1
worms
subgenus
1
worms
suborder
3
worms
subphylum
1
worms
subspecies
6
worms
superfamily
10
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.
First few lines in the review notes.
reviewDate
reviewCommentType
reviewComment
2025-03-30T11:15:36Z
note
found unresolved reference [060980]
2025-03-30T11:15:36Z
note
found unresolved reference [070456]
2025-03-30T11:15:36Z
note
found unresolved reference [077368]
2025-03-30T11:15:36Z
note
found unresolved reference [077679]
In addition, you can find the most frequently occurring notes in the
table below.
Most frequently occurring review notes, if any.
reviewComment
count
found unresolved reference [060980]
1
found unresolved reference [070456]
1
found unresolved reference [077368]
1
found unresolved reference [077679]
1
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
(2025-03-30) 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. Also, thanks to https://github.com/zygoballus for helping
improve the layout of the review tables.
Author contributions
Nomer was responsible for name alignments. Elton carried out dataset
extraction, and generated the review notes. Preston tracked, versioned,
and packaged, the dataset under review.
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.