Bibliography Report

Author

Affiliation

Rainer M. Krug

University of Zürich

Abstract

Reports analysing the IPBES Libraries on Zotero.

• PAND Bibliography
• This Report
• Github repository

Introduction

This report assesses the PAND Bibliography in regards to different measures and shows some information of the content. It does not assess the content of the sources but rather the bibliometric data.

Bibliographic analysis

In most cases, the bibliographic analysis is done on the OpenAlex library. In some cases, we can also do it using the Zenodo data. This is mentioned in the beginning of each subsection

Publication types

Analysis: Zenodo and OpenAlex

OpenAlex and Zotero use different tyoes. These are not directly compable, which is whu=y both are shown.

bib_data$figure_types_data |>
  dplyr::arrange(
    from,
    desc(count)
  ) |>
  knitr::kable(
    caption = "Types of documents from the Zotero bibliography as well as from OpenApex."
  )

Types of documents from the Zotero bibliography as well as from OpenApex.

type	count	from
article	337	OpenAlex
review	100	OpenAlex
letter	17	OpenAlex
preprint	6	OpenAlex
editorial	4	OpenAlex
book-chapter	2	OpenAlex
erratum	1	OpenAlex
journalArticle	604	Zotero
report	30	Zotero
book	22	Zotero
webpage	19	Zotero
bookSection	14	Zotero
conferencePaper	3	Zotero
bill	1	Zotero
blogPost	1	Zotero
document	1	Zotero
newspaperArticle	1	Zotero

bib_data$figure_types

Zenodo versus OpenAlex Types

Analysis: Zenodo and OpenAlex

The types entered in the Zenodo library and the types as retrieved from OpenAlex are not linked, therefore they can differ. This can indicate faulty data entering in Zenodo but not necessarily has to. These cases need to be carefully evaluated and here only given as a starting point.

NA in OpenAlex is likely caused by the doi not found in OpenAlex (not in there, not valid, non-standard DOI in Zenodo). NA in Zotero is linked to non-standard DOI entries (i.e. with http) which can therefore not be linked to OpenAlex data. If all DOIs are in standard format, there should be no NAs in this Table in the column Ferom Zenodo.

TODO: Improvements should be done after feedback.

bib_data$metrics$types$comparison |>
  knitr::kable(
    col.names = c("Type from Zenodo", "Type from [OpenAlex](https://OpenAlex.org){target='_blank'}", "count"),
    caption = "Table giving the combination of types from Zenodo as well as [OpenAlex](https://OpenAlex.org){target='_blank'} and their frequency"
  )

Table giving the combination of types from Zenodo as well as OpenAlex and their frequency

Type from Zenodo	Type from OpenAlex	count
journalArticle	article	302
journalArticle	NA	189
journalArticle	review	88
NA	article	37
report	NA	30
book	NA	22
webpage	NA	19
journalArticle	letter	16
bookSection	NA	14
NA	review	12
journalArticle	preprint	6
journalArticle	editorial	4
conferencePaper	NA	3
journalArticle	book-chapter	1
blogPost	NA	1
bill	NA	1
document	NA	1
newspaperArticle	NA	1
NA	letter	1
NA	book-chapter	1
NA	erratum	1

Year of Publication

Analysis: Zenodo and OpenAlex

The following ranges of publication years can be found in the data.

bib_data$figure_pub_year_data |>
  dplyr::summarize(
    min = min(publication_year, na.rm = TRUE),
    max = max(publication_year, na.rm = TRUE),
    .by = c(from)
  ) |>
  knitr::kable()

from	min	max
Zenodo	1976	2021
OpenAlex	1976	2020

bib_data$figure_pub_year

Warning: Removed 1 row containing missing values or values outside the scale range
(`geom_col()`).

Access Status of References

Analysis: OpenAlex

bib_data$figure_oa_status

50 Most often cited Journals

Analysis: Zenodo

TODO: OpenAlex should be added

bib_data$figure_top_journals

This table contains all Journals as specified in the Zotero database.

bib_data$figure_top_journals_data |>
  IPBES.R::table_dt("cited_journals")

Coutries of Institutes of all authors

Analysis: OpenAlex

In this section we will take a closer look at the countries from which ih the authors ot the publication come. THe data includes all authoirs without weighting.

#|
#| fig-height: 10
#| fig-width: 10

bib_data$figure_top_country_map

This plot only contains the countries with more than 10 references.

#|
#| fig-height: 10
#| fig-width: 10

bib_data$figure_top_country

This table contains all countries and the number of authorship.

bib_data$figure_top_country_data |>
  IPBES.R::table_dt("top_countries")

Cleanliness of the Bibliography

Cleanliness of a bibliography is defined here as the quality of the bibliografic data in the bibliography. It does not concern any topical measures, only measures related to the bibliografic data in the bibliography.

The analysis is at the moment only done for DOIs as corresponding measures are not available at the moment for ISBNs and ISSNs and duplicate ISBNs and ISSNs can be rcorrect as different chapters of a book might be in the bibliography.

Entries with DOIs, ISBNs or ISSNs in Zotero

To identify a reference, the most widely used identifier is the DOI. The following table shows the number of references with a DOI and the number of unique DOIs.

To consider duplicate ISBNs or ISSNs as duplicates entries in the library is not waranted as e.g. differenc chapters of a book can be separate entries in the library and therefore lead to duplicates.

• DOIs: 500 (71.84%) - 2 duplicates
• ISBNss: 28 (4.02%)
• ISBNss: 448 (64.37%)

DOIs in Zotero

The following sections provide some more detailed analysis of the bibliography in Zenodo. The tables all contain clickable links which, shwen clicked, show the respective article in the Zotero bibliograpohy.

Duplicates

The following DOIs are duplicates in the bibliography. This table should be empty.

if (length(bib_data$metrics$zotero_dois$duplicate) > 0) {
  data.frame(
    doi = bib_data$metrics$zotero_dois$duplicate,
    link = paste0(bib_data$bibliography$url, "/items/", names(bib_data$metrics$zotero_dois$duplicate))
  ) |>
    dplyr::mutate(
      sort = doi,
      doi = paste0('<a href="', link, '" target="_blank">', doi, "</a>"),
    ) |>
    dplyr::arrange(
      sort
    ) |>
    dplyr::mutate(
      sort = NULL
    ) |>
    knitr::kable(
      caption = "DOIs in Zenodo which are duplicated",
      escape = FALSE
    )
}

DOIs in Zenodo which are duplicated

	doi	link
UQXN7TPN	10.1038/39057	https://www.zotero.org/groups/2499181/items/UQXN7TPN
I35JTJVU	10.1038/39057	https://www.zotero.org/groups/2499181/items/I35JTJVU

Non Standard

All DOIs should be given as only the DOI without the resolver, i.e. not starting with http. The following table shows all entries which do have a non-conform DOI:

#|

http <- grep("http", bib_data$metrics$zotero_dois$id_raw)
data.frame(
  doi = bib_data$metrics$zotero_dois$id_raw[http],
  link = paste0(bib_data$bibliography$url, "/items/", names(bib_data$metrics$zotero_dois$id_raw)[http])
) |>
  dplyr::mutate(
    doi = paste0('<a href="', link, '" target="_blank">', doi, "</a>"),
    link = NULL
  ) |>
  knitr::kable(
    caption = "DOIs in Zenodo which include a `http`",
    escape = FALSE
  )

DOIs in Zenodo which include a http

	doi
CQUFDDMI	https://doi.org/10.1016/j.biocon.2011.10.002
5WGNCD4N	https://doi.org/10.1016/j.marpol.2017.06.036
W7C34G7L	https://doi.org/10.1016/j.gecco.2016.03.007
AA4H2YRW	https://doi.org/10.1016/j.marpol.2015.04.006
WCE5B8XK	https://doi.org/10.1016/j.biocon.2014.12.019
W332D6Q2	https://doi.org/10.1016/j.biocon.2012.02.009
J5VSEZQD	https://doi.org/10.1016/j.tree.2020.02.005
7NY9SWAQ	https://doi.org/10.1016/j.marpol.2017.10.031
VPKTCZE9	https://doi.org/10.1016/j.scitotenv.2020.142919
Z2GCC8IX	https://doi.org/10.1016/j.biocon.2020.108503
KY7APTMV	https://doi.org/10.1016/j.pecon.2019.03.001
B8GMZTFW	https://doi.org/10.1016/j.biocon.2010.07.030
PJBMNET5	https://doi.org/10.1016/j.ecolecon.2009.11.010
IFMFNTFN	https://doi.org/10.1016/j.gecco.2014.11.010
WVNQ9T8D	https://doi.org/10.1016/j.biocon.2020.108596
7ZNJLF5N	https://doi.org/10.1016/j.ecolecon.2006.07.007
BE2TDGP4	http://dx.doi.org/10.1016/j.jebo.2016.06.007
3VH5RBL4	https://doi.org/10.1016/j.gecco.2018.e00486
IT4N6IJV	https://doi.org/10.1016/j.ecolind.2017.07.002
K94YUNIN	https://doi.org/10.1016/j.biocon.2017.11.007
VY88LCVW	http://dx.doi.org/10.1016/j.onehlt.2015.11.002
VG4FX9UM	https://doi.org/10.1016/j.cosust.2017.08.005
IU6LC9FQ	https://doi.org/10.1016/S0140-6736(20)30183-5
UARICS8K	https://doi.org/10.4269/ajtmh.2011.10-0041

Not Valid

Here we do acheck for the structural validity of the dois. This check needs to be improved. Of these 85 are not valid. These are:

#|

if (length(bib_data$metrics$zotero_dois$not_valid) > 0) {
  data.frame(
    doi = bib_data$metrics$zotero_dois$not_valid,
    link = paste0(bib_data$bibliography$url, "/items/", names(bib_data$metrics$zotero_dois$not_valid))
  ) |>
    dplyr::mutate(
      doi = paste0('<a href="', link, '" target="_blank">', doi, "</a>"),
      link = NULL
    ) |>
    knitr::kable(
      caption = "DOIs in Zenodo which ar not valid",
      escape = FALSE
    )
} else {
  print("All DOIs in Zenodo are valid.")
}

DOIs in Zenodo which ar not valid

	doi
WF2G7HFS	10.1579/0044-7447(2007)36[545:CBBCAH]2.0.CO;2
DAVYFADP	10.1098/rstb.2016.0131
CCEKBKIN	10.1645/0022-3395(2000)086[1135:Eocrih]2.0.Co;2

Not in OpenAlex

To validate the existence and validity of the DOIs, we check if the DOIs are in the OpenAlex database.

Of the 500 unique DOIs in the library, 85 (17%) are in not in OpenAlex. This includes the non-valid DOIS, which are filtered out in the table below.

data.frame(
  doi = bib_data$metrics$zotero_dois$not_in_oa,
  link = paste0(bib_data$bibliography$url, "/items/", names(bib_data$metrics$zotero_dois$not_in_oa))
) |>
  dplyr::mutate(
    doi = paste0('<a href="', link, '" target="_blank">', doi, "</a>"),
    link = NULL
  ) |>
  knitr::kable(
    caption = "DOIs in Zenodo which ar not in [OpenAlex](https://OpenAlex.org){target='_blank'}",
    escape = FALSE
  )

DOIs in Zenodo which ar not in OpenAlex

	doi
YNMPABCX	10.1172/JCI34706
4EUCGTGE	10.1111/j.1755-263X.2010.00121.x
5HWG4BQA	10.1016/S0140-6736(03)14630-2
BTGTHEMD	10.1016/S2542-5196(19)30070-1
YERNE287	10.1016/S0140-6736(20)30185-9
6P69GS3Z	10.1017/S0031182000086121
WF2G7HFS	10.1579/0044-7447(2007)36[545:CBBCAH]2.0.CO;2
AST97QBL	10.1644/07-MAMM-A-015R1.1
YLVPPAWC	10.1128/CMR.00002-11
JHETNMAW	10.1016/S0169-5347(99)01665-1
NZYILREX	10.1016/S0140-6736(07)61256-2
UFREHS9E	10.1017/S0030605317001247
2XRQ9GRV	10.1016/S1473-3099(15)00502-2
N9N83L8B	10.2105/AJPH.2014.302236r
MTRQFYHI	10.1017/S0031182012000200
7EQRR22Y	10.1016/S1473-3099(13)70164-6
G2G9N85D	10.1016/S0140-6736(85)92556-5
XPZXN3Z9	10.2807/1560-7917.ES.2020.25.23.2001005
LQJLBCQD	10.1016/S0140-6736(20)31027-8
4SHKT7H3	10.1016/S0065-308X(05)62006-4
B6VVTJNL	10.1023/A:1009930313242
XDKA4UFJ	10.1016/S0169-5347(03)00123-X
ZF8V6TPP	10.1016/B978-1-4557-4801-3.00322-2
7ABJ9DAJ	10.1016/S2542-5196(17)30010-4
NCNEV5AJ	10.1016/S0140-6736(12)61684-5
UZ8AKLUI	10.1017/S0030605314000234
Q7X2W2C8	10.1017/S0950268820002046
65GJSFXU	10.1186/1476-072X-12-49
CURZ3PFV	10.1111/j.1365-294X.2012.05710.x
JXJHPRD5	10.1637/7554-033106R.1
B9V8HX88	10.5751/ES-00605-090105
QXH5DEYM	10.1056/NEJMp2002106
6SBZVHPL	10.1016/S0140-6736(13)61904-2
7I9NQTB7	10.1016/S0140-6736(12)61678-X
S6QB98QK	10.1056/NEJMoa2001316
S76ABASK	10.1016/S2542-5196(19)30045-2
2NXANHJG	10.1016/S2542-5196(20)30123-6
IWPJBS3K	10.1056/NEJMoa030747
FVRERCHE	10.1017/S0031182018001397
XRLM2RKW	10.1016/S0140-6736(20)31242-3
J6ATTHW5	10.1637/7564-033106R.1
HUQ5STFJ	10.1128/JVI.01498-14
VEPPUJK9	10.1017/S0030605306000056
J9UT783A	10.1016/S0140-6736(99)05128-4
SX9EAGPW	10.1071/WR9880651
Y7287I99	10.1016/S0140-6736(99)04299-3
4GDHH7LN	10.1016/S2542-5196(20)30178-9
TRX5YTM5	10.1056/NEJMoa1401505
WISHL5GH	10.1016/S0140-6736(03)15313-5
C4Q3HC4P	10.1128/JVI.01600-13
N3MMCF6Q	10.1637/8970-062609-Reg.1
T9NAQLV9	10.1128/mBio.01146-1429
CQUFDDMI	10.1016/j.biocon.2011.10.002
5WGNCD4N	10.1016/j.marpol.2017.06.036
W7C34G7L	10.1016/j.gecco.2016.03.007
AA4H2YRW	10.1016/j.marpol.2015.04.006
WCE5B8XK	10.1016/j.biocon.2014.12.019
W332D6Q2	10.1016/j.biocon.2012.02.009
J5VSEZQD	10.1016/j.tree.2020.02.005
7NY9SWAQ	10.1016/j.marpol.2017.10.031
VPKTCZE9	10.1016/j.scitotenv.2020.142919
Z2GCC8IX	10.1016/j.biocon.2020.108503
KY7APTMV	10.1016/j.pecon.2019.03.001
B8GMZTFW	10.1016/j.biocon.2010.07.030
PJBMNET5	10.1016/j.ecolecon.2009.11.010
IFMFNTFN	10.1016/j.gecco.2014.11.010
WVNQ9T8D	10.1016/j.biocon.2020.108596
7ZNJLF5N	10.1016/j.ecolecon.2006.07.007
BE2TDGP4	10.1016/j.jebo.2016.06.007
3VH5RBL4	10.1016/j.gecco.2018.e00486
IT4N6IJV	10.1016/j.ecolind.2017.07.002
K94YUNIN	10.1016/j.biocon.2017.11.007
HQ76S4IR	10.1098/rstb.2016.0123
M4ZM43RA	10.1128/mBio.00812-20
4TAN4QII	10.1098/rsos.181577
VY88LCVW	10.1016/j.onehlt.2015.11.002
VG4FX9UM	10.1016/j.cosust.2017.08.005
YFV5DLMK	10.17605/OSF.IO/5JX3G
ZKA5Z2JF	10.1017/S0031182014001796
PJ8GBW6S	10.1111/cobi.12785
IU6LC9FQ	10.1016/S0140-6736(20)30183-5
DAVYFADP	10.1098/rstb.2016.0131
S89M9Z5P	10.1098/rstb.2016.0173
UARICS8K	10.4269/ajtmh.2011.10-0041
CCEKBKIN	10.1645/0022-3395(2000)086[1135:Eocrih]2.0.Co;2

TODO Do Exist

TODO Finally we check, if these dois exist but are not ingested into OpenAlex. This is done using the doi.org resolver This is disabled at the moment and still needs to be implemented.