A Brief Introduction to openalexR
Source:vignettes/articles/A_Brief_Introduction_to_openalexR.Rmd
A_Brief_Introduction_to_openalexR.Rmd
https://github.com/ropensci/openalexR
Latest version: 2.0.0.9000, 2025-04-29
by Massimo Aria
Full Professor in Social Statistics
PhD in Computational Statistics
Laboratory and Research Group STAD Statistics, Technology, Data Analysis
Department of Economics and Statistics
University of Naples Federico II
email aria@unina.it
An R-package to gather bibliographic data from OpenAlex
openalexR helps you interface with the OpenAlex API to retrieve bibliographic infomation about publications, authors, institutions, sources, funders, publishers, topics and concepts with 5 main functions:
oa_query(): generates a valid query, written following the OpenAlex API syntax, from a set of arguments provided by the user.oa_request(): downloads a collection of entities matching the query created byoa_query()or manually written by the user, and returns a JSON object in a list format.oa2df(): converts the JSON object in classical bibliographic tibble/data frame.oa_fetch(): composes three functions above so the user can execute everything in one step, i.e.,oa_query |> oa_request |> oa2dfoa_random(): to get random entity, e.g.,oa_random("works")gives a different work each time you run it
Works (think papers, publications)
This paper:
Aria, M., & Cuccurullo, C. (2017). bibliometrix:
An R-tool for comprehensive science mapping analysis.
Journal of informetrics, 11(4), 959-975.is associated to the OpenAlex-id
W2755950973. If you know your paper’s OpenAlex ID, all
you need to do is passing identifier = <openalex id>
as an argument in oa_fetch():
paper_id <- oa_fetch(
identifier = "W2755950973",
entity = "works",
verbose = TRUE
)## Requesting url: https://api.openalex.org/works/W2755950973
dplyr::glimpse(paper_id)## Rows: 1
## Columns: 39
## $ id <chr> "https://openalex.org/W2755950973"
## $ title <chr> "bibliometrix : An R-tool for comprehensiv…
## $ display_name <chr> "bibliometrix : An R-tool for comprehensiv…
## $ authorships <list> [<tbl_df[2 x 7]>]
## $ doi <chr> "https://doi.org/10.1016/j.joi.2017.08.007"
## $ publication_date <date> 2017-09-12
## $ publication_year <int> 2017
## $ fwci <dbl> 105.621
## $ cited_by_count <int> 9185
## $ counts_by_year <list> [<data.frame[11 x 2]>]
## $ cited_by_api_url <chr> "https://api.openalex.org/works?filter=cit…
## $ ids <list> <"https://openalex.org/W2755950973", "htt…
## $ type <chr> "article"
## $ is_oa <lgl> FALSE
## $ is_oa_anywhere <lgl> FALSE
## $ oa_status <chr> "closed"
## $ oa_url <lgl> NA
## $ any_repository_has_fulltext <lgl> FALSE
## $ source_display_name <chr> "Journal of Informetrics"
## $ source_id <chr> "https://openalex.org/S205292342"
## $ issn_l <chr> "1751-1577"
## $ host_organization <chr> "https://openalex.org/P4310320990"
## $ host_organization_name <chr> "Elsevier BV"
## $ landing_page_url <chr> "https://doi.org/10.1016/j.joi.2017.08.007"
## $ referenced_works <list> <"https://openalex.org/W1497199863", "http…
## $ referenced_works_count <int> 70
## $ related_works <list> <"https://openalex.org/W45233828", "https…
## $ concepts <list> [<data.frame[10 x 5]>]
## $ topics <list> [<tbl_df[12 x 5]>]
## $ keywords <list> [<data.frame[1 x 3]>]
## $ is_paratext <lgl> FALSE
## $ is_retracted <lgl> FALSE
## $ language <chr> "en"
## $ grants <lgl> NA
## $ apc <list> [<data.frame[2 x 5]>]
## $ first_page <chr> "959"
## $ last_page <chr> "975"
## $ volume <chr> "11"
## $ issue <chr> "4"oa_fetch() is a composition of functions:
oa_query |> oa_request |> oa2df. As results,
oa_query() returns the query string including the OpenAlex
endpoint API server address (default). oa_request()
downloads the bibliographic records matching the query. Finally,
oa2df() converts the final result list to a tibble. The
final result is a complicated tibble, but we can use
show_works() to display a simplified version:
paper_id %>%
show_works() %>%
knitr::kable()| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W2755950973 | bibliometrix : An R-tool for comprehensive science mapping analysis | Massimo Aria | Corrado Cuccurullo | FALSE | Workflow, Bibliometrics, Software |
External id formats
OpenAlex endpoint accepts OpenAlex IDs and other external IDs (e.g., DOI, ISSN) in several formats, including Digital Object Identifier (DOI) and Persistent Identifiers (PIDs).
oa_fetch(
# identifier = "https://doi.org/10.1016/j.joi.2017.08.007", # would also work (PIDs)
identifier = "doi:10.1016/j.joi.2017.08.007",
entity = "works"
) %>%
show_works() %>%
knitr::kable()| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W2755950973 | bibliometrix : An R-tool for comprehensive science mapping analysis | Massimo Aria | Corrado Cuccurullo | FALSE | Workflow, Bibliometrics, Software |
More than one publications/authors
https://api.openalex.org/authors/https://orcid.org/
If you know the OpenAlex IDs of these entities, you can also feed
them into the identifier argument.
oa_fetch(
identifier = c("W2741809807", "W2755950973"),
# identifier = c("https://doi.org/10.1016/j.joi.2017.08.007", "https://doi.org/10.1016/j.joi.2017.08.007"), # TODO
entity = "works",
verbose = TRUE
) %>%
show_works() %>%
knitr::kable()## Requesting url: https://api.openalex.org/works?filter=openalex%3AW2741809807%7CW2755950973## Getting 1 page of results with a total of 2 records...| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W2755950973 | bibliometrix : An R-tool for comprehensive science mapping analysis | Massimo Aria | Corrado Cuccurullo | FALSE | Workflow, Bibliometrics, Software |
| W2741809807 | The state of OA: a large-scale analysis of the prevalence and impact of Open Access articles | Heather Piwowar | Stefanie Haustein | TRUE | Citation, License, Bibliometrics |
However, if you only know their external identifies, say, DOIs, you
would need to use doi as a filter (either the canonical
form with https://doi.org/ or
without should work):
oa_fetch(
# identifier = c("W2741809807", "W2755950973"),
doi = c("10.1016/j.joi.2017.08.007", "https://doi.org/10.1093/bioinformatics/btab727"),
entity = "works",
verbose = TRUE
) %>%
show_works() %>%
knitr::kable()## Requesting url: https://api.openalex.org/works?filter=doi%3A10.1016%2Fj.joi.2017.08.007%7Chttps%3A%2F%2Fdoi.org%2F10.1093%2Fbioinformatics%2Fbtab727## Getting 1 page of results with a total of 2 records...| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W2755950973 | bibliometrix : An R-tool for comprehensive science mapping analysis | Massimo Aria | Corrado Cuccurullo | FALSE | Workflow, Bibliometrics, Software |
| W3206431085 | PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods | Joseph D. Romano | Jason H. Moore | TRUE | Python (programming language), Benchmarking, Benchmark (surveying) |
Filters
In most cases, we are interested in downloading a collection of items that meet one or more inclusion/exclusion criteria (filters). Supported filters for each entity are listed here.
Example: We want to download all works published by a set of authors. We can do this by filtering on the authorships.author.id/author.id or authorships.author.orcid/author.orcid attribute (see more on works attributes):
oa_fetch(
entity = "works",
author.id = c("A5048491430", "A5023888391"),
verbose = TRUE
) %>%
show_works() %>%
knitr::kable()## Requesting url: https://api.openalex.org/works?filter=author.id%3AA5048491430%7CA5023888391## Getting 1 page of results with a total of 125 records...## Warning in oa_request(oa_query(filter = filter_i, multiple_id = multiple_id, :
## The following work(s) have truncated lists of authors: W4230863633.
## Query each work separately by its identifier to get full list of authors.
## For example:
## lapply(c("W4230863633"), \(x) oa_fetch(identifier = x))
## Details at https://docs.openalex.org/api-entities/authors/limitations.| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W2741809807 | The state of OA: a large-scale analysis of the prevalence and impact of Open Access articles | Heather Piwowar | Stefanie Haustein | TRUE | Citation, License, Bibliometrics |
| W2046766973 | Sharing Detailed Research Data Is Associated with Increased Citation Rate | Heather Piwowar | Douglas B. Fridsma | TRUE | Citation, Clinical trial, Impact factor |
| W2045657963 | Data reuse and the open data citation advantage | Heather Piwowar | Todd Vision | TRUE | Citation, Reuse |
| W1572136682 | Altmetrics: Value all research products | Heather Piwowar | NA | TRUE | Altmetrics, Value (mathematics) |
| W2122130843 | Scientometrics 2.0: New metrics of scholarly impact on the social Web | Jason Priem | Bradely H. Hemminger | FALSE | Bookmarking, Altmetrics, Social media |
| W1553564559 | Altmetrics in the wild: Using social media to explore scholarly impact | Jason Priem | Bradley M. Hemminger | TRUE | Altmetrics, Social media, Citation |
orcids <- c("0000-0003-3737-6565", "0000-0002-8517-9411")
canonical_orcids <- paste0("https://orcid.org/", orcids)
oa_fetch(
entity = "works",
author.orcid = canonical_orcids,
verbose = TRUE
) %>%
show_works() %>%
knitr::kable()## Requesting url: https://api.openalex.org/works?filter=author.orcid%3Ahttps%3A%2F%2Forcid.org%2F0000-0003-3737-6565%7Chttps%3A%2F%2Forcid.org%2F0000-0002-8517-9411## Getting 2 pages of results with a total of 348 records...## Warning in oa_request(oa_query(filter = filter_i, multiple_id = multiple_id, :
## The following work(s) have truncated lists of authors: W3202287394, W3207775241.
## Query each work separately by its identifier to get full list of authors.
## For example:
## lapply(c("W3202287394", "W3207775241"), \(x) oa_fetch(identifier = x))
## Details at https://docs.openalex.org/api-entities/authors/limitations.| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W2755950973 | bibliometrix : An R-tool for comprehensive science mapping analysis | Massimo Aria | Corrado Cuccurullo | FALSE | Workflow, Bibliometrics, Software |
| W2777772618 | Interoception and Mental Health: A Roadmap | Sahib S. Khalsa | Nancy Zucker | TRUE | Mental health, Perception |
| W2955219525 | Scaling tree-based automated machine learning to biomedical big data with a feature set selector | Trang T. Le | Jason H. Moore | TRUE | Pipeline (software), Scalability, Feature (linguistics) |
| W3005144120 | Mapping the Evolution of Social Research and Data Science on 30 Years of Social Indicators Research | Massimo Aria | Maria Spano | FALSE | Human geography, Data collection, Position (finance) |
| W2408216567 | Foundations and trends in performance management. A twenty-five years bibliometric analysis in business and public administration domains | Corrado Cuccurullo | Fabrizia Sarto | FALSE | Domain (mathematical analysis), Content analysis, Public domain |
| W2952824318 | A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE | Trang T. Le | Martin P. Paulus | TRUE | Nonlinear system |
Example: We want to download all works that have been cited more than 50 times, published between 2020 and 2021, and include the strings “bibliometric analysis” or “science mapping” in the title. Maybe we also want the results to be sorted by total citations in a descending order.
Setting the argument count_only = TRUE, the function
oa_request() returns the number of items matching the query
without downloading the collection.
oa_fetch(
entity = "works",
title.search = c("bibliometric analysis", "science mapping"),
cited_by_count = ">50",
from_publication_date = "2020-01-01",
to_publication_date = "2021-12-31",
options = list(sort = "cited_by_count:desc"),
count_only = TRUE,
verbose = TRUE
)## Requesting url: https://api.openalex.org/works?filter=title.search%3Abibliometric%20analysis%7Cscience%20mapping%2Ccited_by_count%3A%3E50%2Cfrom_publication_date%3A2020-01-01%2Cto_publication_date%3A2021-12-31&sort=cited_by_count%3Adesc## count db_response_time_ms page per_page
## [1,] 452 119 1 1We can now download the records and transform it into a tibble/data
frame by setting count_only = FALSE (also the default
value):
oa_fetch(
entity = "works",
title.search = c("bibliometric analysis", "science mapping"),
cited_by_count = ">50",
from_publication_date = "2020-01-01",
to_publication_date = "2021-12-31",
options = list(sort = "cited_by_count:desc"),
count_only = FALSE
) %>%
show_works() %>%
knitr::kable()| id | display_name | first_author | last_author | is_oa | top_concepts |
|---|---|---|---|---|---|
| W3160856016 | How to conduct a bibliometric analysis: An overview and guidelines | Naveen Donthu | Weng Marc Lim | TRUE | Bibliometrics, Field (mathematics), Resource (disambiguation) |
| W3001491100 | Software tools for conducting bibliometric analysis in science: An up-to-date review | José A. Moral-Muñoz | Manuel J. Cobo | TRUE | Bibliometrics, Visualization, Set (abstract data type) |
| W3038273726 | Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach | Surabhi Verma | Anders Gustafsson | TRUE | Bibliometrics, Field (mathematics), Empirical research |
| W3044902155 | Financial literacy: A systematic review and bibliometric analysis | Kirti Goyal | Satish Kumar | FALSE | Financial literacy, Citation, Content analysis |
| W3198357836 | Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis | John W. Goodell | Debidutta Pattnaik | FALSE | Scholarship, Valuation (finance), Corporate finance |
| W3042215340 | A bibliometric analysis using VOSviewer of publications on COVID-19 | Yuetian Yu | Erzhen Chen | TRUE | Citation, Bibliometrics, China |
Read on to see how we can shorten these two function calls.
Authors
Similarly to work, we can use identifier to pass in authors’ OpenAlex ID.
Example: We want more information on authors with IDs A5069892096 and A5023888391.
oa_fetch(
identifier = c("A5069892096", "A5023888391"),
verbose = TRUE
) %>%
show_authors() %>%
knitr::kable()## Requesting url: https://api.openalex.org/authors?filter=openalex%3AA5069892096%7CA5023888391## Getting 1 page of results with a total of 2 records...| id | display_name | orcid | works_count | cited_by_count | top_concepts |
|---|---|---|---|---|---|
| A5069892096 | Massimo Aria | 0000-0002-8517-9411 | 217 | 13113 | Physiology, Pathology and Forensic Medicine, Periodontics |
| A5023888391 | Jason Priem | 0000-0001-6187-6610 | 62 | 3864 | Statistics, Probability and Uncertainty, Information Systems, Communication |
Example: We want download all authors’ records of scholars who work at the University of Naples Federico II (OpenAlex ID: I71267560) and who have published more than 499 works.
Let’s first check how many records match the query, then set
count_only = FALSE to download the entire collection. We
can do this by first defining a list of arguments, then adding
count_only (default FALSE) to this list:
my_arguments <- list(
entity = "authors",
last_known_institutions.id = "I71267560",
works_count = ">499"
)
do.call(oa_fetch, c(my_arguments, list(count_only = TRUE)))## count db_response_time_ms page per_page
## [1,] 49 137 1 1
do.call(oa_fetch, my_arguments) %>%
show_authors() %>%
knitr::kable()| id | display_name | orcid | works_count | cited_by_count | top_concepts |
|---|---|---|---|---|---|
| A5114377868 | L. Lista | 0000-0001-6471-5492 | 2925 | 136043 | Nuclear and High Energy Physics, Nuclear and High Energy Physics, Nuclear and High Energy Physics |
| A5106552509 | C. Sciacca | 0000-0002-8412-4072 | 2759 | 100348 | Nuclear and High Energy Physics, Nuclear and High Energy Physics, Nuclear and High Energy Physics |
| A5106315809 | M. Merola | 0000-0002-7082-8108 | 1355 | 73380 | Nuclear and High Energy Physics, Nuclear and High Energy Physics, Nuclear and High Energy Physics |
| A5003544129 | Annamaria Colao | 0000-0001-6986-266X | 1324 | 46429 | Endocrinology, Diabetes and Metabolism, Endocrinology, Diabetes and Metabolism, Surgery |
| A5081032576 | Giovanni Esposito | 0000-0003-0565-7127 | 1077 | 21898 | Surgery, Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging |
| A5076706548 | Salvatore Capozziello | 0000-0003-4886-2024 | 1058 | 39315 | Astronomy and Astrophysics, Nuclear and High Energy Physics, Astronomy and Astrophysics |
You can also use other filters such as display_name,
has_orcid, and orcid:
oa_fetch(
entity = "authors",
display_name.search = "Massimo Aria",
has_orcid = "true"
) %>%
show_authors() %>%
knitr::kable()| id | display_name | orcid | works_count | cited_by_count | top_concepts |
|---|---|---|---|---|---|
| A5069892096 | Massimo Aria | 0000-0002-8517-9411 | 218 | 13180 | Physiology, Pathology and Forensic Medicine, Periodontics |
oa_fetch(
entity = "authors",
orcid = "0000-0002-8517-9411"
) %>%
show_authors() %>%
knitr::kable()| id | display_name | orcid | works_count | cited_by_count | top_concepts |
|---|---|---|---|---|---|
| A5069892096 | Massimo Aria | 0000-0002-8517-9411 | 218 | 13180 | Physiology, Pathology and Forensic Medicine, Periodontics |
Institutions
Example: We want download all records regarding Italian institutions (country_code:it) that are classified as educational (type:education). Again, we check how many records match the query then download the collection:
italian_insts <- list(
entity = "institutions",
country_code = "it",
type = "education",
verbose = TRUE
)
do.call(oa_fetch, c(italian_insts, list(count_only = TRUE)))## Requesting url: https://api.openalex.org/institutions?filter=country_code%3Ait%2Ctype%3Aeducation## count db_response_time_ms page per_page
## [1,] 150 148 1 1## Requesting url: https://api.openalex.org/institutions?filter=country_code%3Ait%2Ctype%3Aeducation## Getting 1 page of results with a total of 150 records...## Rows: 150
## Columns: 22
## $ id <chr> "https://openalex.org/I154387261", "https:/…
## $ display_name <chr> "Vita-Salute San Raffaele University", "Mag…
## $ display_name_alternatives <list> <"Université vie-santé Saint Raphaël", "Un…
## $ display_name_acronyms <list> NA, NA, NA, "UniSanRaffaele", NA, <"USGM",…
## $ international_display_name <list> <"Універсітэт Віта-Салютэ Сан-Рафаэле", "U…
## $ ror <chr> "https://ror.org/01gmqr298", "https://ror.o…
## $ ids <list> <"https://openalex.org/I154387261", "https…
## $ country_code <chr> "IT", "IT", "IT", "IT", "IT", "IT", "IT", "…
## $ geo <list> [<data.frame[1 x 7]>], [<data.frame[1 x 7]…
## $ type <chr> "education", "education", "education", "edu…
## $ homepage_url <chr> "https://www.unisr.it", "https://web.unicz.…
## $ image_url <chr> "https://commons.wikimedia.org/w/index.php?…
## $ image_thumbnail_url <chr> "https://commons.wikimedia.org/w/index.php?…
## $ associated_institutions <list> [<data.frame[1 x 6]>], [<data.frame[1 x 6]…
## $ works_count <int> 33459, 16561, 15765, 12680, 9698, 4616, 392…
## $ cited_by_count <int> 1105598, 410744, 402284, 564221, 285768, 89…
## $ counts_by_year <list> [<data.frame[14 x 3]>], [<data.frame[14 x …
## $ summary_stats <list> <4.812068, 367.000000, 14878.000000>, <4.1…
## $ works_api_url <chr> "https://api.openalex.org/works?filter=inst…
## $ topics <list> [<tbl_df[100 x 5]>], [<tbl_df[100 x 5]>], …
## $ updated_date <chr> "2025-04-27T19:09:01.374431", "2025-04-27T1…
## $ created_date <chr> "2016-06-24", "2016-06-24", "2016-06-24", "…Keywords
Example: We want to download the records of all the keywords that more than 1000 works were tagged with:
popular_keywords <- list(
entity = "keywords",
works_count = ">1000",
verbose = TRUE
)
do.call(oa_fetch, c(popular_keywords, list(count_only = TRUE)))## Requesting url: https://api.openalex.org/keywords?filter=works_count%3A%3E1000## count db_response_time_ms page per_page
## [1,] 101 30 1 1## Requesting url: https://api.openalex.org/keywords?filter=works_count%3A%3E1000## Getting 1 page of results with a total of 101 records...## Rows: 101
## Columns: 7
## $ id <chr> "https://openalex.org/keywords/diagnosis", "https://ope…
## $ display_name <chr> "Diagnosis", "Second Language Acquisition", "Audio-Visu…
## $ works_count <int> 267464, 127763, 117782, 91651, 73541, 71513, 64572, 636…
## $ cited_by_count <int> 888915, 1203886, 1259369, 482101, 808723, 335022, 87885…
## $ works_api_url <chr> "https://api.openalex.org/works?filter=keywords.id:keyw…
## $ updated_date <chr> "2024-04-15T13:29:44.932572", "2024-05-13T10:01:10.6536…
## $ created_date <chr> "2024-04-10", "2024-04-10", "2024-04-10", "2024-04-10",…Other examples
Get all works citing a particular work
We can download all publications citing another publication by using the filter attribute cites.
For example, if we want to download all publications citing the
article Aria and Cuccurullo (2017), we have just to set the argument
filter as cites = "W2755950973" where “W2755950973” is the
OA id for the article by Aria and Cuccurullo.
aria_count <- oa_fetch(
entity = "works",
cites = "W2755950973",
count_only = TRUE,
verbose = TRUE
) ## Requesting url: https://api.openalex.org/works?filter=cites%3AW2755950973
aria_count## count db_response_time_ms page per_page
## [1,] 9235 150 1 1This query will return a collection of NA publications. Among these articles, let’s download the ones published in the following year:
oa_fetch(
entity = "works",
cites = "W2755950973",
publication_year = 2018,
count_only = FALSE,
verbose = TRUE
) %>%
dplyr::glimpse()## Requesting url: https://api.openalex.org/works?filter=cites%3AW2755950973%2Cpublication_year%3A2018## Getting 1 page of results with a total of 32 records...## Rows: 32
## Columns: 43
## $ id <chr> "https://openalex.org/W2896801517", "https…
## $ title <chr> "Global trends in infectious diseases of s…
## $ display_name <chr> "Global trends in infectious diseases of s…
## $ authorships <list> [<tbl_df[2 x 7]>], [<tbl_df[2 x 7]>], [<t…
## $ abstract <chr> "Pork accounts for more than one-third of …
## $ doi <chr> "https://doi.org/10.1073/pnas.1806068115",…
## $ publication_date <date> 2018-10-22, 2018-11-26, 2018-12-20, 2018-…
## $ publication_year <int> 2018, 2018, 2018, 2018, 2018, 2018, 2018, …
## $ fwci <dbl> 4.079, 14.062, 7.865, 43.967, 12.809, 1.24…
## $ cited_by_count <int> 248, 243, 193, 168, 129, 121, 118, 89, 87,…
## $ counts_by_year <list> [<data.frame[8 x 2]>], [<data.frame[7 x 2…
## $ cited_by_api_url <chr> "https://api.openalex.org/works?filter=cit…
## $ ids <list> <"https://openalex.org/W2896801517", "htt…
## $ type <chr> "review", "article", "article", "article",…
## $ is_oa <lgl> TRUE, TRUE, FALSE, TRUE, TRUE, FALSE, FALS…
## $ is_oa_anywhere <lgl> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE,…
## $ oa_status <chr> "bronze", "bronze", "green", "bronze", "go…
## $ oa_url <chr> "https://doi.org/10.1073/pnas.1806068115",…
## $ any_repository_has_fulltext <lgl> TRUE, FALSE, TRUE, FALSE, TRUE, TRUE, FALS…
## $ source_display_name <chr> "Proceedings of the National Academy of Sc…
## $ source_id <chr> "https://openalex.org/S125754415", "https:…
## $ issn_l <chr> "0027-8424", "0043-1397", "0169-5347", "00…
## $ host_organization <chr> "https://openalex.org/P4310320052", "https…
## $ host_organization_name <chr> "National Academy of Sciences", "Wiley", "…
## $ landing_page_url <chr> "https://doi.org/10.1073/pnas.1806068115",…
## $ pdf_url <chr> NA, "https://agupubs.onlinelibrary.wiley.c…
## $ license <chr> NA, NA, NA, NA, "cc-by", NA, NA, "publishe…
## $ version <chr> "publishedVersion", "publishedVersion", NA…
## $ referenced_works <list> <"https://openalex.org/W1530619192", "htt…
## $ referenced_works_count <int> 23, 85, 97, 248, 84, 228, 75, 138, 78, 18,…
## $ related_works <list> <"https://openalex.org/W4391486112", "htt…
## $ concepts <list> [<data.frame[26 x 5]>], [<data.frame[22 x…
## $ topics <list> [<tbl_df[12 x 5]>], [<tbl_df[12 x 5]>], […
## $ keywords <list> [<data.frame[3 x 3]>], [<data.frame[3 x 3…
## $ is_paratext <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ is_retracted <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ language <chr> "en", "en", "en", "en", "en", "en", "en", …
## $ grants <list> <"https://openalex.org/F4320332299", "Nat…
## $ apc <list> NA, [<data.frame[2 x 5]>], [<data.frame[2…
## $ first_page <chr> "11495", "378", "224", "12", "e0207655", "…
## $ last_page <chr> "11500", "390", "238", "63", "e0207655", "…
## $ volume <chr> "115", "55", "34", "50", "13", "205", "45"…
## $ issue <chr> "45", "1", "3", "1", "11", NA, "3", "4-5",…Convert an OpenAlex data frame to a bibliometrix object
The bibliometrix R-package (https://www.bibliometrix.org) provides a set of tools for quantitative research in bibliometrics and scientometrics. Today it represents one of the most used science mapping software in the world. In a recent survey on bibliometric analysis tools, Moral-Muñoz et al. (2020) wrote: “At this moment, maybe Bibliometrix and its Shiny platform contain the more extensive set of techniques implemented, and together with the easiness of its interface, could be a great software for practitioners”.
The function oa2bibliometrix converts a bibliographic data frame of works into a bibliometrix object. This object can be used as input collection of a science mapping workflow.
bib_ls <- list(
identifier = NULL,
entity = "works",
cites = "W2755950973",
from_publication_date = "2022-01-01",
to_publication_date = "2022-03-31"
)
do.call(oa_fetch, c(bib_ls, list(count_only = TRUE)))## count db_response_time_ms page per_page
## [1,] 404 93 1 1
do.call(oa_fetch, bib_ls) %>%
oa2bibliometrix() %>%
dplyr::glimpse()## Warning in oa2bibliometrix(.): oa2bibliometrix() is deprecated. Please use
## bibliometrix::convert2df() instead.## Rows: 404
## Columns: 59
## $ AU <chr> "JÔNATAS AUGUSTO MANZOLLI;JOÃO PEDRO F. TR…
## $ RP <chr> "INESC COIMBRA, UNIVERSITY OF COIMBRA, DEE…
## $ C1 <chr> "INESC COIMBRA, UNIVERSITY OF COIMBRA, DEE…
## $ AU_UN <chr> "C(\"INSTITUTE FOR SYSTEMS ENGINEERING AND…
## $ AU_CO <chr> "PORTUGAL;PORTUGAL;PORTUGAL;PORTUGAL;PORTU…
## $ ID <chr> "WASTEWATER;ENVIRONMENTAL SCIENCE;WEB OF S…
## $ id_url <chr> "https://openalex.org/W4210864411", "https…
## $ title <chr> "Wastewater treatment and emerging contami…
## $ authorships <list> [<tbl_df[3 x 7]>], [<tbl_df[4 x 7]>], [<t…
## $ abstract <chr> NA, NA, "Abstract Conversational agents ar…
## $ doi <chr> "https://doi.org/10.1016/j.chemosphere.202…
## $ publication_date <date> 2022-02-08, 2022-03-01, 2022-03-08, 2022-…
## $ fwci <dbl> 4.712, 70.747, 24.314, 33.854, 9.445, 20.6…
## $ counts_by_year <list> [<data.frame[4 x 2]>], [<data.frame[5 x 2…
## $ cited_by_api_url <chr> "https://api.openalex.org/works?filter=cit…
## $ ids <list> <"https://openalex.org/W4210864411", "htt…
## $ is_oa <lgl> FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, TR…
## $ is_oa_anywhere <lgl> FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, TR…
## $ oa_status <chr> "closed", "bronze", "closed", "closed", "h…
## $ oa_url <chr> NA, "https://link.springer.com/content/pdf…
## $ any_repository_has_fulltext <lgl> FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, FA…
## $ source_display_name <chr> "Chemosphere", "Electronic Markets", "Psyc…
## $ source_id <chr> "https://openalex.org/S203465130", "https:…
## $ issn_l <chr> "0045-6535", "1019-6781", "0742-6046", "00…
## $ host_organization <chr> "https://openalex.org/P4310320990", "https…
## $ host_organization_name <chr> "Elsevier BV", "Springer Science+Business …
## $ landing_page_url <chr> "https://doi.org/10.1016/j.chemosphere.202…
## $ pdf_url <chr> NA, "https://link.springer.com/content/pdf…
## $ license <chr> NA, NA, NA, NA, "cc-by", NA, "cc-by-nc-nd"…
## $ version <chr> NA, "publishedVersion", NA, NA, "published…
## $ referenced_works <list> <"https://openalex.org/W1854025783", "htt…
## $ referenced_works_count <int> 88, 394, 182, 154, 79, 54, 160, 40, 119, 5…
## $ related_works <list> <"https://openalex.org/W4394593659", "htt…
## $ concepts <list> [<data.frame[16 x 5]>], [<data.frame[9 x …
## $ topics <list> [<tbl_df[12 x 5]>], [<tbl_df[12 x 5]>], […
## $ keywords <list> [<data.frame[1 x 3]>], NA, [<data.frame[2…
## $ is_paratext <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ is_retracted <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ language <chr> "en", "en", "en", "en", "en", "en", "en", …
## $ grants <list> <"https://openalex.org/F4320321001", "Nat…
## $ apc <list> [<data.frame[2 x 5]>], [<data.frame[2 x 5…
## $ first_page <chr> "133932", "297", "1129", "7527", "104608",…
## $ last_page <chr> "133932", "338", "1155", "7550", "104608",…
## $ volume <chr> "297", "32", "39", "60", "136", "30", "159…
## $ issue <chr> NA, "1", "6", "24", NA, "2", NA, "7", NA, …
## $ id_oa <chr> "W4210864411", "W4220923293", "W4220991995…
## $ CR <chr> "W1854025783;W1896090423;W1965064785;W1990…
## $ TI <chr> "WASTEWATER TREATMENT AND EMERGING CONTAMI…
## $ AB <chr> NA, NA, "ABSTRACT CONVERSATIONAL AGENTS AR…
## $ SO <chr> "CHEMOSPHERE", "ELECTRONIC MARKETS", "PSYC…
## $ DT <chr> "REVIEW", "ARTICLE", "ARTICLE", "ARTICLE",…
## $ DB <chr> "OPENALEX", "OPENALEX", "OPENALEX", "OPENA…
## $ JI <chr> "S203465130", "S137519996", "S102896891", …
## $ J9 <chr> "S203465130", "S137519996", "S102896891", …
## $ PY <int> 2022, 2022, 2022, 2022, 2022, 2022, 2022, …
## $ TC <int> 214, 183, 176, 164, 137, 127, 122, 121, 11…
## $ DI <chr> "10.1016/j.chemosphere.2022.133932", "10.1…
## $ SR_FULL <chr> "JÔNATAS AUGUSTO MANZOLLI, 2022, CHEMOSPHE…
## $ SR <chr> "JÔNATAS AUGUSTO MANZOLLI, 2022, CHEMOSPHE…About OpenAlex
OpenAlex is a fully open catalog of the global research system. It’s named after the ancient Library of Alexandria. The OpenAlex dataset describes scholarly entities and how those entities are connected to each other. There are five types of entities:
Works are papers, books, datasets, etc; they cite other works
Authors are people who create works
Institutions are universities and other orgs that are affiliated with works (via authors)
Concepts tag Works with a topic
Acknowledgements
Package hex was made with Midjourney and thus inherits a CC BY-NC 4.0 license.