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https://github.com/ropensci/openalexR

Latest version: 1.4.0, 2024-10-24

 

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

https://massimoaria.com

 

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 by oa_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 |> oa2df

  • oa_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…
## $ author                      <list> [<data.frame[2 x 12]>]
## $ ab                          <chr> "The use of bibliometrics is gradually ext…
## $ publication_date            <date> 2017-09-12
## $ so                          <chr> "Journal of Informetrics"
## $ so_id                       <chr> "https://openalex.org/S205292342"
## $ host_organization           <chr> "Elsevier BV"
## $ issn_l                      <chr> "1751-1577"
## $ url                         <chr> "https://doi.org/10.1016/j.joi.2017.08.007"
## $ pdf_url                     <lgl> NA
## $ license                     <lgl> NA
## $ version                     <lgl> NA
## $ first_page                  <chr> "959"
## $ last_page                   <chr> "975"
## $ volume                      <chr> "11"
## $ issue                       <chr> "4"
## $ is_oa                       <lgl> FALSE
## $ is_oa_anywhere              <lgl> FALSE
## $ oa_status                   <chr> "closed"
## $ oa_url                      <lgl> NA
## $ any_repository_has_fulltext <lgl> FALSE
## $ language                    <chr> "en"
## $ grants                      <lgl> NA
## $ cited_by_count              <int> 7406
## $ counts_by_year              <list> [<data.frame[10 x 2]>]
## $ publication_year            <int> 2017
## $ cited_by_api_url            <chr> "https://api.openalex.org/works?filter=ci…
## $ ids                         <list> <"https://openalex.org/W2755950973", "http…
## $ doi                         <chr> "https://doi.org/10.1016/j.joi.2017.08.007"
## $ type                        <chr> "article"
## $ referenced_works            <list> <"https://openalex.org/W1497199863", "htt…
## $ related_works               <list> <"https://openalex.org/W45233828", "https:…
## $ is_paratext                 <lgl> FALSE
## $ is_retracted                <lgl> FALSE
## $ concepts                    <list> [<data.frame[10 x 5]>]
## $ topics                      <list> [<tbl_df[12 x 5]>]
## $ apc                         <list> [<data.frame[2 x 5]>]

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 so url is_oa top_concepts
W2755950973 bibliometrix : An R-tool for comprehensive science mapping analysis Massimo Aria Corrado Cuccurullo Journal of Informetrics https://doi.org/10.1016/j.joi.2017.08.007 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 so url is_oa top_concepts
W2755950973 bibliometrix : An R-tool for comprehensive science mapping analysis Massimo Aria Corrado Cuccurullo Journal of Informetrics https://doi.org/10.1016/j.joi.2017.08.007 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 so url is_oa top_concepts
W2755950973 bibliometrix : An R-tool for comprehensive science mapping analysis Massimo Aria Corrado Cuccurullo Journal of Informetrics https://doi.org/10.1016/j.joi.2017.08.007 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 PeerJ https://doi.org/10.7717/peerj.4375 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 so url is_oa top_concepts
W2755950973 bibliometrix : An R-tool for comprehensive science mapping analysis Massimo Aria Corrado Cuccurullo Journal of Informetrics https://doi.org/10.1016/j.joi.2017.08.007 FALSE Workflow, Bibliometrics, Software
W3206431085 PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods Joseph D. Romano Jason H. Moore Bioinformatics https://doi.org/10.1093/bioinformatics/btab727 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 so url 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 PeerJ https://doi.org/10.7717/peerj.4375 TRUE Citation, License, Bibliometrics
W2046766973 Sharing Detailed Research Data Is Associated with Increased Citation Rate Heather Piwowar Douglas B. Fridsma PLoS ONE https://doi.org/10.1371/journal.pone.0000308 TRUE Citation, Clinical trial, Impact factor
W2045657963 Data reuse and the open data citation advantage Heather Piwowar Todd Vision PeerJ https://doi.org/10.7717/peerj.175 TRUE Citation, Reuse
W1572136682 Altmetrics: Value all research products Heather Piwowar NA Nature https://doi.org/10.1038/493159a TRUE Altmetrics, Value (mathematics)
W2122130843 Scientometrics 2.0: New metrics of scholarly impact on the social Web Jason Priem Bradely H. Hemminger First Monday https://doi.org/10.5210/fm.v15i7.2874 FALSE Bookmarking, Altmetrics, Social media
W1553564559 Altmetrics in the wild: Using social media to explore scholarly impact Jason Priem Bradley M. Hemminger arXiv (Cornell University) https://arxiv.org/abs/1203.4745 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 320 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 so url is_oa top_concepts
W2755950973 bibliometrix : An R-tool for comprehensive science mapping analysis Massimo Aria Corrado Cuccurullo Journal of Informetrics https://doi.org/10.1016/j.joi.2017.08.007 FALSE Workflow, Bibliometrics, Software
W2777772618 Interoception and Mental Health: A Roadmap Sahib S. Khalsa Nancy Zucker Biological Psychiatry Cognitive Neuroscience and Neuroimaging https://doi.org/10.1016/j.bpsc.2017.12.004 TRUE Mental health, Allostasis, Anxiety
W2955219525 Scaling tree-based automated machine learning to biomedical big data with a feature set selector Trang T. Le Jason H. Moore Bioinformatics https://doi.org/10.1093/bioinformatics/btz470 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 Social Indicators Research https://doi.org/10.1007/s11205-020-02281-3 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 Scientometrics https://doi.org/10.1007/s11192-016-1948-8 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 Frontiers in Aging Neuroscience https://doi.org/10.3389/fnagi.2018.00317 TRUE Correlation, Mood, Set (abstract data type)

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,]   376                  58    1        1

We 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 so url is_oa top_concepts
W3160856016 How to conduct a bibliometric analysis: An overview and guidelines Naveen Donthu Weng Marc Lim Journal of Business Research https://doi.org/10.1016/j.jbusres.2021.04.070 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 El Profesional de la Informacion https://doi.org/10.3145/epi.2020.ene.03 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 Journal of Business Research https://doi.org/10.1016/j.jbusres.2020.06.057 TRUE Bibliometrics, Field (mathematics), Empirical research
W3044902155 Financial literacy: A systematic review and bibliometric analysis Kirti Goyal Satish Kumar International Journal of Consumer Studies https://doi.org/10.1111/ijcs.12605 FALSE Financial literacy, Content analysis, Citation
W3042215340 A bibliometric analysis using VOSviewer of publications on COVID-19 Yuetian Yu Erzhen Chen Annals of Translational Medicine https://doi.org/10.21037/atm-20-4235 TRUE Citation, Bibliometrics, China
W3198357836 Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis John W. Goodell Debidutta Pattnaik Journal of Behavioral and Experimental Finance https://doi.org/10.1016/j.jbef.2021.100577 FALSE Scholarship, Valuation (finance), Corporate finance

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 affiliation_display_name top_concepts
A5069892096 Massimo Aria 0000-0002-8517-9411 197 10955 University of Naples Federico II Physiology, Pathology and Forensic Medicine, Periodontics
A5023888391 Jason Priem 0000-0001-6187-6610 62 3693 OurResearch 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,]    46                 164    1        1
do.call(oa_fetch, my_arguments) %>% 
  show_authors() %>%
  knitr::kable()
## Warning: Unknown or uninitialised column: `name`.
## Warning: Unknown or uninitialised column: `display_name`.
## Warning: Unknown or uninitialised column: `name`.
## Warning: Unknown or uninitialised column: `display_name`.
## Warning: Unknown or uninitialised column: `name`.
## Warning: Unknown or uninitialised column: `display_name`.
## Warning: Unknown or uninitialised column: `name`.
## Warning: Unknown or uninitialised column: `display_name`.
id display_name orcid works_count cited_by_count affiliation_display_name top_concepts
A5091797706 L. Lista 0000-0001-6471-5492 3438 155375 Istituto Nazionale di Fisica Nucleare, Sezione di Napoli Nuclear and High Energy Physics, Nuclear and High Energy Physics, Nuclear and High Energy Physics
A5106552509 C. Sciacca 0000-0002-8412-4072 2710 94358 University of Naples Federico II Nuclear and High Energy Physics, Nuclear and High Energy Physics, Nuclear and High Energy Physics
A5106315809 M. Merola 0000-0002-7082-8108 1326 70620 Istituto Nazionale di Fisica Nucleare, Sezione di Napoli Nuclear and High Energy Physics, Nuclear and High Energy Physics, Nuclear and High Energy Physics
A5003544129 Annamaria Colao 0000-0001-6986-266X 1310 44049 University of Naples Federico II Endocrinology, Diabetes and Metabolism, Endocrinology, Diabetes and Metabolism, Surgery
A5037805233 Micaela Morelli 0000-0003-0394-5782 1164 12062 University of Naples Federico II Cellular and Molecular Neuroscience, Cellular and Molecular Neuroscience, Neurology
A5076706548 Salvatore Capozziello 0000-0003-4886-2024 1024 34376 University of Naples Federico II 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 affiliation_display_name top_concepts
A5069892096 Massimo Aria 0000-0002-8517-9411 197 10955 University of Naples Federico II 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 affiliation_display_name top_concepts
A5069892096 Massimo Aria 0000-0002-8517-9411 197 10955 University of Naples Federico II 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,]   232                  41    1        1
dplyr::glimpse(do.call(oa_fetch, italian_insts))
## Requesting url: https://api.openalex.org/institutions?filter=country_code%3Ait%2Ctype%3Aeducation
## Getting 2 pages of results with a total of 232 records...
## Rows: 232
## Columns: 21
## $ id                         <chr> "https://openalex.org/I861853513", "https:/…
## $ display_name               <chr> "Sapienza University of Rome", "University …
## $ display_name_alternatives  <list> <"Université La Sapienza de Rome", "Rimska…
## $ display_name_acronyms      <list> NA, "UNIMI", "UNIBO", "UNIPD", NA, NA, "UN…
## $ display_name_international <list> <"Universiteit van Rome", "جامعة روما سابي…
## $ ror                        <chr> "https://ror.org/02be6w209", "https://ror.o…
## $ ids                        <list> <"https://openalex.org/I861853513", "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.uniroma1.it", "https://www.uni…
## $ 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[4 x 6]>], [<data.frame[2 x 6]…
## $ works_count                <int> 209637, 185366, 176817, 173604, 122598, 117…
## $ cited_by_count             <int> 5134159, 5470057, 4673112, 5019135, 3162965…
## $ counts_by_year             <list> [<data.frame[13 x 3]>], [<data.frame[13 x …
## $ 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> "2024-10-23T18:34:17.183337", "2024-10-24T1…
## $ created_date               <chr> "2016-06-24", "2016-06-24", "2016-06-24", "…

Concepts (think theme, keywords)

Example: We want to download the records of all the concepts that concern at least one million works:

popular_concepts <- list(
  entity = "concepts",
  works_count = ">1000000",
  verbose = TRUE
)

do.call(oa_fetch, c(popular_concepts, list(count_only = TRUE)))
## Requesting url: https://api.openalex.org/concepts?filter=works_count%3A%3E1000000
##      count db_response_time_ms page per_page
## [1,]   273                  18    1        1
dplyr::glimpse(do.call(oa_fetch, popular_concepts))
## Requesting url: https://api.openalex.org/concepts?filter=works_count%3A%3E1000000
## Getting 2 pages of results with a total of 273 records...
## Rows: 273
## Columns: 16
## $ id                         <chr> "https://openalex.org/C41008148", "https://…
## $ display_name               <chr> "Computer science", "Medicine", "Biology", …
## $ display_name_international <list> <"informatika", "የኮምፒውተር፡ጥናት", "Informatic…
## $ description                <chr> "study of computation", "field of study for…
## $ description_international  <list> <"studie van berekening en inligtingverwer…
## $ wikidata                   <chr> "https://www.wikidata.org/wiki/Q21198", "ht…
## $ level                      <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1…
## $ ids                        <list> <"https://openalex.org/C41008148", "https:…
## $ image_url                  <chr> "https://upload.wikimedia.org/wikipedia/com…
## $ image_thumbnail_url        <chr> "https://upload.wikimedia.org/wikipedia/com…
## $ ancestors                  <list> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, [<…
## $ related_concepts           <list> [<data.frame[93 x 5]>], [<data.frame[51 x …
## $ works_count                <int> 91640517, 63165832, 46945702, 43366261, 376…
## $ cited_by_count             <int> 677663491, 814030740, 884155767, 570502558,…
## $ counts_by_year             <list> [<data.frame[13 x 3]>], [<data.frame[13 x …
## $ works_api_url              <chr> "https://api.openalex.org/works?filter=conc…

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,]  7509                 109    1        1

This 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 31 records...
## Rows: 31
## Columns: 39
## $ 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…
## $ author                      <list> [<data.frame[2 x 12]>], [<data.frame[2 x …
## $ ab                          <chr> "Pork accounts for more than one-third of …
## $ publication_date            <date> 2018-10-22, 2018-11-26, 2018-12-20, 2018-…
## $ so                          <chr> "Proceedings of the National Academy of Sc…
## $ so_id                       <chr> "https://openalex.org/S125754415", "https:…
## $ host_organization           <chr> "National Academy of Sciences", "Wiley", "…
## $ issn_l                      <chr> "0027-8424", "0043-1397", "0169-5347", "00…
## $ url                         <chr> "https://doi.org/10.1073/pnas.1806068115",…
## $ pdf_url                     <chr> "https://www.pnas.org/content/pnas/115/45/…
## $ license                     <chr> NA, NA, NA, NA, "cc-by", NA, NA, "publishe…
## $ version                     <chr> "publishedVersion", "publishedVersion", NA…
## $ 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",…
## $ 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://www.pnas.org/content/pnas/115/45/…
## $ any_repository_has_fulltext <lgl> TRUE, FALSE, TRUE, FALSE, TRUE, TRUE, FALS…
## $ language                    <chr> "en", "en", "en", "en", "en", "en", "en", …
## $ grants                      <list> <"https://openalex.org/F4320332299", "Nat…
## $ cited_by_count              <int> 218, 199, 172, 150, 124, 114, 111, 84, 83,…
## $ counts_by_year              <list> [<data.frame[7 x 2]>], [<data.frame[6 x 2…
## $ publication_year            <int> 2018, 2018, 2018, 2018, 2018, 2018, 2018, …
## $ cited_by_api_url            <chr> "https://api.openalex.org/works?filter=cit…
## $ ids                         <list> <"https://openalex.org/W2896801517", "htt…
## $ doi                         <chr> "https://doi.org/10.1073/pnas.1806068115",…
## $ type                        <chr> "review", "article", "article", "article",…
## $ referenced_works            <list> <"https://openalex.org/W1530619192", "htt…
## $ related_works               <list> <"https://openalex.org/W4384639906", "htt…
## $ is_paratext                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ is_retracted                <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ concepts                    <list> [<data.frame[25 x 5]>], [<data.frame[22 x…
## $ topics                      <list> [<tbl_df[12 x 5]>], [<tbl_df[12 x 5]>], […
## $ apc                         <list> NA, [<data.frame[2 x 5]>], [<data.frame[2…

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,]   402                  33    1        1
do.call(oa_fetch, bib_ls) %>% 
  oa2bibliometrix() %>% 
  dplyr::glimpse()
## Rows: 402
## Columns: 53
## $ AU                          <chr> "YIXIA CHEN;MING‐WEI LIN;DAN ZHUANG", "WEN…
## $ RP                          <chr> "COLLEGE OF COMPUTER AND CYBER SECURITY, F…
## $ C1                          <chr> "COLLEGE OF COMPUTER AND CYBER SECURITY, F…
## $ AU_UN                       <chr> "FUJIAN NORMAL UNIVERSITY;FUJIAN NORMAL UN…
## $ AU_CO                       <chr> "CHINA;CHINA;CHINA", "MALAYSIA;INDIA;INDIA…
## $ ID                          <chr> "WASTEWATER;ENVIRONMENTAL SCIENCE;CONTAMIN…
## $ id_url                      <chr> "https://openalex.org/W4210864411", "https…
## $ title                       <chr> "Wastewater treatment and emerging contami…
## $ author                      <list> [<data.frame[3 x 12]>], [<data.frame[4 x …
## $ publication_date            <date> 2022-02-08, 2022-03-08, 2022-02-09, 2022-…
## $ so_id                       <chr> "https://openalex.org/S203465130", "https:…
## $ host_organization           <chr> "Elsevier BV", "Wiley", "Taylor & Francis"…
## $ issn_l                      <chr> "0045-6535", "0742-6046", "0020-7543", "10…
## $ url                         <chr> "https://doi.org/10.1016/j.chemosphere.202…
## $ pdf_url                     <chr> NA, NA, NA, "https://link.springer.com/con…
## $ license                     <chr> NA, NA, NA, NA, "cc-by", NA, "cc-by-nc-nd"…
## $ version                     <chr> NA, NA, NA, "publishedVersion", "published…
## $ first_page                  <chr> "133932", "1129", "7527", "297", "104608",…
## $ last_page                   <chr> "133932", "1155", "7550", "338", "104608",…
## $ volume                      <chr> "297", "39", "60", "32", "136", "30", "159…
## $ issue                       <chr> NA, "6", "24", "1", NA, "2", NA, NA, "6", …
## $ is_oa                       <lgl> FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, TR…
## $ is_oa_anywhere              <lgl> FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, TR…
## $ oa_status                   <chr> "closed", "closed", "closed", "bronze", "h…
## $ oa_url                      <chr> NA, NA, NA, "https://link.springer.com/con…
## $ any_repository_has_fulltext <lgl> FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FA…
## $ language                    <chr> "en", "en", "en", "en", "en", "en", "en", …
## $ grants                      <list> <"https://openalex.org/F4320321001", "Nat…
## $ counts_by_year              <list> [<data.frame[3 x 2]>], [<data.frame[3 x 2…
## $ cited_by_api_url            <chr> "https://api.openalex.org/works?filter=cit…
## $ ids                         <list> <"https://openalex.org/W4210864411", "htt…
## $ doi                         <chr> "https://doi.org/10.1016/j.chemosphere.202…
## $ referenced_works            <list> <"https://openalex.org/W1854025783", "htt…
## $ related_works               <list> <"https://openalex.org/W4388943160", "htt…
## $ is_paratext                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ is_retracted                <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
## $ concepts                    <list> [<data.frame[16 x 5]>], [<data.frame[24 x…
## $ topics                      <list> [<tbl_df[8 x 5]>], [<tbl_df[12 x 5]>], [<…
## $ apc                         <list> [<data.frame[2 x 5]>], [<data.frame[2 x 5…
## $ id_oa                       <chr> "W4210864411", "W4220991995", "W4210997151…
## $ CR                          <chr> "W1854025783;W1896090423;W1965064785;W1990…
## $ TI                          <chr> "WASTEWATER TREATMENT AND EMERGING CONTAMI…
## $ AB                          <chr> "IN RECENT YEARS, EMERGING CONTAMINANTS HA…
## $ SO                          <chr> "CHEMOSPHERE", "PSYCHOLOGY AND MARKETING",…
## $ DT                          <chr> "REVIEW", "ARTICLE", "ARTICLE", "ARTICLE",…
## $ DB                          <chr> "OPENALEX", "OPENALEX", "OPENALEX", "OPENA…
## $ JI                          <chr> "S203465130", "S102896891", "S65690446", "…
## $ J9                          <chr> "S203465130", "S102896891", "S65690446", "…
## $ PY                          <int> 2022, 2022, 2022, 2022, 2022, 2022, 2022, …
## $ TC                          <int> 172, 140, 118, 116, 101, 98, 90, 90, 87, 8…
## $ DI                          <chr> "10.1016/j.chemosphere.2022.133932", "10.1…
## $ SR_FULL                     <chr> "YIXIA CHEN, 2022, CHEMOSPHERE", "WENG MAR…
## $ SR                          <chr> "YIXIA CHEN, 2022, CHEMOSPHERE", "WENG MAR…

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.