Russian Journals indexed by Scopus, RSCI, and WoS

russian data citation indices scopus web of science r rsci issn.org crossref lens.org

How difficult it can be to build an aggregated list of the scientific journal titles indexed in A&I databases and citation indices? Extremely difficult, if those venues are the Russian academic journals. In this post I am reviewing the key obstacles and trying to build such a list of the Russian journals indexed in Web of Science Core Collection, Scopus, and RSCI (Russian Citation Index by Web of Science). This is a version updated on June 9, 2021.

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06-09-2021

Obstacles

  1. Legacy

The well-known problem of the academic titles is that they can change a title, publisher, and the credentials (ISSN, DOI prefix, etc). This can be a difficulty, if you have no access to the commercial services provided by ISSN Agency. But still it is a typical, not “Russian” problem.

  1. Translated Titles

A story started in 1954, when AIP got additonal funding from NSF for translation of the foreign journals. At that time USSR did not pay respect to things like copyright, so the commercial relations were quite difficult and involved the intermediaries, who launched the English versions of the Soviet titles (eventually privatized). In 1973 USSR signed the Universal Copyright Convention which spurred a M$-royalty-driven cooperation. After the Soviet Union ceased to exist, many publishers visited Moscow, and few managed to purchase the licenses for the translated versions (I have not seen the documents myself, but assume that the licenses are lifelong and irrevokable). That’s why nowadays there are dozens of journals existing in 2 language versions (Rus/Eng), registered by different publishers and in different countries, with up to 4 ISSN numbers (2 times p+e), but… also having one editorial board and practically the same set of articles.

Most A&I databases index the English versions, which de jure are not Russian, but de facto originate from the Russian editions. Shall we count those indexed titles as Russian or not?

  1. Combined titles

A quality of Soviet journals was not equally superb for all the titles, and some publishers decided to pack the best articles from few journals and sell it under a new cover. Such journals still exist. Assume that a combo title, traslating 50% of 2 Russian journals, is indexed in SCI - shall we count those Russian titles as “indexed”? There are some circulating “white lists” that regard such sources as “indexed” (though with special notes).

  1. Country of origin

This is the most controversary aspect. What makes a journal Russian or say Turkish? Is it a language? Or citizenship of the editors? Or a country stated in the ISSN journal profile? A location of the publisher? Or maybe of the founders? What if there are few international founders?

I hope this explains why the question “How many Russian academic titles are indexed in Scopus or Web of Science?” is doomed.

Scopus

Russian office of Elsevier publish their own, manually-curated list of the Russian titles indexed by Scopus. I will use the version released today (!) and remove the discontinued titles. I take it as it is, leaving Elsevier responsible for possible errors.

Show code
scopus <- readxl::read_xlsx(paste0(dir, "/sources/russian_titles_in_scopus_06.2021.xlsx"), 
                    sheet = "Title List", skip = 6) %>% 
  select(code = 1, srctitle = 3, pissn = 4, eissn = 5, Status) %>% 
  filter(Status=="Active", grepl("J", code)) %>% 
  pivot_longer(cols = c("pissn", "eissn"), names_to = "type", values_to = "issn") %>% 
  filter(!is.na(issn)) %>% 
  mutate(db = "scopus") %>% 
  select(db, srctitle, type, issn)

glimpse(scopus) 
Rows: 1,119
Columns: 4
$ db       <chr> "scopus", "scopus", "scopus", "scopus", "scopus", "~
$ srctitle <chr> "Ab Imperio", "Ab Imperio", "Acarina", "Acarina", "~
$ type     <chr> "pissn", "eissn", "pissn", "eissn", "eissn", "pissn~
$ issn     <chr> "2164-9731", "2164-9731", "0132-8077", "2221-5115",~

RSCI (WoS/Russian Science Citation Index)

Russian Science Citation Index is a joined project of Clarivate and the National Electronic Library aka eLIBRARY.RU. It has an ambiguous name, as eLIBRARY.RU has its own citation index (РИНЦ/RINC), which is also translated as Russian Science Citation Index. Sometimes, they are confused, e.g. RSCI Wikipedia page relates to the RINC, but also contains the external links relating to the Clarivate. As a result this page is referenced here and there in different sense - e.g. Wikipedia page for Web of Science refers to RSCI Wiki page as to its regional database). The project is supervised by the Russian Academy of Sciences (RAS) whose role is thought to ensure a proper selection process to fill in RSCI with the best Russian titles.

In May 2021 RAS issued a new list of RSCI titles. You know, as a table in PDF file (RAS-style).

I will not copy here a code I used to parse that PDF into a CSV, it is the same as I used for parsing the other PDF table in one of previous posts. So now I just read CSV (and you can download it as Excel file in the end of the post).

Show code
rsci <- read_csv(paste0(dir, "/sources/2021_rsci_list_parsed.csv")) %>% 
  select(srctitle = title, issn1, issn2) %>% 
  mutate(db = "rsci") %>% 
  pivot_longer(cols = c("issn1", "issn2"), 
               names_to = "type", values_to = "issn") %>% 
  filter(!is.na(issn)) %>% 
  select(db, srctitle, type, issn) %>% 
  filter(!is.na(issn))

glimpse(rsci)
Rows: 1,286
Columns: 4
$ db       <chr> "rsci", "rsci", "rsci", "rsci", "rsci", "rsci", "rs~
$ srctitle <chr> "Academia. Архитектура и строительство", "Acarina",~
$ type     <chr> "issn1", "issn1", "issn2", "issn1", "issn2", "issn1~
$ issn     <chr> "2077-9038", "0132-8077", "2221-5115", "2541-9420",~

Web of Science Core Collection

Clarivate do not craft a “special list” of the Russian journal titles, so my approach is first to select from Master Journal List all the titles where the country of origin is RUSSIA. This leaves a lot of “meta-Russian” journals apart, so I also took from Web of Science Masterl lists the titles present in Scopus and RSCI. This adds, to the previously selected titles, translated titles and some other of mixed origin. I used the versions dated as of May 18, 2021.

Show code
wos_merged <- paste0(dir, "/sources/") %>% list.files(full.names = TRUE) %>% 
  .[grepl("wos-core",.) & grepl("csv",.)] %>% 
  map_df(read_csv) %>% 
  pivot_longer(cols = c("ISSN", "eISSN"), 
               names_to = "issn.type", values_to = "issn") %>% 
  filter(!is.na(issn)) %>% 
  select(srctitle = 1, address = 3, type = issn.type, issn = issn)

wos <- bind_rows(
  wos_merged %>% filter(grepl("russia",address, ignore.case = TRUE)),
  wos_merged %>% filter(issn %in% rsci$issn),
  wos_merged %>% filter(issn %in% scopus$issn)
  ) %>% 
  mutate(db = "wos") %>% 
  select(db, srctitle, type, issn) %>% 
  distinct() 

remove(wos_merged)
glimpse(wos)
Rows: 788
Columns: 4
$ db       <chr> "wos", "wos", "wos", "wos", "wos", "wos", "wos", "w~
$ srctitle <chr> "NOVOE LITERATURNOE OBOZRENIE", "NOVYI MIR", "QUAES~
$ type     <chr> "ISSN", "ISSN", "ISSN", "eISSN", "ISSN", "eISSN", "~
$ issn     <chr> "0869-6365", "0130-7673", "2311-911X", "2313-6871",~

Aggregation

The next steps involved:

  1. cleaning and few manual corrections (removing “–” or Cyrillix X from ISSNs).

  2. adding ISSN-L to each individual ISSN (I use ISSN-L/ISSN mapping files, provided by ISSN.org) and ISSN registration info for each ISSN-L (the code is similar to that in previous post about VAK titles)

  3. checking if ISSNs registered in CrossRef and if any 2020 publications are deposited (the code is also available in the post about VAK titles)

  4. combining the harvested information into a wide table with ISSN-L as a key

Final Table

As the joint table is the main purpose of this post, some columns are adjusted with URLs:

You can use the interactive version below or download the table in Excel or CSV format.

Show code
db_pivot <- read_csv(paste0(dir, "/russian_titles_in_WSR_pivot_wc_wp.csv"))  %>% 
  select(issn_L, titles, wos, rsci, scopus,
         issn, issn_country = country_issn, 
         issn_title = src_title_issn, 
         cr_member = member,
         cr_publisher = publisher,
         cr_location = location,
         cr_2020_number = starts_with("cr_20")) 

db_pivot %>% arrange(desc(cr_2020_number)) %>% 
  mutate(issn_L = paste0('<a href=\'', 
                         paste0("https://portal.issn.org/resource/ISSN/", issn_L), 
                         '\'\\s target = \"_blank\")>', issn_L, '</a>')) %>%
  mutate(in_Lens = sapply(str_split(issn, "\\|"), 
                       function(x) paste0(paste0("source.issn:", x), collapse = "%20OR%20"))) %>%
  mutate(in_Lens = paste0("https://www.lens.org/lens/search/scholar/list?q=", 
                       gsub("-","",in_Lens), 
                       "&p=0&n=100")) %>%
  mutate(in_Lens = paste0('<a href=\'', in_Lens, 
                       '\'\\s target = \"_blank\")>', "search", '</a>')) %>%
  mutate(cr_2020 = sapply(str_split(issn, "\\|"), 
                       function(x) paste0(paste0("issn:", x), collapse = ","))) %>%
  mutate(cr_2020 = paste0("https://http://api.crossref.org/works?filter=", 
                        cr_2020, 
                       ",from-pub-date:2020-01,until-pub-date:2020-12")) %>%
  mutate(cr_2020 = paste0('<a href=\'', cr_2020, 
                       '\'\\s target = \"_blank\")>', 
                       ifelse(is.na(cr_2020_number),0,cr_2020_number), 
                       '</a>')) %>%
  rowwise() %>% 
  mutate(cr_member = ifelse(is.na(cr_member), NA_character_, 
         paste0("https://api.crossref.org/members/", cr_member))) %>% 
  mutate(cr_location = ifelse(is.na(cr_location), NA_character_, 
                              paste0("(location: ", cr_location,")"))) %>% 
  mutate(cr_publisher = ifelse(is.na(cr_member), NA_character_,
           paste0('<a href=\'', cr_member,  '\'\\s target = \"_blank\")>', 
                  cr_publisher, '</a>'))) %>%
  unite(c("cr_publisher", "cr_location"), col = "cr_publisher", 
        sep = "</br>", na.rm=TRUE) %>% 
  mutate_at(c("wos", "rsci", "scopus"), ~as.factor(.x)) %>% 
  mutate_at(c("issn", "titles"), ~gsub("\\|",";</br>",.x)) %>% 
  select(issn_L, titles, issn, wos, rsci, scopus, 
        in_Lens, cr_2020, cr_publisher, issn_country, issn_title) %>% 
  DT::datatable(rownames = FALSE, escape = FALSE, filter = 'top', 
               caption = htmltools::tags$caption(style = 'caption-side: bottom; text-align: left; font-size: 80%; color: #969696; font-family: Roboto Condensed;',
               'Data: portal.issn.org | crossref.org | elibrary.ru/project_rsci.asp | mjl.clarivate.com | elsevierscience.ru/products/scopus/ (see in the text).'),
               class = 'compact striped', extensions = 'Buttons', 
               options = list(searchHighlight = TRUE,
                 columnDefs = list(
                  list(width = '350px', targets = c(1)),
                  list(width = '300px', targets = c(8)),
                  list(width = '250px', targets = c(10)),
                  list(width = '80px', targets = c(0,2)),
                  list(width = '40px', targets = c(3:5)),
                  list(className = 'dt-center', targets = c(2:7))
                 ),
                buttons = c('csv', "excel"))) %>% 
     formatStyle('scopus',  backgroundColor = styleEqual('yes', '#ff6c00'), fontWeight = 'bold') %>% 
    formatStyle('wos',  backgroundColor = styleEqual('yes', '#5e33bf'), fontWeight = 'bold') %>% 
    formatStyle('rsci',  backgroundColor = styleEqual('yes', '#5EF085'), fontWeight = 'bold')

Limitations

  1. The table includes few journal titles that are hardly Russian, but RAS approved them to be a part of RSCI (it is their headache now).

  2. There can be some translated titles, indexed by Web of Science with other than Russian country of origin, which could be considered as “meta-Russian” in our exercise.

  3. The