B.2 Carga de datos

B.2.1 Datos de ejemplo

En el paquete se incluyen dos conjuntos de datos de ejemplo correspondientes a la búsqueda en WoS por el campo Organización-Nombre preferido de la UDC (Organization-Enhaced: OG = Universidade da Coruna):

  • wosdf: año 2015.

  • wosdf2: área de investigación ‘Mathematics’, años 2008-2017.

Variables WoS:

# View(wosdf2) # En RStudio...
variable.labels <- attr(wosdf, "variable.labels")
knitr::kable(as.data.frame(variable.labels)) # caption = "Variable labels"
variable.labels
PT Publication type
AU Author
BA Book authors
BE Editor
GP Group author
AF Author full
BF Book authors fullname
CA Corporate author
TI Title
SO Publication name
SE Series title
BS Book series
LA Language
DT Document type
CT Conference title
CY Conference year
CL Conference place
SP Conference sponsors
HO Conference host
DE Keywords
ID Keywords Plus
AB Abstract
C1 Addresses
RP Reprint author
EM Author email
RI Researcher id numbers
OI Orcid numbers
FU Funding agency and grant number
FX Funding text
CR Cited references
NR Number of cited references
TC Times cited
Z9 Total times cited count
U1 Usage Count (Last 180 Days)
U2 Usage Count (Since 2013)
PU Publisher
PI Publisher city
PA Publisher address
SN ISSN
EI eISSN
BN ISBN
J9 Journal.ISI
JI Journal.ISO
PD Publication date
PY Year published
VL Volume
IS Issue
PN Part number
SU Supplement
SI Special issue
MA Meeting abstract
BP Beginning page
EP Ending page
AR Article number
DI DOI
D2 Book DOI
PG Page count
WC WOS category
SC Research areas
GA Document delivery number
UT Access number
PM Pub Med ID

Se puede crear una base de datos con la función CreateDB.wos():

db <- CreateDB.wos(wosdf2, label = "Mathematics_UDC_2008-2017 (01-02-2019)")
str(db, 1)
## List of 11
##  $ Docs      :'data.frame':  389 obs. of  26 variables:
##  $ Authors   :'data.frame':  611 obs. of  4 variables:
##  $ AutDoc    :'data.frame':  1260 obs. of  2 variables:
##  $ Categories:'data.frame':  46 obs. of  2 variables:
##  $ CatDoc    :'data.frame':  866 obs. of  2 variables:
##  $ Areas     :'data.frame':  26 obs. of  2 variables:
##  $ AreaDoc   :'data.frame':  771 obs. of  2 variables:
##  $ Addresses :'data.frame':  896 obs. of  5 variables:
##  $ AddAutDoc :'data.frame':  1328 obs. of  3 variables:
##  $ Journals  :'data.frame':  150 obs. of  12 variables:
##  $ label     : chr "Mathematics_UDC_2008-2017 (01-02-2019)"
##  - attr(*, "variable.labels")= Named chr [1:62] "Publication type" "Author" "Book authors" "Editor" ...
##   ..- attr(*, "names")= chr [1:62] "PT" "AU" "BA" "BE" ...
##  - attr(*, "class")= chr "wos.db"

B.2.2 Cargar datos de directorio

Se pueden cargar automáticamente los archivos wos (tienen una limitación de 500 registros) de un subdirectorio:

dir("UDC_2008-2017 (01-02-2019)", pattern='*.txt')
##  [1] "savedrecs01.txt" "savedrecs02.txt" "savedrecs03.txt" "savedrecs04.txt"
##  [5] "savedrecs05.txt" "savedrecs06.txt" "savedrecs07.txt" "savedrecs08.txt"
##  [9] "savedrecs09.txt" "savedrecs10.txt" "savedrecs11.txt" "savedrecs12.txt"
## [13] "savedrecs13.txt" "savedrecs14.txt" "savedrecs15.txt"

Se pueden combinar los ficheros y crear la correspondiente base de datos con los siguientes comandos:

wos.txt <- ImportSources.wos("UDC_2008-2017 (01-02-2019)", other = FALSE)
db.txt <- CreateDB.wos(wos.txt)