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GESIS Search

Source: R/gesis_search.R
gesis_search.Rd

Query the GESIS search engine to retrieve metadata on research data, variables, tools, publications, libraries, and websites.

Usage

gesis_search(
  query = NULL,
  type = NULL,
  default_operator = "AND",
  fields = field_weights(),
  sort = "relevance",
  publication_year = NULL,
  countries = NULL,
  topics = NULL,
  authors = NULL,
  sources = NULL,
  study_title = NULL,
  study_group = NULL,
  collection_year = NULL,
  thematic_collections = NULL,
  method_data_collection = NULL,
  method_sampling = NULL,
  method_time = NULL,
  method_unit = NULL,
  data_type = NULL,
  interview_language = NULL,
  pages = 1,
  tidy = FALSE
)

# S3 method for class 'gesis_records'
as.data.frame(x, ...)

Arguments

query

The search term to query. Terms can be seperated by operators OR / AND. If no operator is specified, defaults to the operator specified in default_operator. If NULL, searches for all records. Queryless searches can still be filtered using the parameters below.

type

Type of search results to retrieve. Can be one of the following:

  • research_data: Survey data records

  • variables: Variables related to survey data records

  • instruments_tools: Measurement instruments like items, scales, questionnaires, tests, and indexes offered by ZIS.

  • publication: Publications like journal articles or book chapters

  • gesis_bib: Records from the GESIS library

  • gesis_web: GESIS websites

  • gesis_person: Institutional websites of GESIS employees

If NULL, includes all result types. Defaults to NULL.

default_operator

Character specifying the default operator to use as seperator of search terms. Can be "AND" or "OR". Defaults to "AND". Ignored if query is NULL.

fields

Character vector of field weights as returned by field_weights. Used to specify how much weight is given to query matches in certain metadata fields. The higher the weight, the more a field influences the match probability. Defaults to the default values specified by field_weights. Ignored if query is NULL.

sort

Attribute to sort by. Must be one of the following:

  • relevance: Sorts by relevance (whatever that means)

  • newest_first: Sorts by publication year, descending

  • oldest_first: Sorts by publication year, ascending

  • title_ascending: Sorts lexicographically by title, ascending

  • title_descending: Sorts lexicographically by title, descending

  • variable_ascending: Sorts lexicographically by variable name, ascending

  • variable_descending: Sorts lexicographically by variable name, descending

Defaults to "relevance" to mirror the behavior of the web interface.

publication_year

Numeric or character vector of length 2 specifying the time range in which a record was published. The first value is the start year and the second value is the end year. If NULL, returns records from all years. Defaults to NULL.

countries

Character vector specifying the country in which the record was published. If NULL, returns records from all countries. Defaults to NULL.

topics

Character vector specifying the topics to filter by. Example values include "Political behavior and attitudes" or "Migration". See https://search.gesis.org/ for a full list of possible topics.

authors

Character vector specifying the authors to filter by.

sources

Character vector specifying the source of the record.

study_title

Character vector specifying the study title. Only sensible for research data or variables.

study_group

Character vector specifying the study group. Only sensible for research data or variables.

collection_year

Numeric or character vector of length 2 specifying the time range in which a dataset was collected. The first value is the start year and the second value is the end year. If NULL, returns records from all years. Defaults to NULL. Only sensible for research data or variables.

thematic_collections

Character vector specifying the thematic collection a dataset or variable belongs to. Example values include "COVID-19" or "Environment and climate". See https://search.gesis.org/ for a full list of possible topics.

method_data_collection, method_sampling, method_time, method_unit

Arguments to filter by the methodology used in a study. It is possible to filter by the mode of data collection (method_data_collection), sampling procedure (method_sampling), temporal research design (method_unit) and analysis unit (method_unit). Only sensible for research data and variables.

data_type

Character vector specifying the data type of a dataset or variable. Example values include "numeric", "geospatial", and "text". Only sensible for research data and variables.

interview_language

Character vector specifying the interview language of a variable. Usually only "german" and "english" are available. Only sensible for variables.

pages

Numeric vector specifying the page numbers of the search results. By default, only the first page is returned. If NULL, iterates through all pages.

tidy

If TRUE, returns the records in a rectangular shape that can be wrangled more easily. In this form, some more complex metadata fields that cannot be converted to a rectangular shapre are discarded. If FALSE, returns the records as a list-like gesis_records object. This object is more comprehensive, but harder to work with. Defaults to FALSE.

x

Object of class gesis_records

...

Arguments passed on to the respective S3 methods.

Value

If tidy = FALSE, returns an object of class gesis_records consisting of multiple objects of class gesis_record. Each gesis_record contains attributes index, id, and score specifying the index, the record ID, and the match score.

If tidy = TRUE, returns a dataframe or tibble where each row is a record and each column is a metadata field.

In any case, the query used to retrieve the data is stored in the attribute query.

Examples

# Make a queryless search across the entire database and return
# the first 10 results
gesis_search()
#> A list of <gesis_records> with 10 records
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-27818
#> Title: Die Macht der Verhältnisse und die Stärke des Subjekts: eine Studie über
#> ostdeutsche Manager vor und nach 1989 ; zugleich eine biographietheoretische
#> Erklärung für Stabilität und Instabilität der DDR
#> Date: 2005
#> Persons:
#> • Nagel, Ulrike
#> • Teipen, Christina
#> • Velez, Andrea
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-22385
#> Title: Book Review: The Genetic Imaginary: DNA in the Canadian Criminal Justice
#> System
#> Date: 2005
#> Person:
#> • Benecke, Mark
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-31770
#> Title: Vermittlungsgutscheine: Zwischenergebnisse der Begleitforschung 2004. T.
#> 1, Datenstruktur und deskriptive Analysen
#> Date: 2005
#> Persons:
#> • Heinze, Anja
#> • Pfeiffer, Friedhelm
#> • Spermann, Alexander
#> • ... and 2 more
#> # ℹ 7 more records
#> # ℹ Use `print(n = ...)` to see more records

# Queries can be narrowed down by providing a query string
record <- gesis_search("climate change")

# gesis_search() searches for all types of records by default. If you only
# want to search for, say, datasets, you can set the `type` argument.
gesis_search(type = "research_data")
#> A list of <gesis_records> with 10 records
#> <gesis_record>
#> Type: research_data
#> ID: ZA4580
#> Title: German General Social Survey (ALLBUS) - Cumulation 1980-2012
#> Date: 2014
#> Persons:
#> • Allerbeck, Klaus
#> • Allmendinger, Jutta
#> • Andreß, Hans-Jürgen
#> • ... and 23 more
#> 
#> <gesis_record>
#> Type: research_data
#> ID: ZA6249
#> Title: Sächsische Längsschnittstudie - Welle 31, 2019
#> Date: 2020
#> Persons:
#> • Förster, Peter
#> • Brähler, Elmar
#> • Stöbel-Richter, Yve
#> • ... and 2 more
#> 
#> <gesis_record>
#> Type: research_data
#> ID: ZA1571
#> Title: Typologie der Wünsche 1986
#> Date: 1987
#> Person:
#> • BURDA Marktforschung, Offenburg
#> # ℹ 7 more records
#> # ℹ Use `print(n = ...)` to see more records

# By default, only 10 results (1 page) are returned. You can specify
# which pages should queried or if all should be returned
gesis_search("climate change", pages = 2:3) # pages 2 and 3
#> A list of <gesis_records> with 20 records
#> <gesis_record>
#> Type: variables
#> ID: exploredata-ZA3850_VarV195
#> Title: V195 - HOCHWASSER:KLIMAVERäND.?
#> Date: 2003
#> 
#> <gesis_record>
#> Type: variables
#> ID: exploredata-ZA6802_Varvn64
#> Title: vn64 - Salienz Klimawandel
#> Date: 2019
#> 
#> <gesis_record>
#> Type: variables
#> ID: exploredata-ZA6805_Varkp4_1290
#> Title: kp4_1290 - Klimaschutz, Ego
#> Date: 2019
#> # ℹ 17 more records
#> # ℹ Use `print(n = ...)` to see more records
if (FALSE) gesis_search("climate change", pages = NULL) # all pages

# By default, results are wrapped in a complex list structure. This is
# good for representing detailed information, but not for analyzing data.
# Results can be tidied up to a dataframe using either `as_tibble()`
# or by setting the `tidy` argument to TRUE
tibble::as_tibble(record)
#> # A tibble: 10 × 83
#>    id             title type  date  title_en study_id study_title study_title_en
#>    <chr>          <chr> <chr> <chr> <chr>    <chr>    <chr>       <chr>         
#>  1 exploredata-Z… vg1.… vari… 2016  vg1.14 … ZA5978   Youth Stud… Youth Study M…
#>  2 exploredata-Z… q72 … vari… 2019  q72 - S… ZA5700   Vorwahl-Qu… Pre-election …
#>  3 exploredata-Z… V195… vari… 2003  V195 - … ZA3849   Politbarom… Politbaromete…
#>  4 exploredata-Z… kpa1… vari… 2019  kpa1_12… ZA6804   Wahlkampf-… Short-term Ca…
#>  5 exploredata-Z… V893… vari… 2013  V893 - … ZA4612   German Gen… German Genera…
#>  6 exploredata-Z… G113… vari… 2016  G113 - … ZA5976   Youth in a… Youth in a Ti…
#>  7 exploredata-Z… vn72… vari… 2019  vn72 - … ZA5702   Vor- und N… Pre- and Post…
#>  8 exploredata-Z… kp2_… vari… 2019  kp2_129… ZA6804   Wahlkampf-… Short-term Ca…
#>  9 exploredata-Z… kp4_… vari… 2019  kp4_130… ZA6804   Wahlkampf-… Short-term Ca…
#> 10 exploredata-Z… kp8_… vari… 2019  kp8_129… ZA6804   Wahlkampf-… Short-term Ca…
#> # ℹ 75 more variables: variable_label <chr>, variable_label_en <chr>,
#> #   variable_name <chr>, variable_name_sorting <chr>, variable_code_list <chr>,
#> #   variable_interview_instructions_en <chr>, study_id_title <chr>,
#> #   study_id_title_en <chr>, date_recency <int>,
#> #   time_collection_max_year <int>, time_collection_min_year <int>,
#> #   time_collection_years <chr>, countries_collection <list>,
#> #   methodology_collection_ddi <list>, selection_method_ddi <list>, …
gesis_search("climate change", tidy = TRUE)
#> # A tibble: 10 × 83
#>    id             title type  date  title_en study_id study_title study_title_en
#>    <chr>          <chr> <chr> <chr> <chr>    <chr>    <chr>       <chr>         
#>  1 exploredata-Z… vg1.… vari… 2016  vg1.14 … ZA5978   Youth Stud… Youth Study M…
#>  2 exploredata-Z… q72 … vari… 2019  q72 - S… ZA5700   Vorwahl-Qu… Pre-election …
#>  3 exploredata-Z… V195… vari… 2003  V195 - … ZA3849   Politbarom… Politbaromete…
#>  4 exploredata-Z… kpa1… vari… 2019  kpa1_12… ZA6804   Wahlkampf-… Short-term Ca…
#>  5 exploredata-Z… V893… vari… 2013  V893 - … ZA4612   German Gen… German Genera…
#>  6 exploredata-Z… G113… vari… 2016  G113 - … ZA5976   Youth in a… Youth in a Ti…
#>  7 exploredata-Z… vn72… vari… 2019  vn72 - … ZA5702   Vor- und N… Pre- and Post…
#>  8 exploredata-Z… kp2_… vari… 2019  kp2_129… ZA6804   Wahlkampf-… Short-term Ca…
#>  9 exploredata-Z… kp4_… vari… 2019  kp4_130… ZA6804   Wahlkampf-… Short-term Ca…
#> 10 exploredata-Z… kp8_… vari… 2019  kp8_129… ZA6804   Wahlkampf-… Short-term Ca…
#> # ℹ 75 more variables: variable_label <chr>, variable_label_en <chr>,
#> #   variable_name <chr>, variable_name_sorting <chr>, variable_code_list <chr>,
#> #   variable_interview_instructions_en <chr>, study_id_title <chr>,
#> #   study_id_title_en <chr>, date_recency <int>,
#> #   time_collection_max_year <int>, time_collection_min_year <int>,
#> #   time_collection_years <chr>, countries_collection <list>,
#> #   methodology_collection_ddi <list>, selection_method_ddi <list>, …

# Using the fields argument you can control how different text fields
# are weighted in matching the query string.
# Search for "climate change" only in texts, not in other fields
gesis_search("climate change", fields = field_weights(
  full_text = 10,
  abstract_en = 5,
  abstract = 3
))
#> A list of <gesis_records> with 10 records
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-22412
#> Title: Does tomorrow ever come? Disaster narrative and public perceptions of
#> climate change
#> Date: 2006
#> Persons:
#> • Lowe, Thomas
#> • Brown, Katrina
#> • Dessai, Suraje
#> • ... and 3 more
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-43950
#> Title: Can affluence explain public attitudes towards climate change mitigation
#> policies? A multilevel analysis with data from 27 EU countries
#> Date: 2014
#> Person:
#> • Sasko, David
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-36454
#> Title: Modifying the 2° C target: climate policy objectives in the contested
#> terrain of scientific policy advice, political preferences, and rising
#> emissions
#> Date: 2013
#> Person:
#> • Geden, Oliver
#> # ℹ 7 more records
#> # ℹ Use `print(n = ...)` to see more records

# Search for articles in a specified journal
gesis_search("urban planning", fields = field_weights(coreJournalTitle = 10))
#> A list of <gesis_records> with 10 records
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-70580
#> Title: Built environment, ethics and everyday life
#> Date: 2020
#> Persons:
#> • Kärrholm, Mattias
#> • Kopljar, Sandra
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-71915
#> Title: City Planning and Green Infrastructure: Embedding Ecology into Urban
#> Decision-Making (Editorial)
#> Date: 2021
#> Persons:
#> • Osmond, Paul
#> • Wilkinson, Sara
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-72488
#> Title: The Hybrid Space of Collaborative Location-Based Mobile Games and the
#> City: A Case Study of Ingress
#> Date: 2020
#> Persons:
#> • Sengupta, Ulysses
#> • Tantoush, Mahmud
#> • Bassanino, May
#> • ... and 1 more
#> # ℹ 7 more records
#> # ℹ Use `print(n = ...)` to see more records

# Search strings are separated by an AND operator by default
# this default can be overwritten by setting default_operator = "OR"
# or by manually separating the query string
weight <- field_weights(title = 100)
and <- gesis_search(
  "climate change",
  sort = "title_ascending",
  fields = weight
)
or1 <- gesis_search(
  "climate OR change",
  sort = "title_ascending",
  fields = weight
)
or2 <- gesis_search(
  "climate change",
  sort = "title_ascending",
  default_operator = "OR",
  fields = weight
)
attr(and, "query") <- NULL
attr(or1, "query") <- NULL
attr(or2, "query") <- NULL
identical(and, or1)
#> [1] FALSE
identical(or1, or2)
#> [1] TRUE

# Similarly, you can construct complex query terms using operators
gesis_search("(climate or environmental) AND (change OR crisis OR action)")
#> A list of <gesis_records> with 10 records
#> <gesis_record>
#> Type: variables
#> ID: exploredata-ZA6289_Varbc5_4
#> Title: bc5_4 - environmental info lack: climate change
#> Date: 2016
#> 
#> <gesis_record>
#> Type: variables
#> ID: exploredata-ZA6289_Varbc4_4
#> Title: bc4_4 - environmental worries: climate change
#> Date: 2016
#> 
#> <gesis_record>
#> Type: publication
#> ID: gesis-ssoar-95723
#> Title: Environmental awareness: The case of climate change
#> Date: 2018
#> Persons:
#> • Weber, Shlomo
#> • Wiesmeth, Hans
#> # ℹ 7 more records
#> # ℹ Use `print(n = ...)` to see more records

# Another way to narrow down the search is to set filters. GESIS Search
# offers a number of filters, including topic, publication year or
# methodology. Sensible values can be checked on https://search.gesis.org/.
gesis_search(topics = "climate change", type = "publication")
#> A list of <gesis_records> with 0 records