Database delivered

The Student Survey Database

The database, named “Student Survey”, is archived in Nakala warehouse (IR* HumaNum) :

IMAGEUN - Student Survey

The entire database and associated metadata are available in a downloadable archive. The database is structured in two files:

• A respondents file containing all the variables from the survey
• A geometries file containing the geometries of the regions drawn by the respondents

List of Files

The archive made available on NAKALA contains the following files:

• survey.csv: All the survey data, except for the mental map questions
• geometries.gpkg: Geographic layer of the regions drawn (and their associated words)
• survey_dictionnary_metadata.ods: Dictionary of variables from the survey.csv file
• geom_dictionnary_metadata.ods: Dictionary of variables in the geometries.gpkg file

The three data formats used for this database are:

• Comma Separated Values (.csv): Format of the main database file
• Geopackage (.gpkg): Storage format for the regions drawn by the respondents. This format, defined by the Open Geospatial Consortium standard, is open, interoperable and widely used
• ODS: Format of the two dictionaries of variables of the database

Join Key

The respondents file (survey.csv) is structured in a standard way, where each line corresponds to a respondent. In the geometries file (geometries.gpkg), each line corresponds to a polygon (drawn region) associated with a word (e.g. “Europe”). The regions drawn by a respondent are thus stored in several lines. There can be up to five regions drawn by a respondent.

In order to build a single table containing all the data from the survey, it is necessary to join the two files provided. The join field to be used to link these two tables is the unique respondent identifier, coded as follows: X0001_met_respID_aut.

survey.csv

The survey.csv file contains a table with 2,030 rows (number of respondents) and 102 columns (number of descriptive variables).

Statistical Summary

Variable	Type	n_missing	complete_rate	character.min	character.max	character.empty	character.n_unique	character.whitespace	factor.ordered	factor.n_unique	factor.top_counts
A0101_cad_langua	character	0	1.0	2	2	0	5	0	NA	NA	NA
A0302_cad_medium_lab_en	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	5	On : 1189, On : 762, On : 72, On : 6
A0303_cad_enviro_lab_en	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	5	Alo: 1881, Wit: 70, Wit: 38, In : 28
A0405_cad_univer_lab	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	54	Erl: 288, Fra: 257, Par: 169, Ant: 138
A0405_cad_univer_lab_city	character	0	1.0	4	17	0	18	0	NA	NA	NA
A0405_cad_univer_lab_country	character	0	1.0	6	19	0	6	0	NA	NA	NA
A0406_cad_fields_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	8	Soc: 510, Art: 502, Bus: 371, Nat: 260
A0407_cad_levels_lab_en	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	5	Bac: 907, A-l: 623, Mas: 418, PhD: 46
A0508_cad_gender_lab_en	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	4	Fem: 1253, Mal: 722, Oth: 30, Pre: 24
A0609_cad_birthc_lab_en	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	68	Fra: 693, Ger: 549, Tur: 229, Tun: 156
A0609_cad_birthc_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	68	FRA: 693, DEU: 549, TUR: 229, TUN: 156
A0610_cad_birthy_lab	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	52	200: 386, 200: 341, 199: 283, 200: 183
A0611_cad_iddoc1_lab_en	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	50	Fra: 689, Ger: 561, Tur: 225, Tun: 156
A0611_cad_iddoc1_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	50	FRA: 689, DEU: 561, TUR: 225, TUN: 156
A0612_cad_iddoc2_lab_en	factor	1674	0.2	NA	NA	NA	NA	NA	TRUE	66	Fra: 47, Tur: 44, Tun: 42, Pre: 42
A0612_cad_iddoc2_lab_rec	factor	1674	0.2	NA	NA	NA	NA	NA	TRUE	66	FRA: 47, TUR: 44, TUN: 42, nsp: 42
A0613_cad_belong_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	89	___: 1863, ___: 17, ___: 16, ___: 12
B0701_lan_langu5_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	82	FRA: 715, DEU: 458, TUR: 216, ARA: 73
B0701_lan_otlan5_lab_rec	factor	1909	0.1	NA	NA	NA	NA	NA	TRUE	65	POL: 14, CZE: 5, NUL: 5, DUT: 5
B0702_lan_dailan_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	112	FRA: 478, DEU: 279, DEU: 199, TUR: 184
B0702_lan_otdail_lab_rec	factor	1931	0.0	NA	NA	NA	NA	NA	TRUE	53	POL: 10, ALB: 5, NUL: 5, GCF: 4
C0901_mob_living_lab_en	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	3	No: 1452, Yes: 571, Pre: 6
C1002_mob_livfam_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	130	___: 1801, USA: 16, FRA: 16, DEU: 9
C1002_mob_livoth_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	66	___: 1944, USA: 6, FRA: 4, CAN: 3
C1002_mob_livpro_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	68	___: 1917, AUS: 11, FRA: 7, NZL: 7
C1002_mob_livstu_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	135	___: 1699, FRA: 44, ESP: 21, CAN: 19
C1103_mob_travel_lab_en	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	3	Yes: 1727, No: 295, Pre: 7
C1204_mob_trlist_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	1576	___: 321, FRA: 22, DEU: 12, GBR: 7
D1301_mob_living_lab_en	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	3	Yes: 1557, No: 417, Pre: 55
D1402_mob_livpro_lab_rec	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	927	___: 675, CAN: 63, FRA: 47, USA: 36
D1402_mob_livstu_lab_rec	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	913	___: 673, FRA: 51, CAN: 45, ESP: 34
D1503_mob_travel_lab_en	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	3	Yes: 1972, No: 43, Pre: 14
D1604_mob_trlist_lab_rec	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	1798	___: 112, USA: 10, FRA: 9, TUR: 9
E1801_map_cresid_lab_en	factor	1	1.0	NA	NA	NA	NA	NA	TRUE	6	Fra: 724, Ger: 587, Tur: 235, Fra: 222
F2101_med_topics_lab_en	factor	82	1.0	NA	NA	NA	NA	NA	TRUE	1198	art: 22, nsp: 15, pol: 15, art: 15
F2202_med_intern_lab_en	factor	92	1.0	NA	NA	NA	NA	NA	TRUE	8	Ver: 446, Hig: 445, Fai: 353, Pre: 254
F2202_med_locale_lab_en	factor	91	1.0	NA	NA	NA	NA	NA	TRUE	8	Fai: 319, Hig: 315, Fai: 300, Med: 297
F2202_med_nation_lab_en	factor	92	1.0	NA	NA	NA	NA	NA	TRUE	8	Hig: 508, Ver: 420, Fai: 335, Med: 259
F2303_med_medias_lab_en	factor	96	1.0	NA	NA	NA	NA	NA	TRUE	147	soc: 189, onl: 154, tel: 129, tel: 95
F2304_med_langue_lab_rec	factor	152	0.9	NA	NA	NA	NA	NA	TRUE	115	ENG: 432, DEU: 343, FRA: 263, ENG: 94
F2304_med_lanoth_lab_rec	factor	1975	0.0	NA	NA	NA	NA	NA	TRUE	28	POL: 7, JPN: 5, ALB: 3, KOR: 3
G2501_cul_lgsort_lab_en	factor	98	1.0	NA	NA	NA	NA	NA	TRUE	3	Yes: 1729, No: 199, Pre: 4
G2602_cul_lgview_lab_rec	factor	299	0.9	NA	NA	NA	NA	NA	TRUE	203	ENG: 418, DEU: 228, ENG: 186, ENG: 68
G2602_cul_otview_lab_rec	factor	1721	0.2	NA	NA	NA	NA	NA	TRUE	75	JPN: 91, KOR: 77, JPN: 13, KOR: 11
G2603_cul_lgread_lab_rec	factor	416	0.8	NA	NA	NA	NA	NA	TRUE	96	ENG: 319, DEU: 275, ENG: 264, FRA: 183
G2603_cul_otread_lab_rec	factor	1971	0.0	NA	NA	NA	NA	NA	TRUE	22	JPN: 14, POL: 8, KOR: 6, SWE: 6
G2704_cul_orsort_lab_en	factor	105	0.9	NA	NA	NA	NA	NA	TRUE	3	Yes: 1744, No: 133, Pre: 48
G2805_cul_orread_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	719	___: 818, USA: 105, FRA: 29, JPN: 24
G2805_cul_orview_lab_rec	factor	0	1.0	NA	NA	NA	NA	NA	TRUE	841	___: 530, USA: 191, USA: 35, USA: 33
H3001_eur_words1_lab_en	factor	747	0.6	NA	NA	NA	NA	NA	TRUE	143	eur: 152, con: 148, uni: 134, uni: 53
H3001_eur_words1_lab_fr	character	766	0.6	3	29	0	136	0	NA	NA	NA
H3001_eur_words1_lab_rec	factor	206	0.9	NA	NA	NA	NA	NA	TRUE	649	uni: 133, con: 109, uni: 84, eur: 50
H3001_eur_words2_lab_en	factor	1031	0.5	NA	NA	NA	NA	NA	TRUE	140	con: 70, eur: 65, fre: 53, eur: 50
H3001_eur_words2_lab_fr	character	1054	0.5	3	43	0	133	0	NA	NA	NA
H3001_eur_words2_lab_rec	factor	295	0.9	NA	NA	NA	NA	NA	TRUE	813	con: 53, eur: 49, uni: 36, uni: 32
H3001_eur_words3_lab_en	factor	1267	0.4	NA	NA	NA	NA	NA	TRUE	130	eur: 45, cul: 38, fre: 35, eur: 29
H3001_eur_words3_lab_fr	character	1295	0.4	3	43	0	123	0	NA	NA	NA
H3001_eur_words3_lab_rec	factor	502	0.8	NA	NA	NA	NA	NA	TRUE	812	eur: 45, sup: 42, لا : 28, cul: 23
H3102_eur_images_lab_en	factor	138	0.9	NA	NA	NA	NA	NA	TRUE	6	Qui: 888, Neu: 490, Ver: 266, Qui: 179
I3301_cad_educp1_lab_en	factor	145	0.9	NA	NA	NA	NA	NA	TRUE	10	Gra: 401, Sec: 380, Hig: 329, Hig: 242
I3302_cad_educp2_lab_en	factor	145	0.9	NA	NA	NA	NA	NA	TRUE	10	Sec: 379, Gra: 367, Hig: 303, Hig: 216
I3403_cad_paysp1_lab_en	factor	154	0.9	NA	NA	NA	NA	NA	TRUE	86	Fra: 567, Ger: 459, Tur: 213, Tun: 133
I3403_cad_paysp1_lab_rec	factor	154	0.9	NA	NA	NA	NA	NA	TRUE	86	FRA: 567, DEU: 459, TUR: 213, TUN: 133
I3404_cad_paysp2_lab_en	factor	154	0.9	NA	NA	NA	NA	NA	TRUE	82	Fra: 545, Ger: 460, Tur: 210, Tun: 141
I3404_cad_paysp2_lab_rec	factor	154	0.9	NA	NA	NA	NA	NA	TRUE	82	FRA: 545, DEU: 460, TUR: 210, TUN: 141
K3601_met_submit_aut	character	175	0.9	7	7	0	8	0	NA	NA	NA
X0001_met_respID_aut	character	0	1.0	12	12	0	2030	0	NA	NA	NA
X0004_met_firact_aut	character	0	1.0	7	7	0	8	0	NA	NA	NA

Dictionary of Variables

The survey_dictionnary_metadata.ods file defines and presents all the variables stored in the survey.csv file.

Dictionnaire des variables de la base de données des répondant·es

CODENAME	Variable_name_or_question	Code_quest	Code_thema	Letter_thema	Page_of_questionnaire	Num_question_thema	Question_ID	Input_mode	Data_type	Value_type	Built_after_collect
X0001_met_respID_aut	Respondent ID	X0001	metadt	X	00	01	respID	automatic	STRING	automatically generated by Maptionnaire tool	NO
X0004_met_firact_aut	First Active	X0004	metadt	X	00	04	firact	automatic	TIME	automatically generated by Maptionnaire tool	NO
A0101_cad_langua	Language chosen	A0101	cadrag	A	01	01	langua	Drop-down list	STRING	code ISO 639-1	NO
A0302_cad_medium_lab_en	What technical medium are you using to complete this questionnaire?...7	A0302	cadrag	A	03	02	medium	Drop-down list	STRING	modalities in english	NO
A0303_cad_enviro_lab_en	Please describe the situational context in which you are completing this questionnaire:	A0303	cadrag	A	03	03	enviro	Drop-down list	STRING	modalities in english	NO
A0405_cad_univer_lab_city	City of university	A0405	cadrag	A	04	05	univer	Drop-down list	STRING	modalities in english	YES
A0405_cad_univer_lab_country	Country of university	A0405	cadrag	A	04	05	univer	Drop-down list	STRING	modalities in english	YES
A0406_cad_fields_lab_rec	What is your principal field of study?	A0406	cadrag	A	04	06	fields	Unique choice	STRING	modalities in english	NO
A0407_cad_levels_lab_en	What is your current level of academic studies?	A0407	cadrag	A	04	07	levels	Drop-down list	STRING	modalities in english	NO
A0508_cad_gender_lab_en	You are:	A0508	cadrag	A	05	08	gender	Unique choice	STRING	modalities in english	NO
A0609_cad_birthc_lab_rec	What is your country of birth? Recoded for pseudonymization	A0609	cadrag	A	06	09	birthc	Recoding	BOOLEAN	true/false	YES
A0610_cad_age_rec	Recoded age categories for pseudonymization	A0610	cadrag	A	06	10	birthy	Recoding	STRING	age category	YES
A0611_cad_iddoc1_lab_rec	From what country(ies) do you hold ID documents ? Country 1:	A0611	cadrag	A	06	11	iddoc1	Recoding	BOOLEAN	true/false	YES
A0612_cad_iddoc2_lab_rec	From what country(ies) do you hold ID documents ? Country 2:	A0612	cadrag	A	06	12	iddoc2	Recoding	BOOLEAN	true/false	YES
A0613_cad_belong_lab_rec	Do you have another sense of national belonging? If so, please specify:	A0613	cadrag	A	06	13	belong	Recoding	BOOLEAN	true/false	YES
B0701_lan_langu5_lab_rec	What language(s) did you speak before you were 5 years old?	B0701	langue	B	07	01	langu5	Multiple choices recoded	STRING	modalities based on langage code ISO 639-1	YES
B0701_lan_otlan5_lab_rec	What language(s) did you speak before you were 5 years old?	B0701	langue	B	07	01	otlan5	Open field recoded	STRING	modalities based on langage code ISO 639-1	YES
B0702_lan_dailan_lab_rec	Which of these languages ​​do you speak on a daily basis?	|B0702	|langue	|B	|07	|02	|dailan	|Multiple choices recode	|STRING	|modalities based on langage code ISO 639-1	|YES
B0702_lan_otdail_lab_rec	Which of these languages ​​do you speak on a daily basis?	|B0702	|langue	|B	|07	|02	|otdail	|Open field recoded	|STRING	|modalities based on langage code ISO 639-1	|YES
C0901_mob_living_lab_en	Have you ever lived in a country other than the one you currently live (for more than 4 months)?	C0901	mobiok	C	09	01	living	Unique choice	STRING	modalities in english	NO
C1002_mob_livfam_lab_rec	If for family reasons (C0901_mob_living_lab_en), specify in which country(ies):	C1002	mobiok	C	10	02	livfam	Open field recoded	STRING	modalities based on country code ISO 3166	YES
C1002_mob_livstu_lab_rec	If for studies (C0901_mob_living_lab_en), specify in which country(ies):	C1002	mobiok	C	10	02	livstu	Open field recoded	STRING	modalities based on country code ISO 3166	YES
C1002_mob_livpro_lab_rec	If for professional reasons (C0901_mob_living_lab_en), specify in which country(ies):	C1002	mobiok	C	10	02	livpro	Open field recoded	STRING	modalities based on country code ISO 3166	YES
C1002_mob_livoth_lab_rec	If for others reasons (C0901_mob_living_lab_en), specify in which country(ies):	C1002	mobiok	C	10	02	livoth	Open field recoded	STRING	modalities based on country code ISO 3166	YES
C1103_mob_travel_lab_en	Have you travelled to a country other than the one you currently live (and stayed there for more than 3 days)?	C1103	mobiok	C	11	03	travel	Unique choice	STRING	modalities in english	NO
C1204_mob_trlist_lab_rec	If so (question « C1103_mob_travel_lab_en »), in which country(ies) ? (5 countries maximum)	C1204	mobiok	C	12	04	trlist	Open field recoded	STRING	modalities based on country code ISO 3166	YES
D1301_mob_living_lab_en	Would you like to live in a country (for a period of more than 4 months) other than the one in which you currently live?	D1301	mobimg	D	13	01	living	Unique choice	STRING	modalities in english	NO
D1402_mob_livpro_lab_rec	If so (question « D1301_mob_living_lab_en »), name the countries considered to work ? (5 countries maximum)	D1402	mobimg	D	14	02	livpro	Open field recoded	STRING	modalities based on country code ISO 3166	YES
D1402_mob_livstu_lab_rec	If so (question « D1301_mob_living_lab_en »), name the countries considered to study ? (5 countries maximum)	D1402	mobimg	D	14	02	livstu	Open field recoded	STRING	modalities based on country code ISO 3166	YES
D1503_mob_travel_lab_en	Would you like to visit a country (for a period of more than 3 days) other than the one in which you currently live?	D1503	mobimg	D	15	03	travel	Unique choice	STRING	modalities in english	NO
D1604_mob_trlist_lab_rec	If so (question « D1503_mob_travel_lab_en »), in which country(ies) ? (5 countries maximum)	D1604	mobimg	D	16	04	trlist	Open field recoded	STRING	modalities based on country code ISO 3166	YES
E1801_map_cresid_lab_en	Center the map on the country where you currently live:	E1801	maping	E	18	01	cresid	Unique choice	STRING	modalities in english	NO
F2101_med_topics_lab_en	Which of the following topics have you been interested in during the last week?	F2101	medias	F	21	01	topics	Multiple choices recoded	STRING	modalities in english	YES
F2202_med_intern_lab_en	Using the scales, indicate your interest in the international news	F2202	medias	F	22	02	intern	Unique choice	STRING	modalities in english	NO
F2202_med_locale_lab_en	Using the scales, indicate your interest in the local news	F2202	medias	F	22	02	locale	Unique choice	STRING	modalities in english	NO
F2202_med_nation_lab_en	Using the scales, indicate your interest in the national news	F2202	medias	F	22	02	nation	Unique choice	STRING	modalities in english	NO
F2303_med_medias_lab_en	What media have you used to stay informed over the last week?	F2303	medias	F	23	03	medias	Unique choice	STRING	modalities in english	NO
F2304_med_langue_lab_rec	Do you read the media in one or more of the following languages?	F2304	medias	F	23	04	langue	Multiple choices recoded	STRING	modalities based on langage code ISO 639-1	YES
F2304_med_lanoth_lab_rec	If « other » (question « F2304_med_langue_lab_rec »), specify your answer :	F2304	medias	F	23	04	lanoth	Open field recoded	STRING	modalities based on langage code ISO 639-1	YES
G2501_cul_lgsort_lab_en	During the last month, have you watched (film, series, video) or read any publication (book, comic, novel, etc	G2501	cultur	G	25	01	lgsort	Unique choice	STRING	modalities in english	NO
G2602_cul_lgview_lab_rec	In which language(s) have you watched films, series or videos?	G2602	cultur	G	26	02	lgview	Multiple choices recoded	STRING	modalities based on langage code ISO 639-1	YES
G2602_cul_otview_lab_rec	If « other » (question « G2602_cul_lgview_lab_rec »), specify your answer :	G2602	cultur	G	26	02	otview	Open field recoded	STRING	modalities based on langage code ISO 639-1	YES
G2603_cul_lgread_lab_rec	In what language(s) have you read (books, comics, novels, etc.)?	G2603	cultur	G	26	03	lgread	Multiple choices recoded	STRING	modalities based on langage code ISO 639-1	YES
G2603_cul_otread_lab_rec	If « other » (question « G2603_cul_lgread_lab_rec »), specify your answer :	G2603	cultur	G	26	03	otread	Open field recoded	STRING	modalities based on langage code ISO 639-1	YES
G2704_cul_orsort_lab_en	During the last month, have you watched (film, series, video) or read publications (book, comic, novel, etc) written or produced by a foreign author* ?	G2704	cultur	G	27	04	orsort	Unique choice	STRING	modalities in english	NO
G2805_cul_orread_lab_rec	From what country(ies) are the authors of the works you have read ? Origin(s) of books, comics, novels etc.:	G2805	cultur	G	28	05	orread	Open field recoded	STRING	modalities based on country code ISO 3166	YES
G2805_cul_orview_lab_rec	From what country(ies) are the authors of the works you have watched ? Origin(s) of films, series or videos authors :	G2805	cultur	G	28	05	orview	Open field recoded	STRING	modalities based on country code ISO 3166	YES
H3001_eur_words1_lab_rec	What words do you associate with 'Europe' (Word or expression n°1)	H3001	europe	H	30	01	words1	Open field recoded	STRING	modalities (recoded) in chosen language	YES
H3001_eur_words2_lab_rec	What words do you associate with 'Europe' (Word or expression n°2)	H3001	europe	H	30	01	words2	Open field recoded	STRING	modalities (recoded) in chosen language	YES
H3001_eur_words3_lab_rec	What words do you associate with 'Europe' (Word or expression n°3)	H3001	europe	H	30	01	words3	Open field recoded	STRING	modalities (recoded) in chosen language	YES
H3001_eur_words1_lab_en	What words do you associate with 'Europe' (Word or expression n°1)	H3001	europe	H	30	01	words1	Open field recoded	STRING	50 first modalities (recoded) in English	YES
H3001_eur_words2_lab_en	What words do you associate with 'Europe' (Word or expression n°2)	H3001	europe	H	30	01	words2	Open field recoded	STRING	50 first modalities (recoded) in English	YES
H3001_eur_words3_lab_en	What words do you associate with 'Europe' (Word or expression n°3)	H3001	europe	H	30	01	words3	Open field recoded	STRING	50 first modalities (recoded) in English	YES
H3001_eur_words3_lab_fr	What words do you associate with 'Europe' (Word or expression n°3)	H3001	europe	H	30	01	words3	Open field recoded	STRING	50 first modalities (recoded) in french	YES
H3001_eur_words1_lab_fr	What words do you associate with 'Europe' (Word or expression n°1)	H3001	europe	H	30	01	words1	Open field recoded	STRING	50 first modalities (recoded) in french	YES
H3001_eur_words2_lab_fr	What words do you associate with 'Europe' (Word or expression n°2)	H3001	europe	H	30	01	words2	Open field recoded	STRING	50 first modalities (recoded) in french	YES
H3102_eur_images_lab_en	In general, your view of the European Union (EU) is:	H3102	europe	H	31	02	images	Drop-down list	STRING	modalities in english	NO
I3301_cad_educp1_lab_en	What is the highest level of studies of your parent 1 (mother or guardian 1)?	I3301	cadrag	I	33	01	educp1	Drop-down list	STRING	modalities in english	NO
I3302_cad_educp2_lab_en	What is the highest level of studies of your parent 2 (father or guardian 2)?	I3302	cadrag	I	33	02	educp2	Drop-down list	STRING	modalities in english	NO
I3403_cad_paysp1_lab_rec	What is the country of birth of your parent 1 (mother or guardian 1)?	I3403	cadrag	I	34	03	paysp1	Recoding	BOOLEAN	true/false	YES
I3404_cad_paysp2_lab_rec	What is the country of birth of your parent 2 (father or guardian 2)?	I3404	cadrag	I	34	04	paysp2	Recoding	BOOLEAN	true/false	YES
K3601_met_submit_aut	Submitted	K3601	metadt	K	36	01	submit	automatic	TIME	automatically generated by Maptionnaire tool	NO

Exploration of Variables

Distribution of individuals by modality:

globColor = "#85c1d3"

bdr_dict = transpose(dataDict)
bdr_ojs = transpose(data)
<!-- Inputs.table(transpD) -->

varList = Object.keys(bdr_ojs[0])

viewof variables = Inputs.select(varList, {label: "Sélectionner la variable : "})

index = varList.indexOf(variables)

function dec(input, value) {
input
.value--;
if(input.value < 0){
input.value = 0
};
input.dispatchEvent(new Event("input", { bubbles: true })); // Native events bubble, so we should too
}


// function increasing avec limit au max de la liste
function inc(input, value) {
input.value++;
if(input.value >= varList.length){
input.value = varList.length - 1
};
input.dispatchEvent(new Event("input", { bubbles: true })); // Native events bubble, so we should too
}


// Les deux boutons inputs
MyInput = ({value = index} = {}) => {

const output = htl.html`<output>`;

const node = htl.html`<div>
<button onclick=${() => dec(node, value)}>Variable précedente</button>
<button onclick=${() => inc(node, value)}>Variable suivante</button>
</div>`;

// Update the display whenever the value changes
Object.defineProperty(node, "value", {
get() {
return value;
},
set(v) {
output.value = value = +v;
}
});

// Set the initial value
node.value = value;

return node;
}

viewof next = MyInput()

// Get full question from dictionnary
dictFilter = bdr_dict.filter(d => d.CODENAME == varList[next])
varQuestion = dictFilter[0].Variable_name_or_question

bdr_sub = bdr_ojs.map(row => row[`${varList[next]}`])
varUnique = [...new Set(bdr_sub.filter(value => value !== undefined))];
loopMax = {
  let maxChar = 0;
  for (let index = 0; index < varUnique.length; ++index) {
    const valeur = varUnique[index];
    maxChar = Math.max(maxChar, valeur.length);
    console.log("Longueur maximale des valeurs uniques :", maxChar);

  }
  return maxChar
}

Variable sélectionnée :
Question :

// Plot histogram
Plot.plot({
  width: 800,
  height: 400 + (loopMax*5),
  marginBottom: loopMax*5,
  x: {label: null, tickRotate: -90},
  <!-- x: {label: null}, -->
  y: {grid: true},
   marks: [
    Plot.barY(bdr_ojs, Plot.groupX(
      {
        y: "count",
        title: (elems) => `${elems.length} rows`,
        fill: (elems) => {
          const fillValue = elems[0][varList[next]] === "Prefer not to answer" ? "#cbd5d8" : globColor;
          return fillValue;
        }
      },
      { x: varList[next]}
    )),
    Plot.ruleY([0])
  ]
});

Figure 1: Variables de la base de données répondants

geometries.gpkg

The geometries.gpkg files is a table with 2744 rows (nb. of regions drawn) and 34 columns (nb. de descriptive variables).

Statistical Summary

Variable	Type	n_missing	complete_rate	logical.count
ID_geom	character	0	1.0	NA
X0001_met_respID_aut	character	0	1.0	NA
wkt	character	0	1.0	NA
geojson	character	0	1.0	NA
E1902_map_region	character	0	1.0	NA
E1903_map_rgname	character	276	0.9	NA
E1903_map_rgname_lab_rec	character	291	0.9	NA
E1903_map_rgname_lab_fr	character	291	0.9	NA
E1903_map_rgname_lab_en	character	291	0.9	NA
E1903_map_rgname_concept_fr	character	291	0.9	NA
E1903_map_rgname_concept_en	character	295	0.9	NA
E1903_map_rgname_scale	character	291	0.9	NA
E1903_map_rgname_type	character	291	0.9	NA
E1903_map_rgname_parent1_en	character	291	0.9	NA
E1903_map_rgname_parent2_en	character	2663	0.0	NA
E1903_map_rgname_parent3_en	character	2736	0.0	NA
typ_uni	logical	0	1.0	TRU: 1605, FAL: 1139
typ_mult_uni	logical	0	1.0	FAL: 2579, TRU: 165
typ_scale	logical	0	1.0	FAL: 2007, TRU: 737
typ_over	logical	0	1.0	FAL: 2640, TRU: 104
typ_dnk	logical	0	1.0	FAL: 2682, TRU: 62
typ_HS_del	logical	0	1.0	FAL: 2621, TRU: 123
typ_only_text	logical	0	1.0	FAL: 2705, TRU: 39
geom_carto	logical	0	1.0	TRU: 2517, FAL: 227
Index	numeric	0	1.0	NA
Zoom	numeric	0	1.0	NA
weight_geom	numeric	211	0.9	NA
weight_geom_tot	numeric	211	0.9	NA
weight_resp	numeric	211	0.9	NA
weight_resp_tot	numeric	211	0.9	NA
weight_scale	numeric	211	0.9	NA
weight_scale_tot	numeric	211	0.9	NA
area	numeric	0	1.0	NA

Dictionary of Variables

The geom_dictionnary_metadata.ods file defines and presents all the variables stored in the geometries.gpkgtable.

Characteristics of the Drawn Spaces

A. Number of polygons drawn per respondent

Figure 2: Number of regions drawn per respondent

B. Number of regions drawn by type

Figure 3: Number of regions drawn by type

WarningGeometries for cartography?

Some drawn regions with questionable geometry, such as scribbles or polygon closure problems, have not been removed from the database to avoid losing information, particularly concerning the word associated with the region

For this reason, not all polygons stored in the geometry database are specific to cartography. The “geom_carto” variable allows you to select only those geometries to be taken into account in cartographic representations.

You can select cartography-specific geometries as follows:

BDG_carto <- BDG_merged[BDG_merged$geom_carto == TRUE,]

C. Some examples of polygons, by type

The following map shows some of the possible cases resulting from the constructed typology.

BDGT = FileAttachment("data/geoms_typo_3857.geojson").json()

geo1 = require("geotoolbox@1")

leaflet = html`<link href='${resolve('leaflet@1.8.0/dist/leaflet.css')}' rel='stylesheet' />`

// sorting function

listRepT = [{ID: "7at2jdl924n7", type: "unique"},
            {ID: "4j38b97snf24", type: "multiple region"},
            {ID: "873oam9g67s8", type: "scale"},
            {ID: "4f23j8egj4m4", type: "intersected"},
            {ID: "9lc2hxp3gp3a", type: "combined 1"},
            {ID: "6mp8wro96yaa", type: "combined 2"},
            {ID: "7z27o9mnz3c3", type: "combined 3"}];

viewof typeT = Inputs.select(listRepT.map(d => d.type), {label: "Select respondent"})

repT = listRepT.find(obj => obj.type === typeT).ID

geomFilterT = geo1.filter(BDGT, (d) => d.X0001_met_respID_aut === repT);

geomArrT = geomFilterT.features.sort(function (b, a) {
    if (a.properties.area < b.properties.area)
        return -1;
    else if (a.properties.area > b.properties.area)
        return 1;
});

geomSelT = geo1.featurecollection(geomArrT);

dataT = geo1.remove({
  x: geomSelT,
  field: ["Zoom", "wkt", "geojson", "E1902_map_region"]});

Inputs.table(geo1.table(dataT));

{
  // Set highlight
function highlightFeature(e) {
    var layer = e.target;
    layer.setStyle({
        weight: 3,
        color: '#e0a6b3',
        dashArray: '',
        fillOpacity: 0.3
    });
}

  // Reset Highlight
  function resetHighlight(e) {
    layer.resetStyle(e.target);
}

  // Zoom on click + popUp
  function zoomToFeature(e) {
    map.fitBounds(e.target.getBounds());
}

  // OnEach featur
  function onEachFeature(feature, layer) {
    layer.bindPopup(function (Layer) {
    return Layer.feature.properties.ID_geom + '<br>' + 
    '"' + Layer.feature.properties.E1903_map_rgname_lab_rec + '"' + 
    '<br>' + 
    'trad. : "' + Layer.feature.properties.E1903_map_rgname_lab_fr + '"';
  })
    layer.on({
        mouseover: highlightFeature,
        mouseout: resetHighlight,
        click: zoomToFeature
    });
}

  // MAP
const container = yield htl.html`<div style="height: 500px;">`;
const map = L.map(container);
const layer = L.geoJSON(geomSelT, {
onEachFeature: onEachFeature,
  style: {
    fillOpacity: 0.3,
    color: globColor,
    weight: 2}
  }).addTo(map);

// fit map to geom bounds  
map.fitBounds(layer.getBounds(), {maxZoom: 9});
  
// Tile Layer  
L.tileLayer("https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",
    {attribution: '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors &copy; <a href="https://carto.com/attributions">CARTO</a>',
      subdomains: "abcd",
      maxZoom: 10
    }).addTo(map);
}

Explore Regions by Respondent

Here you can select a sub-corpus by country of response and then explore the geometries of each student in this sub-corpus.

Tip

Click on “Next respondent” to generate the map

BDG = FileAttachment("data/geoms_map_3857.geojson").json()

geo = require("geotoolbox@2")

// sorting function

listCountry = ["France Antilles", 
               "France Metropolitan", 
               "Germany",
               "Ireland",
               "Tunisia",
               "Turkey"];

viewof country = Inputs.select(listCountry, {label: "Select country"})

geomFilter = geo.filter(BDG, (d) => d.A0405_cad_univer_lab_country === country)

respList = geomFilter.features.map(d => d.properties.X0001_met_respID_aut)

respListUnique = [...new Set(respList.filter(value => value !== undefined))]

viewof textResp = Inputs.text({label: "id répondant·e", placeholder: "idresp", submit: true})

respIndex = respList.indexOf(textResp)

<!-- md` \ *Cliquez sur "Répondant·e suivant·e" pour générer la première carte* \ ` -->

viewof nextResp = Inputs.button([
  ["Répondant précedent", value => value - 1],
  ["Répondant suivant", value => value + 1],
  ["Reset", value => 0]
], {value: respIndex, label: ""})

respo = respList[nextResp]

geomSel = geo.filter(geomFilter, (d) => d.X0001_met_respID_aut  === respo)

geomSort = geomSel.features.sort(function (b, a) {
    if (a.properties.area < b.properties.area)
        return -1;
    else if (a.properties.area > b.properties.area)
        return 1;
});

geomFinal = geo.featurecollection(geomSort)

data1 = geo.properties.remove({
  x: geomFinal,
  field: ["Zoom", "wkt", "geojson", "E1902_map_region"]});

Inputs.table(geo.properties.table(data1));

{
  // Set highlight
function highlightFeature(e) {
    var layer = e.target;
    layer.setStyle({
        weight: 3,
        color: '#e0a6b3',
        dashArray: '',
        fillOpacity: 0.3
    });
}

  // Reset Highlight
  function resetHighlight(e) {
    layer.resetStyle(e.target);
}

  // Zoom on click + popUp
  function zoomToFeature(e) {
    map.fitBounds(e.target.getBounds());
}

  // OnEach feature
  function onEachFeature(feature, layer) {
    layer.bindPopup(function (Layer) {
    return Layer.feature.properties.X0001_met_respID_aut + 
    ' - "' + Layer.feature.properties.ID_geom + '" <br>' + 
    '<strong> name : </strong> "' + Layer.feature.properties.E1903_map_rgname_lab_rec + '" <br>' + 
    '<strong>trad. : </strong> "' + Layer.feature.properties.E1903_map_rgname_lab_fr + '"';
  })
    layer.on({
        mouseover: highlightFeature,
        mouseout: resetHighlight,
        click: zoomToFeature
    });
}

  // MAP
const container = yield htl.html`<div style="height: 500px;">`;
const map = L.map(container);
const layer = L.geoJSON(geomSort, {
onEachFeature: onEachFeature,
  style: {
    fillOpacity: 0.3,
    color: globColor,
    weight: 2}
  }).addTo(map);
  
// Change projection
//L.Projection.SphericalMercator;  
//L.CRS.EPSG4326    
// fit map to geom bounds  
map.fitBounds(layer.getBounds(), {maxZoom: 9});
  
// Tile Layer  
L.tileLayer("https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png",
    {attribution: '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors &copy; <a href="https://carto.com/attributions">CARTO</a>',
      subdomains: "abcd",
      maxZoom: 10
    }).addTo(map);
  
}

Precautions for Use

The data in this survey is the result of a large-scale, unsupervised survey. For this reason, the sample of respondents is not representative of the studied population. The sample has not been rebalanced, and no weighting of individuals is proposed in this database. Care should be taken when comparing sub-groups of respondents (by gender, country of study, discipline, etc.), as the number of individuals in sub-groups may be unbalanced.

Before re-using the database, please refer to the Accessibility and Confidentiality section.