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Surface Groups Costa Rica 1984-2023
No full textSurface groups for Costa Rica (years 1984 - 2023) as georeferenced TIF files.
Classified land cover (surface) of each pixel indicated as:
0 = built-up surfaces: surfaces with buildings of non-natural materials such as concrete, metal, and glass (e.g., residential buildings, industrial plants, roads)
1 = grassy surfaces: surfaces covered by grass or other plants with similar surface reflectance (e.g., natural grassland, city parks)
2 = surfaces with crop fields: surfaces with vegetation for agricultural purposes (e.g., hayfields, vineyards)
3 = forest-covered surfaces: surfaces covered by trees or other plants with similar surface reflectance (e.g., mixed forests, moors)
4 = surfaces without vegetation: surfaces with (almost) no vegetation or buildings (e.g., bare rock, sand plains)
5 = water surfaces: any type of water surface (e.g., rivers, lakes)
9 = missing surface classification, most likely due to cloud cover
If a TIF file for a given year within the observation period is missing, no valid satellite imagery was available for that year (e.g., due to constant cloud cover)
Spontaneous encoding of event roles in hominids_Supplementary Information
No full textIn this file you will find:
- a README document
- the data set necessary to the analyses
- the analyses (script & Data files
Surface Groups Guyana 1984-2023
No full textSurface groups for Guyana (years 1984 - 2023) as georeferenced TIF files.
Classified land cover (surface) of each pixel indicated as:
0 = built-up surfaces: surfaces with buildings of non-natural materials such as concrete, metal, and glass (e.g., residential buildings, industrial plants, roads)
1 = grassy surfaces: surfaces covered by grass or other plants with similar surface reflectance (e.g., natural grassland, city parks)
2 = surfaces with crop fields: surfaces with vegetation for agricultural purposes (e.g., hayfields, vineyards)
3 = forest-covered surfaces: surfaces covered by trees or other plants with similar surface reflectance (e.g., mixed forests, moors)
4 = surfaces without vegetation: surfaces with (almost) no vegetation or buildings (e.g., bare rock, sand plains)
5 = water surfaces: any type of water surface (e.g., rivers, lakes)
9 = missing surface classification, most likely due to cloud cover
If a TIF file for a given year within the observation period is missing, no valid satellite imagery was available for that year (e.g., due to constant cloud cover)
DDS21, Cross Sectional Survey Wave 2: Popular Vote on 03.03.2024
No full textThe dataset contains the anonymised results of a cross-sectional survey of eligible voters conducted following a popular vote on 03 March 2024. The vote concerned two subjects:
- The poular initiative "For a better life in old age" ("Initiative for a 13th AHV pension"; FSO proposal no. 665, "vote1" in the data set)
- The popular initiative "In favour of a secure and sustainable pension scheme" ("Pension initiative"; FSO proposal no. 666, "vote2" in the data set)
Topics covered in the survey include voting decisions, arguments concerning the referenda, political knowledge, values, and beliefs, media consumption, and a survey experiment on political advertisements.
Data is provided in SAV, RDS, and CSV formats. SAV is the primary target format, and researchers are advised to use this version where possible. The SAV file contains user-defined missing variable levels. Users working in an R programming environment may wish to ensure that their chosen method of data import does not simply coerce these to simple "NA"s.
Due to anonymity reasons, some variables are not included in the downloadable dataset, or provided with a reduced level of precision. This concerns:
- The place of residence at the municipality level (omitted)
- Client device metadata (omitted; a separate variable indicating whether the survey was filled out on a mobile or a desktop platform is included)
- Variables related to respondents' current or previous occupation (plain text answers omitted; ISCO-08-coded variables have their precision reduced from the unit group level to the major group level)
- Variables related to respondents' country of birth, as well as the countries of birth of their parents (reduced to a dummy variable indicating whether or not the country of birth is Switzerland)
We additionally omit variables solely collected for internal purposes of the DDS21 project; this concerns items measuring satisfaction with the survey, as well as free-form comments about the survey.
These variables are only available on request and with prior consent of the authors. Please send an e-mail with your justified request to [email protected]. The DDS21 project was approved by the Ethics Committee of the University Zurich (UZH PhF Ethics Committee, number 23.05.04)
NutzerInnen-Befragung in Einrichtungen der Obdachlosenhilfe in 8 Städten der Schweiz - 2020 und 2021 (OBDACH)
No full textDer Datensatz enthält die Daten aus der quantitativen Face-to-Face-Befragung von Menschen ab 18 Jahren in 8 Städten der Schweiz, die sich zum Zeitraum der Befragung in 62 Einrichtungen für Menschen ohne eine Wohnung aufhielten und gemäss Definition (FEANTSA, ETHOS) zum Zeitpunkt der Befragung als obdachlos gelten (nach den ETHOS-Kategorien 1 und 2). Die Befragungen wurden in einer Erhebungswoche im Dezember 2020 und im März 2021 durchgeführt
RuptDuPuits
No full textRuptDuPuits is part of the KarstConduitCatalogue, a dataset encompassing a wide spectrum of hydrologically active cave conduit geometries. High resolution geometric data of cave wall models were acquired by terrestrial and mobile laserscanning methods. Hydrologists may find this dataset suitable for the analysis of key geometric characteristics shaped by typical cave conduits, including along-conduit distributions of aperture and roughness elements
CHILL: Questionnaire Dataset (m-Path app)
No full textThis dataset comprises all questionnaire data gathered during the CHILL m-Path app phase, including every ESM assessment and all daily and weekly questionnaires administered across the baseline, intervention, and monitoring periods. This dataset does NOT include the intervention data and the mobile sensing data
Q-Guide: example for a thesis (DOC ONLY)
No full textExample of the application of the Q-Guide to a student thesis
Metrical, morphosyntactic, and syntactic analysis of the Rigveda
No full textThe dataset contains:
• the main data table, RV_data.csv, with morphosyntactic, syntactic and metrical information on each Rigvedic word form, and
• a script, disticha.rmd, for the analysis of disticha in the main types of Rigvedic stanzas which were studied as an example for the application of the data table, resulting in the published article:
Salvatore Scarlata and Paul Widmer, Syntactic evidence for metrical structure in Rigvedic stanzas, Indo-European Linguistics 13 (2025), 1-21, doi:10.1163/22125892-bja10041, issn: 2212-5892.
In addition the dataset contains:
• a further data table, RV-polylex.csv, wherein all compounded word forms are analyzed, and
• some ancillary basic scripts for linking the two tables respectively for simplified representations: join.r resp. pivot01–03.r.
Finally, the dataset contains:
• a data table, RV-polylexREJECTS.csv, containing words for which it was not possible to assess them as compounde
KarstConduitCatalogue
No full textKarstConduitCatalogue is a dataset encompassing a wide spectrum of hydrologically active cave conduit geometries. High resolution geometric data of cave wall models were acquired by terrestrial and mobile laserscanning methods. Hydrologists may find this dataset suitable for the analysis of key geometric characteristics shaped by typical cave conduits, including along-conduit distributions of aperture and roughness elements