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Surface Groups Liberia 1984-2021
No full textSurface groups for Liberia (years 1984 - 2021) 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)
DISINTEGRATION: Tracking Europeans' opinions of Brexit and the EU: An EU-wide, six wave cross-sectional survey, 2017–2019
No full textBrexit marked a turning point in EU history. For the first time an EU member state left the EU, leading to concerns about the stability of the EU as a whole. Indeed, Brexit carried significant spillover effects in the other EU member states, both in terms of the loss of cooperation gains that disintegration entails, and for the risks of political contagion. To understand whether and how such spillover effects materialized during the Brexit withdrawal negotiations, we repeatedly fielded an EU-wide, six-wave cross-sectional survey in 6-month intervals between July 2017 and December 2019.
The survey includes information on public opinion across 28 EU Member States including questions probing respondents’ attitudes towards the EU, perceptions of the Brexit process, as well as general political attitudes and demographic characteristics. The identities of all participants are anonymized. The final data includes weights based on language region, age, gender and party affinity in order to ensure representativeness.
The data were collected by placing questions on an EU-wide online survey omnibus (the “EuroPulse”) that was regularly conducted by Dalia Research. In each wave, the sample consists of a census representative sample of approximately 10’000 working- age respondents (aged 18–69) from all EU member states, with sample sizes roughly proportional to their population size. While the overall sample is representative of the EU population, samples from France, Germany, Italy, Poland, Spain, and the UK are also nationally representative
Atharvaveda Paippalāda Zurich Edition Book 10
No full textThe tenth book of the Paippalāda Recension of the Atharvaveda comprises 10 sūktas (hymns) with a total of 165 stanzas. Each stanza is provided with an English translation, detailed linguistic and Indological comments, critical apparatus, parallel passages in the Sanskrit literature and a full morpho-lexical analysis. This information is encoded in TEI-XML format
mitenand DSGS/Ensemble LSF/Insieme LIS
No full textThis dataset is part of our research paper at LREC-COLING 2024:
Jiang, Zifan, Göhring, Anne, Moryossef, Amit, Sennrich, Rico, Ebling, Sarah. 2024. SwissSLi: The Multi-parallel Sign Language Corpus for Switzerland. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Online: https://aclanthology.org/2024.lrec-main.1342
Our study contains the sign language version of two sets of television programs in three spoken/sign languages released between 2020 and 2023 fall. They were created by the Swiss Broadcasting Corporation (SRG) in spoken language and then translated into sign language.
This dataset contains mitenand (German/DSGS), Ensemble (French/LSF-CH), and Insieme (Italian/LIS-CH) which report the work of charity organizations, are parallel and produced weekly. Most episodes originate from German and are then translated into other languages.
mitenand in Gebärdensprache:
https://www.srf.ch/play/tv/sendung/mitenand-in-gebaerdensprache?id=1d478b33-be72-4258-a330-c8c15bc1f6aa
Ensemble - signé:
https://www.rts.ch/play/tv/emission/ensemble-signe?id=12546856
Insieme LIS:
https://www.rsi.ch/play/tv/programma/insieme-lis?id=70397
Helveticus DSGS/LSF/LIS
No full textThis dataset is part of our research paper at LREC-COLING 2024:
Jiang, Zifan, Göhring, Anne, Moryossef, Amit, Sennrich, Rico, Ebling, Sarah. 2024. SwissSLi: The Multi-parallel Sign Language Corpus for Switzerland. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Online: https://aclanthology.org/2024.lrec-main.1342
Our study contains the sign language version of two sets of television programs in three spoken/sign languages released between 2020 and 2023 fall. They were created by the Swiss Broadcasting Corporation (SRG) in spoken language and then translated into sign language.
This dataset contains Helveticus in three languages which covers historical content with animations and is produced irregularly. Most episodes originate from German and are then translated into other languages.
Helveticus in Gebärdensprache:
https://www.srf.ch/play/tv/sendung/helveticus-in-gebaerdensprache?id=46863500-56d8-4414-a3d9-e84a6a843287
Helveticus signé:
https://www.rts.ch/play/tv/emission/helveticus-signe?id=10953398
Helveticus LIS:
https://www.rsi.ch/play/tv/programma/helveticus-lis?id=70391
Befragung zu Massnahmen zur Diversität in (gewinnorientierten) Organisationen in der Schweiz und Deutschland (2017&2020)
No full textFragebogen zum Thema Diversity, der sich an Schweizer und deutsche Organisationen (Grossteil gewinnorientierte Firmen) richtet. Abgefragt werden Diversity-Massnahmen, die innerhalb der Organisation durchgeführt werden, sowie weitere Massnahmen, die zur Steigerung der Diversität im Management beitragen könnten.
Der Fragebogen umfasst zwei Wellen. Bei der zweiten Befragung wurden einige Fragen weggelassen und durch andere Fragen ergänzt. Der Grossteil der Fragen ist gleich geblieben und erlaubt einen Vergleich der zwei Zeitpunkte.
Erhebung der 1. Welle: Sept. 2017 - Nov. 2017
Erhebung der 2. Welle: Nov. 2019 - Jan. 2020
Der Datensatz enthält beide Zeitpunkte (Variable: Wave
Surface Groups Botswana 1984-2021
No full textSurface groups for Botswana (years 1984 - 2021) 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)
Surface Groups Cabo Verde 1984-2021
No full textSurface groups for Cabo Verde (years 1984 - 2021) 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)