dashboard-krankenversicherung-okp

maintainer: Office fédéral de la santé publique - section gestion de données et statistique DMS

title_for_slug: Dashboard Krankenversicherung OKP

fr: sante assurance-maladie assurance dashboard

de: dashboard versicherung gesundheit krankenversicherung

en: dashboard health-insurance insurance health

it: assicurazione-malattie assicurazione dashboard salute

author: Bundesamt für Gesundheit BAG - Office fédéral de la santé publique OFSP - Ufficio federale della sanità pubblica UFSP

de: Loi fédérale sur l'assurance-maladie (LAMal)

fr: Le fichier contient les données présentées dans les graphiques des pages principales

en: The file contains the data presented in the charts on the main pages

de: Die Datei enthält die Daten, die in den Grafiken auf den Hauptseiten dargestellt werden

it: Il file contiene i dati presentati nei grafici delle pagine principali.

fr: Le fichier contient les données présentées dans le Dashboard de l'assurance-maladie

en: The file contains the data presented in the health insurance dashboard

de: Die Datei enthält die Daten, die im Dashboard Krankenversicherung dargestellt werden

it: Il file contiene i dati presentati nel dashboard sull'assicurazionemalattie

fr: Le Dashboard assurance-maladie (AOS) présente des données sur l'assurance-maladie en Suisse. Il se limite à l'assurance obligatoire des soins (AOS), selon la loi fédérale sur l'assurance-maladie, également connue sous le nom d'assurance de base ou d'assurance-maladie sociale. L'OFSP surveille les assureurs-maladie qui appliquent l'AOS. D'autres données et chiffres clés sont disponibles sur le site de l’OFSP.

en: The Dashboard heath Insurance (OKP) shows data on health insurance in Switzerland. It is limited to compulsory health insurance (OKP), in accordance with the Federal Health Insurance Law, also known as basic insurance or social health insurance. The FOPH supervises the health insurers that provide OKP. Further data and key figures are available on the FOPH website.

de: Das Dashboard Krankenversicherung (OKP) zeigt Daten zur Krankenversicherung in der Schweiz. Es beschränkt sich auf die obligatorische Krankenpflegeversicherung (OKP), nach dem Bundesgesetz über die Krankenversicherung, auch als Grundversicherung oder soziale Krankenversicherung bekannt. Das BAG beaufsichtigt die Krankenversicherer, die die OKP durchführen. Weitere Daten und Kennzahlen, sind auf der Webseite des BAG verfügbar.

it: Il Dashboard dell'assicurazione malattie (OKP) mostra i dati sull'assicurazione malattie in Svizzera. Si limita all'assicurazione  malattie obbligatoria (OKP), ai sensi della Legge federale sull'assicurazione malattia, nota anche come assicurazione di base o assicurazione malattie sociale. L'UFSP vigila sulle assicurazioni malattie che forniscono l'OKP. Ulteriori dati e cifre chiave sono disponibili sul sito dell'UFSP.

assicurazione

display_name: assicurazione

assicurazione-malattie

display_name: assicurazione-malattie

assurance

display_name: assurance

assurance-maladie

display_name: assurance-maladie

dashboard

display_name: dashboard

gesundheit

display_name: gesundheit

health

display_name: health

health-insurance

display_name: health-insurance

insurance

display_name: insurance

krankenversicherung

display_name: krankenversicherung

salute

display_name: salute

sante

display_name: sante

versicherung

display_name: versicherung

fr: Dashboard assurance-maladie AOS

de: Dashboard Krankenversicherung OKP

en: Dashboard health insurance OKP

it: Dashboard assicurazione malattie OKP

heal

fr: Santé

de: Gesundheit

en: Health

it: Salute

bundesamt-fur-gesundheit-bag

de: Bundesamt für Gesundheit BAG

en: Federal Office of Public Health FOPH

fr: L'Office fédéral de la santé publique (OFSP) fait partie du Département fédéral de l'intérieur. De concert avec les cantons, il assume la responsabilité des domaines touchant à la santé publique ainsi que la mise en œuvre de la politique sanitaire. Autorité à vocation nationale, il représente les intérêts sanitaires de la Suisse dans les organisations internationales et auprès d'autres Etats.

de: Das Bundesamt für Gesundheit (BAG) ist Teil des Eidgenössischen Departements des Innern. Es ist - zusammen mit den Kantonen - verantwortlich für die Gesundheit der Schweizer Bevölkerung und für die Entwicklung der nationalen Gesundheitspolitik. Zudem vertritt das BAG als nationale Behörde die Schweiz in Gesundheitsbelangen in internationalen Organisationen und gegenüber anderen Staaten.

en: The Federal Office of Public Health (FOPH) is part of the Federal Department of Home Affairs. Along with the cantons it is responsible for public health in Switzerland and for developing national health policy. As the national health authority, the FOPH also represents Switzerland's interests in the field of health in international organisations and with respect to other countries.

it: L'Ufficio federale della sanità pubblica (UFSP) è incorporato nel Dipartimento federale dell'interno. Unitamente ai Cantoni, è responsabile della salute della popolazione svizzera e dello sviluppo della politica nazionale in materia di salute. In qualità di autorità nazionale rappresenta inoltre gli interessi della Svizzera in materia di sanità in seno a organizzazioni internazionali e nei rapporti con altri Stati.


author: BFS/OFS

state: active

type: dataset

it: Ambiente. Statistica tascabile 2020

media_type: text/html

format: HTML

mimetype: text/html

fr: Environnement. Statistique de poche 2020

media_type: application/pdf

format: PDF

mimetype: application/pdf

de: Umwelt. Taschenstatistik 2020

en: Environment. Pocket Statistics 2020

espace-et-environnement

display_name: espace-et-environnement

raum-und-umwelt

display_name: raum-und-umwelt

territori-ed-ambient

display_name: territori-ed-ambient

territorio-e-ambiente

display_name: territorio-e-ambiente

territory-and-environment

display_name: territory-and-environment

spatial: Schweiz

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS

de: Bundesamt für Statistik BFS

en: Federal Statistical Office FSO

it: Ufficio federale di statistica UST

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.

en: The FSO is Switzerland's national competence centre for official statistics. It produces and publishes statistical information on the status and development of the population, economy, society, education, research, territory and the environment. This information is used for opinion building among the population and for the planning and management of key policy areas. They make an important contribution to a modern, democratic state.

it: L’UST è il centro di competenza nazionale per la statistica pubblica della Svizzera. Produce e pubblica informazioni statistiche sullo stato e sull'evoluzione della popolazione, dell'economia, della società, della formazione, della ricerca, del territorio e dell'ambiente. Queste informazioni servono alla formazione dell'opinione pubblica nonché alla pianificazione e alla gestione in ambiti politici di centrale importanza. Forniscono un importante contributo per uno Stato moderno e democratico.

political_level: confederation

type: organization

approval_status: approved

key: guid

key: uri

value: BFS – DCAT Harvester


de: Allgemeine Preisentwicklung in der Schweiz. Veränderungsraten der Jahresdurchschnitte

format: XLS

fr: Evolution générale des prix en Suisse. Taux de variation des moyennes annuelles

preise

display_name: preise

pretschs

display_name: pretschs

prezzi

display_name: prezzi

prices

display_name: prices

prix

display_name: prix

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

en: Economy and finance

it: Economia e finanze


fr: Organisation du travail et aménagement du temps de travail en Suisse et en comparaison européenne 2019

de: Arbeitsorganisation und Arbeitszeitgestaltung in der Schweiz und im europäischen Vergleich 2019

arbeit-und-erwerb

display_name: arbeit-und-erwerb

lavoro-e-reddito

display_name: lavoro-e-reddito

lavur-e-gudogn

display_name: lavur-e-gudogn

travail-et-remuneration

display_name: travail-et-remuneration

work-and-income

display_name: work-and-income


fr: Personnes ayant déménagé selon l'époque de construction

de: Umgezogene Personen nach Bauperiode der Gebäude

it: Persone che hanno traslocato secondo l'epoca di costruzione

bau--und-wohnungswesen

display_name: bau--und-wohnungswesen

construction-and-housing

display_name: construction-and-housing

construction-et-logement

display_name: construction-et-logement

construcziuns-ed-abitaziuns

display_name: construcziuns-ed-abitaziuns

costruzioni-e-abitazioni

display_name: costruzioni-e-abitazioni

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

en: Population and society

it: Popolazione e società


fr: Exploitations agricoles: gestion, formation, condition de propriété et reprise selon la classe de taille SAU

fr: Ce dataset présente le nombre d'exploitations agricoles selon la classe de taille de la surface agricole utile, la gestion, la formation, la condition de propriété et la reprise, en 2010, 2013, 2016 et 2020.

fr: Structure JSON

format: SERVICE

de: JSON-Struktur

de: Landwirtschaftsbetriebe: Betriebsführung, Ausbildung, Eigentumsverhältnisse und Weiterführung nach Grössenklasse LN

de: Dieses Dataset präsentiert die Zahl der Landwirtschaftsbetriebe nach Grössenklasse der landwirtschaftlichen Nutzfläche, Betriebsführung, Ausbildung, Eigentumsverhältnisse und Weiterführung, 2010, 2013, 2016 und 2020.

agricoltura-e-selvicoltura

display_name: agricoltura-e-selvicoltura

agricultura-ed-economia-forestala

display_name: agricultura-ed-economia-forestala

agriculture-and-forestry

display_name: agriculture-and-forestry

agriculture-et-sylviculture

display_name: agriculture-et-sylviculture

land--und-forstwirtschaft

display_name: land--und-forstwirtschaft

agri

fr: Agriculture, pêche, sylviculture et alimentation

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

it: Agricoltura, pesca, silvicoltura e prodotti alimentari


energie

title_for_slug: energie

fr: Énergie

fr: Ce dataset présente les chiffres annuels des Statistiques des villes suisses 2023 - Energie: Service des eaux et Service du gaz; Eau captée par an; Eau livrée en 24 heures; En litres par habitant et jour de la région desservie; Fourniture de gaz, en 2021. Les descriptions (informations générales, légende, explication des codes, liste variables, explications variables, source, status de la donnée) des variables du fichier CSV sont disponibles dans l’annexe.

de: Energie

de: Dieses Dataset präsentiert die jährlichen Zahlen der Statistik der Schweizer Städte 2023 - Energie: Wasser- und Gasversorgung; Jährliche Wassergewinnung; Tägliche Wasserabgabe; Liter je einwohner/in und Tag des Versorgunsgebietes; Gasverkauf, 2021. Die Beschreibungen (allgemeine Informationen, Legende, Erklärungen zur Codes, Liste der Variablen, Erklärungen zur Variablen, Quellen, Status der Daten) der Variablen in der CSV-Datei sind im Anhang verfügbar.

format: ODS

media_type: text/csv

format: CSV

mimetype: text/csv

energia

display_name: energia

energie

display_name: energie

energy

display_name: energy

espace-et-environnement

display_name: espace-et-environnement

raum-und-umwelt

display_name: raum-und-umwelt

territori-ed-ambient

display_name: territori-ed-ambient

territorio-e-ambiente

display_name: territorio-e-ambiente

territory-and-environment

display_name: territory-and-environment

ener

en: Energy

it: Energia


fr: Kanton Bern - Die Bevölkerungszahlen auf lokaler Ebene vor 1850

fr: Ce dataset présente les effectifs de la population du canton de Berne au niveau local (paroisse ou commune) selon des dénombrements ou recensements effectués entre 1730 - 1850. Les descriptions des variables du fichier CSV sont disponibles dans l’annexe.

de: Dieses Dataset präsentiert die Bevölkerungszahlen des Kantons Bern auf lokaler Ebene (Pfarrgemeinde oder politische Gemeinde) gemäss Erhebungen und Volkszählungen ausgeführt zwischen 1730 - 1850. Die Beschreibungen der Variablen in der CSV-Datei sind im Anhang verfügbar.

it: Questo dataset presenta l’effettivo della popolazione del Cantone Berna a livello locale (parrocchia o comune) secondo i conteggi o i censimenti effettuati tra il 1730 - 1850. Per le descrizioni delle variabili del file CSV si rimanda all’allegato.

bevolkerung

display_name: bevolkerung

popolazione

display_name: popolazione

population

display_name: population

populaziun

display_name: populaziun

spatial: Gemeinden


it: Kanton Schwyz - Die Bevölkerungszahlen auf lokaler Ebene vor 1850

it: Questo dataset presenta l’effettivo della popolazione del Cantone Svitto a livello locale (parrocchia o comune) secondo i conteggi o i censimenti effettuati tra il 1743 - 1850. Per le descrizioni delle variabili del file CSV si rimanda all’allegato.

de: Dieses Dataset präsentiert die Bevölkerungszahlen des Kantons Schwyz auf lokaler Ebene (Pfarrgemeinde oder politische Gemeinde) gemäss Erhebungen und Volkszählungen ausgeführt zwischen 1743 - 1850. Die Beschreibungen der Variablen in der CSV-Datei sind im Anhang verfügbar.

fr: Ce dataset présente les effectifs de la population du canton de Schwyz au niveau local (paroisse ou commune) selon des dénombrements ou recensements effectués entre 1743 - 1850. Les descriptions des variables du fichier CSV sont disponibles dans l’annexe.


fr: Appréciation de la qualité de l'environnement

de: Einschätzung der Umweltqualität

spatial: Sonstige Raumgliederungen

envi

fr: Environnement


fr: femme securite-sociale genre homme

de: mann geschlecht frau soziale-sicherheit

en: social-security woman man gender

it: genere sicurezza-sociale uomo donna

fr: Effectifs mensuels moyens de bénéficiaires d'indemnités journalières de l'assurance-chômage (AC), de rentes de l'assurance-invalidité (AI) et de l'aide sociale (AS) et part de ces effectifs par statut de revenu du travail, sexe, classe de nationalités et classe d'âges

de: Durchschnittlicher Monatsbestand der Beziehenden von ALV-Taggeldern (ALV), IV-Renten (IV) und Sozialhilfe (SH) und Anteil dieser Bestände nach Erwerbsstatus, Geschlecht, Nationalitätenkategorie und Altersgruppe

en: Monthly average number of recipients of daily unemployment insurance allowances (UI), invalidity insurance pensions (II) and social assistance (SA) and proportion of those numbers, by work income status, sex, nationality group and age group

it: Effettivo mensile medio di persone beneficiarie di indennità giornaliere dell'assicurazione contro la disoccupazione (AD), di rendite dell'assicurazione invalidità (AI) e dell'aiuto sociale (AS) e quota di tali beneficiari per statuto di reddito, sesso, categoria di nazionalità e fascia di età

fr: Ce dataset présente les chiffres annuels des effectifs mensuels moyens des bénéficiaires dans l'assurance chômage (AC), l'aide sociale (AS) et l'assurance invalidité (AI), en nombre absolu et en pourcentage, selon la prestation, le sexe, la classe d'âges et la nationalité (Suisses/Suissesses, étrangers/étrangères), depuis 2010. Les descriptions des variables du fichier CSV sont disponibles dans l’annexe.

de: Dieses Dataset präsentiert den jährlichen durchschnittlichen Monatsbestand in der Arbeitslosenversicherung (ALV), Sozialhilfe (SH) und Invalidenversicherung (IV), absolut und in %, nach Leistung, Geschlecht. Altersklasse und Nationalität (Schweizer\innen, Ausländer\innen), seit 2010. Die Beschreibungen der Variablen in der CSV-Datei sind im Anhang verfügbar.

en: This dataset presents the annual data on monthly average number of recipients of daily unemployment insurance allowances (UI), invalidity insurance pensions (II) and social assistance (SA), in absolute numbers and percentages, by benefit, gender, age group and nationality (Swiss/foreigners), since 2010. Descriptions of the variables in the CSV file are available in the Appendix.

it: Questo dataset presenta i dati annuali dal 2010 relativi agli effettivi mensili medi di persone beneficiarie dell’assicurazione contro la disoccupazione (AD), dell’aiuto sociale (AS) e dell’assicurazione per l'invalidità (AI), in numero assoluto e in percentuale, secondo la prestazione, il sesso, la fascia di età e la nazionalità (svizzera o straniera). Per le descrizioni delle variabili del file CSV si rimanda all’allegato.

donna

display_name: donna

femme

display_name: femme

frau

display_name: frau

gender

display_name: gender

genere

display_name: genere

genre

display_name: genre

geschlecht

display_name: geschlecht

homme

display_name: homme

man

display_name: man

mann

display_name: mann

securite-sociale

display_name: securite-sociale

segirezza-sociala

display_name: segirezza-sociala

sicurezza-sociale

display_name: sicurezza-sociale

social-security

display_name: social-security

soziale-sicherheit

display_name: soziale-sicherheit

uomo

display_name: uomo

woman

display_name: woman

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS

fr: L'OFS est le centre de compétence de la statistique publique suisse. Il produit des informations statistiques sur la population, l'économie, la société, la formation et la recherche, le territoire et l'environnement. Ces informations servent à la formation de l’opinion publique. Elles sont un outil de planification et de gouvernance dans tous les domaines de l’action politique et contribuent au bon fonctionnement de notre État moderne et démocratique.


de: Dieses Dataset präsentiert die jährliche Anzahl der Klienten in sozialmedizinischen Institutionen nach Grossregion und Kanton des Betriebes, Beherbergungstyp, Herkunft, Destination, Geschlecht und Altersklasse, ab 2006.

fr: Nombre de clients dans les institutions médico-sociales selon la grande région et le canton de l'établissement, le type d'hébergement, la provenance, la destination, le sexe et la classe d'âge

fr: Ce dataset présente le nombre annuel de clients dans les institutions médico-sociales selon la grande région et le canton de l'établissement, le type d'hébergement, la provenance, la destination, le sexe et la classe d'âge, depuis 2006.

gesundheit

display_name: gesundheit

health

display_name: health

salute

display_name: salute

sanadad

display_name: sanadad

sante

display_name: sante

heal

fr: Santé

de: Gesundheit

it: Salute

de: Bundesamt für Statistik BFS

de: Das BFS ist das nationale Kompetenzzentrum der öffentlichen Statistik der Schweiz. Es produziert und publiziert statistische Informationen über den Stand und die Entwicklung von Bevölkerung, Wirtschaft, Gesellschaft, Bildung, Forschung, Raum und Umwelt. Diese Informationen dienen der Meinungsbildung in der Bevölkerung sowie der Planung und Steuerung von zentralen Politikbereichen. Sie leisten einen wichtigen Beitrag für einen modernen, demokratischen Staat.


fr: Musées: collection et expositions

it: Musei: collezione ed esposizioni

de: Museen: Sammlung und Ausstellungen

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport


fr: population mere couple pere

de: mutter paar vater bevolkerung

en: couple father population mother

it: popolazione coppia madre padre

fr: Ménages privés selon le type de ménage et des caractéristiques régionales

fr: Ce dataset présente les chiffres annuels du nombre de ménages selon le type de ménage, le canton et la région linguistique, depuis 2010. Les descriptions des variables du fichier CSV sont disponibles dans l’annexe.

de: Privathaushalte nach Haushaltstyp und regionalen Merkmalen

de: Dieses Dataset präsentiert die jährlichen Zahlen der Haushalte nach Haushaltstyp, Kanton und Sprachgebiet, seit 2010. Die Beschreibungen der Variablen in der CSV-Datei sind im Anhang verfügbar.

it: Economie domestiche secondo il tipo di economia domestica et le caratteristiche regionali

it: Questo dataset presenta le cifre annuali per il numero di economie domestiche secondo il tipo di economia domestica, il Cantone e la regione linguistica, dal 2010. Per le descrizioni delle variabili del file CSV si rimanda all’allegato.

en: Private households by household type and regional characteristics

en: This dataset presents the annual figures for the number of households by type of household, canton and linguistic region, since 2010. Descriptions of the variables in the CSV file are available in the Appendix.

bevolkerung

display_name: bevolkerung

coppia

display_name: coppia

couple

display_name: couple

father

display_name: father

madre

display_name: madre

mere

display_name: mere

mother

display_name: mother

mutter

display_name: mutter

paar

display_name: paar

padre

display_name: padre

pere

display_name: pere

popolazione

display_name: popolazione

population

display_name: population

populaziun

display_name: populaziun

vater

display_name: vater

spatial: Sprachgebiete

soci

fr: Population et société

de: Bevölkerung und Gesellschaft


maintainer: Bundesamt für Energie BFE

title_for_slug: Schweizerische Elektrizitätsstatistik: Schweizerische Elektrizitätsbilanz - Monatswerte

fr: ogd35-bfe electricite production importation exportation consommation

de: ogd35-bfe elektrizitat produktion import export verbrauch

en: ogd35-bfe electricity production import export

it: ogd35-bfe elettricita produzione importazione esportazione consumo

author: Bundesamt für Energie BFE

fr: Cette statistique recense sur une base mensuelle la production, l'importation, l'exportation et la consommation d'électricité en Suisse. Elle présente la production des centrales hydrauliques, des centrales nucléaires, des centrales thermiques classiques et renouvelables.A partir de l’année  2020, la production des centrales thermiques, des éoliennes et des installations photovoltaïques est indiquée séparément. Elle indique également la consommation des installations de pompage d'accumulation et les pertes en ligne. Elle est établie dans le cadre de la Statistique de l'électricité, qui fait partie de la statistique publique de la Suisse (base légale: LSF).

de: Die Schweizerische Elektrizitätsbilanz - Monatswerte gibt Auskunft über Produktion, Import / Export und Verbrauch von Elektrizität in der Schweiz auf monatlicher Basis. Bei der Produktion werden Wasserkraftwerke, Kernkraftwerke, konventionell-thermische und erneuerbare Kraftwerke unterschieden.Die Produktion der thermischen Kraftwerke, der Windkraft- und Photovoltaikanlagen wird seit dem Jahr 2020 neu separat ausgewiesen.  Der Verbrauch der Speicherpumpen und die Leitungsverluste werden ebenfalls ausgewiesen. Die monatliche Elektrizitätsbilanz wird im Rahmen der Elektrizitätsstatistik erstellt, welche Teil der öffentlichen Statistik der Schweiz ist (gesetzliche Grundlage: BStatG).

fr: Statistique suisse de l'électricité: bilan mensuel suisse de l'électricité

it: Statistica svizzera dell'elettricità: bilancio svizzero dell'elettricità - valori mensili

ener

fr: Énergie

de: Energie

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

it: Economia e finanze

de: Bundesamt für Energie BFE

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).


name: Fachstelle Open Government Data des Kantons Zürich

fr: Datenkatalog

de: Datenkatalog

en: Datenkatalog

it: Datenkatalog

fr: DCAT-AP CH – The Swiss Application Profile for Data Portals and Catalogues

de: API-Endpoint für Datensätze im Metadatenkatalog des Kantons Zürich

media_type: application/json

de: Enthält alle aktuell im Metadatenkatalog des Kantons Zürich enthaltenen Datensätze mit ihren Metadaten: (1) häufig nachgefragte Excel-Tabellen, (2) Indikatoren aus dem Gemeindeporträt, (3) Publikationen des Statistischen Amts sowie (4) offene Behördendaten des Kantons Zürich (ausgenommen offene Geodaten).

format: JSON

de: Enthält alle aktuell im Metadatenkatalog des Kantons Zürich enthaltenen Datensätze mit ihren Metadaten. Folgt dem Metadaten-Standard 'DCAT-AP CH v1' (eCH-0200).

fachstelle-ogd-kanton-zuerich

de: Fach- und Koordinationsstelle Open Government Data Kanton Zürich

de: Die Fach- und Koordinationsstelle Open Government Data (OGD) ist das kantonale Kompetenzzentrum für offene Behördendaten im Statistischen Amt. Wir unterstützen die Organisationseinheiten und Organe des Kantons bei der Bereitstellung ihrer nicht schützenswerten Daten als Open Data.

political_level: canton

kanton-zuerich

capacity: public

value: ZH-Kt Fachstelle OGD - DCAT Harvester

de: Web Service des Metadatenkatalogs des Kantons Zürich


de: Datenstruktur auf Deutsch

en: Data structure in German

de: Datenwürfel auf Deutsch

en: Data cube in German

de: Datenwürfel auf Englisch

en: Data cube in English

de: Datenstruktur auf Englisch

en: Data structure in English

de: Einkommensverteilungskonto zu laufenden Preisen 2013 - 2016 bei Jahr, Transaktion und Wirtschaftsbereich

en: Allocation of primary income account at current prices 2013 - 2016 by Year, Transaction and Economic activity

national-accounts

display_name: national-accounts

volkswirtschaftliche-gesamtrechnungen

display_name: volkswirtschaftliche-gesamtrechnungen

amt-fuer-statistik-fl

de: Amt für Statistik

en: Office of Statistics

en: The Office of Statistics is Liechtenstein's statistical information center. It provides the national and municipal authorities as well as the public with relevant, reliable and coherent statistical information on society, economy and environment in Liechtenstein.

de: Das Amt für Statistik ist das statistische Informationszentrum Liechtensteins. Es liefert den Landes- und Gemeindebehörden sowie der Öffentlichkeit relevante, zuverlässige und kohärente statistische Informationen zu Gesellschaft, Wirtschaft und Umwelt in Liechtenstein.

political_level: other

value: DCAT Harvester Amt für Statistik FL

de: Einkommensverteilungskonto zu laufenden Preisen 2013 - 2016 nach Wirtschaftsbereich

en: Allocation of primary income account at current prices 2013 - 2016 by economic activity


de: Einzelbasis - Lernende in Liechtenstein bei Jahr, Lehrjahr und Geschlecht

en: Individual basis - Apprentices in Liechtenstein by Year, Apprenticeship year and Sex

banken

display_name: banken

banking-institutions

display_name: banking-institutions

econ

de: Wirtschaft und Finanzen

en: Economy and finance

de: Einzelbasis - Lernende in Liechtenstein nach Lehrjahr und Geschlecht seit 2017

en: Individual basis - Apprentices in Liechtenstein by apprenticeship year and sex since 2017


de: Studierende aus Liechtenstein an Universitäten nach Jahr, Studienland/ Universität und Geschlecht

en: Students from Liechtenstein at universities by Year, Country/ university and Sex

hochschulen

display_name: hochschulen

tertiary-education

display_name: tertiary-education

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

de: Studierende aus Liechtenstein an Universitäten nach Studienland/ Universität und Geschlecht seit 2005/06

en: Students from Liechtenstein at universities by country/ university and sex since 2005/06


maintainer: Basel-Landschaft

fr: federal votation

de: abstimmung national

it: nazionale votazione

fr: Formatbeschreibung

de: Formatbeschreibung

en: Formatbeschreibung

it: Formatbeschreibung

fr: Descripziun dal format

de: Descripziun dal format

en: Descripziun dal format

it: Descripziun dal format

fr: Descrizione del formato

de: Descrizione del formato

en: Descrizione del formato

it: Descrizione del formato

fr: Description du format

de: Description du format

en: Description du format

it: Description du format

identifier: csv

mimetype: application/json

identifier: json

rm: Resultats finals da la votaziun federala "Kantonale Beiträge an Spitalbehandlungen", 9 da favrer 2003, Kanton Basel-Landschaft, ordinà tenor vischnancas.

fr: Résultats finaux du vote fédéral "Kantonale Beiträge an Spitalbehandlungen", 9 février 2003, Kanton Basel-Landschaft, répartis par municipalités.

de: Schlussresultate der eidgenössischen Abstimmung "Kantonale Beiträge an Spitalbehandlungen", 9. Februar 2003, Kanton Basel-Landschaft, aufgeschlüsselt nach Gemeinden.

it: Risultati finali della votazione federale "Kantonale Beiträge an Spitalbehandlungen", 9 febbraio 2003, Kanton Basel-Landschaft, suddivisi per municipalit.

abstimmung

display_name: abstimmung

federal

display_name: federal

national

display_name: national

nazionale

display_name: nazionale

plaun-naziunal

display_name: plaun-naziunal

votation

display_name: votation

votazione

display_name: votazione

votaziun

display_name: votaziun

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

kanton-basel-landschaft

fr: Canton de Bâle-Campagne

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

it: Cantone di Basilea-Campagna

en:
The Canton of Basel-Country publishes open datasets of cantonal offices and agencies.
Further information at https://ogd.bl.ch/

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

value: BL - Abstimmungen


fr: cantonal votation

de: kantonal abstimmung

it: cantonale votazione

author: Basel-Landschaft

rm: Resultats finals da la votaziun chantunala "Änderung vom 10. Februar der Kantonsverfassung (§ 55 Öffentlichkeit von Verhandlungen und § 56 Information) und Datenschutzgesetz", 27 da november 2011, Kanton Basel-Landschaft, ordinà tenor vischnancas.

fr: Résultats finaux du vote cantonal "Änderung vom 10. Februar der Kantonsverfassung (§ 55 Öffentlichkeit von Verhandlungen und § 56 Information) und Datenschutzgesetz", 27 novembre 2011, Kanton Basel-Landschaft, répartis par municipalités.

de: Schlussresultate der kantonalen Abstimmung "Änderung vom 10. Februar der Kantonsverfassung (§ 55 Öffentlichkeit von Verhandlungen und § 56 Information) und Datenschutzgesetz", 27. November 2011, Kanton Basel-Landschaft, aufgeschlüsselt nach Gemeinden.

it: Risultati finali della votazione cantonale "Änderung vom 10. Februar der Kantonsverfassung (§ 55 Öffentlichkeit von Verhandlungen und § 56 Information) und Datenschutzgesetz", 27 novembre 2011, Kanton Basel-Landschaft, suddivisi per municipalit.

cantonal

display_name: cantonal

cantonale

display_name: cantonale

kantonal

display_name: kantonal

plaun-chantunal

display_name: plaun-chantunal


wasserrechte

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: wasserrechte

de: konzession wasserrecht entnahme ruckgabe kanal wasserrechtskanal stauwehr stauwehrreglement wasserrechtskonzession eheliche-konzession wasserrechtsbezirk wasserrechtsnummer

author: Kanton Zürich

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

fr: Öffentliche Oberflächengewässer, Wasserrechte, Gewässerraum und Hochwasserrückhaltebecken

format: WMS

fr: WFS für Open-Government-Data des Kantons Zürich (OGD ZH WFS)

format: WFS

fr: Die konzessionierten Wasserrechte wurden ab 1997 mit den öffentlichen Oberflächengewässern im GIS erfasst und werden seit 1998 als eigener Datensatz in Abstimmung zu den öffentlichen Oberflächengewässern vom AWEL, Abt. Wasserbau nachgeführt. Seit Januar 2022 werden aktive und gelöschte Wasserrechte in getrennten Datensätzen zu Verfügung gestellt. Die Daten sind auf dem SDE Server vom GIS-ZH abgelegt unter: GISZHPUB.WASSERRECHTE_F für die Wasserrechtsweiher (Flächendaten) GISZHPUB.WASSERRECHTE_GELOESCHT_F für die gelöschten Wasserrechtsweiher (Flächendaten) GISZHPUB.WASSERRECHTE_L für die Wasserrechtskanäle und Leitungen (Liniendaten) GISZHPUB.WASSERRECHTE_GELOESCHT_L für die gelöschten Wasserrechtskanäle und Leitungen (Liniendaten) GISZHPUB.WASSERRECHTE_P für die Entnahme- und Rückgabeorte (Punktdaten) GISZHPUB.WASSERRECHTE_GELOESCHT_P für die gelöschten Entnahme- und Rückgabeorte (Punktdaten)

spatial: Kanton Zürich

fr: Kanton Zürich

de: Kanton Zürich

en: Kanton Zürich

it: Kanton Zürich

geoinformation-kanton-zuerich

fr: Département de Géoinformation du Canton de Zurich

de: Geoinformation Kanton Zürich

en: Department of Geoinformation of the Canton of Zurich

it: Dipartimento della geoinformazione del Cantone di Zurigo

fr:
Le département de géomatique est le centre de compétence du system d'information géographique du canton de Zurich.
Nous coordinons l'aquisition des géodonnées d'intérêt commun sur le territoire cantonal et les mettons à disposition des
secteurs public et privé et des particuliers.

en:
The department of geoinformation is the geospatial competency center of the Canton of Zurich.
We coordinate the acquisition of geodata within the cantonal territory and provide public, private, and government sectors with data of outstanding quality.

de: Die Abteilung Geoinformation ist das Kompetenzzentrum für räumliche Informationen im Kanton Zürich. Wir versorgen Gesellschaft, Wirtschaft und öffentliche Verwaltung mit qualitativ hochstehenden Geodaten und Informationen über den Kanton Zürich.

it: La divisione della geoinformazione è il centro d'eccellenza del Cantone di Zurigo per dati georeferenziati. Mettiamo a disposizione dati geografici e informazioni di alta qualità per l'economia, la società e la pubblica amministrazione su tutto il cantone.

value: ZH - Geocat Harvester

fr: Wasserrechte

de: Wasserrechte

en: Wasserrechte

it: Wasserrechte


maintainer: Sektion energieeffizienter Verkehr

title_for_slug: Kennzahlen alternativ angetriebene PW

de: alternative-antriebe elektromobilitat hybridfahrzeuge co2 ogd92-bfe personenwagen elektrische-fahrzeuge

fr: Chiffres clés des voitures de tourisme neuves à propulsion alternative

de: Kennzahlen alternativ angetriebene PW

en: Key figures for alternatively powered passenger cars

it: Indicatori relativi alle automobili a propulsione alternativa

de: Storymap

fr: Modèles de voitures de tourisme hybrides rechargeables les plus prisés

de: Beliebteste Plug-In PW-Modelle (PHEV)

en: Most popular plug-in models (cars)

it: Automobili plug-in più diffuse (modelli PHEV)

fr: Depuis 2015, l’Office fédéral de l’énergie recense chaque trimestre les modèles de voitures de tourisme hybrides rechargeables (PHEV) les plus prisés; depuis 2021, les données sont disponibles à un rythme mensuel. Tous les modèles hybrides rechargeables disponibles en Suisse sont pris en compte.

en: Since 2015, the Swiss Federal Office of Energy has reported the most popular plug-in models (PHEVs) among passenger cars on a quarterly basis; since 2021, the data has been available on a monthly basis. All plug-in models from Switzerland are counted together.

de: Ab 2015 weist das Bundesamt für Energie quartalsweise die beliebtesten Plug-In Modelle (PHEV) bei den Personenwagen aus, ab 2021 sind die Daten in monatlicher Auflösung verfügbar. Dabei werden alle Plug-In Modelle aus der Schweiz zusammengezählt.

it: Dal 2015 l'Ufficio federale dell'energia indica su base trimestrale i modelli più diffusi di automobili plug-in (PHEV); dal 2021 i dati sono disponibili con risoluzione mensile. Vengono conteggiati tutti i modelli plug-in presenti in Svizzera.

fr: Statistiques des motorisations alternatives des voitures de tourisme

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2015 les statistiques des motorisations alternatives des voitures de tourisme.
Sont réputés véhicules à propulsion alternative les véhicules dont la propulsion ne se fait pas exclusivement avec un moteur à combustion à essence ou à diesel.
Ce jeu de données montre le nombre de voitures de tourisme à motorisation alternative par type de motorisation et par canton. Les données sont présentées sous forme de totaux annuels (2015-actuel), trimestriels (2015-2020) ou mensuels (2021-actuel).
Légende: t1 = émissions moyennes de CO2, t2 = nombre de BEV, t3 = nombre de PHEV essence, t4 = nombre de PHEV diesel, t5 = nombre de hybride essence, t6 = nombre de hybride diesel, t7 = nombre de gaz naturel, t8 = nombre de nouvelles immatriculations, t10 = nombre de hydrogène

[La numérotation des cantons est celle de l’OFS](https://www.bfs.admin.ch/asset/fr/453856)

Trimestre 1-4 = Q1-Q4, Trimestre 5 = Total annuel
Mois 1-12 = Janvier-Février, Mois 13 = Total annuel

Le total annuel peut être un peu différent des totaux mensuels ou trimestriels cumulés en raison des ajustements rétroactifs dans la source de données utilisée.

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has evaluated key figures on alternatively powered passenger cars since 2015.
Alternatively powered vehicles are vehicles that are not solely powered by a petrol or diesel internal combustion engine.
This data set shows the number of alternatively powered passenger cars by type of drive per canton. The data is reported as annual totals (2015-current) as well as quarterly totals (2015-2020) and monthly totals (2021-current).

Key: t1 = Average CO2 emissions, t2 = Number of BEVs, t3 = Number of petrol PHEVs, t4 = Number of diesel PHEVs, t5 = Number of hybrid petrol, t6 = Number of hybrid diesel, t7 = Number of natural gas, t8 = Number of new registrations, t10 = Number of hydrogen

[Numbering of cantons according to FSO](https://www.bfs.admin.ch/bfs/en.assetdetail.453856.html)

Quarter 1-4 = Q1-Q4, Quarter 5 = Annual total
Month 1-12 = January-February, Month 13 = Annual total

The annual total may differ slightly from the cumulative monthly or quarterly totals due to retroactive adjustments in the data source used.

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie seit 2015 wichtige Kennzahlen zu den alternativ angetriebenen Personenwagen aus. Als alternativ angetriebenen Fahrzeuge gelten Fahrzeuge, die nicht ausschliesslich über einen Benzin- oder Diesel-Verbrennungsmotor angetrieben werden.
Dieser Datensatz weist die Anzahl alternativ angetriebener Personenwagen nach Antriebsart pro Kanton aus. Die Daten werden als Jahressummen (2015-aktuell) sowie Quartalssummen (2015-2020) bzw. Monatssummen (2021-aktuell) ausgewiesen.

Legende: t1 = Durchschnittliche CO2-Emissionen, t2 = Anzahl BEV, t3 = Anzahl Benzin PHEV, t4 = Anzahl Diesel PHEV, t5 = Anzahl Hybrid Benzin, t6 = Anzahl  Hybrid Diesel, t7 = Anzahl Erdgas, t8 = Anzahl Neuzulassungen, t10 = Anzahl Wasserstoff

[Nummerierung der Kantone gemäss BFS](https://www.bfs.admin.ch/asset/de/453856)

Quartale 1-4 = Q1-Q4, Quartal 5 = Jahressumme
Monate 1-12 = Januar-Dezember, Monat 13 = Jahressumme

Die Jahressumme kann minimal von den kumulierten Monats- bzw. Quartalssummen abweichen. Dies ist auf laufende rückwirkende Anpassungen in der zugrundeliegenden Datenquelle zurückzuführen.

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'USTRA, dal 2015 l'Ufficio federale dell'energia analizza importanti indicatori relativi alle automobili a propulsione alternativa.
Per veicoli a propulsione alternativa si intendono veicoli che non sono mossi esclusivamente da un motore a combustione a benzina o diesel.
Questo set di dati mostra il numero di auto turistiche con motore alternativo per tipo di motore e per cantone. I dati sono presentati come totali annuali (dal 2015 ad oggi), trimestrali (dal 2015 al 2020) o mensili (dal 2021 ad oggi).

Legenda: t1 = Emissioni medie di CO2, t2 = Numero di BEV, t3 = Numero di PHEV benzina, t4 = Numero di PHEV diesel, t5 = Numero di ibride benzina, t6 = Numero di ibride diesel, t7 = Numero di gas naturale, t8 = Numero nuove immatricolazioni, t10 = Numero di idrogeno

[Numerazione dei Cantoni secondo UST](https://www.bfs.admin.ch/bfs/it.assetdetail.453856.html)

Trimestre 1-4 = Q1-Q4, Trimestre 5 = Totale annuale
Mese 1-12 = Gennaio-Febbraio, Mese 13 = Totale annuale

Il totale annuale può essere leggermente diverso dai totali mensili o trimestrali cumulati a causa di rettifiche retroattive nella fonte dei dati usata.

fr: Modèles de voitures de tourisme entièrement électriques les plus prisés

de: Beliebteste vollelektrische PW-Modelle (BEV)

en: Most popular all-electric models (cars)

it: Modelli più diffusi di automobili completamente elettriche

fr: Depuis 2015, l’Office fédéral de l’énergie recense chaque trimestre les modèles de voitures de tourisme entièrement électriques (BEV) les plus prisés; depuis 2021, les données sont disponibles à un rythme mensuel. Tous les modèles entièrement électriques disponibles en Suisse sont pris en compte.

en: Since 2015, the Swiss Federal Office of Energy has reported the most popular all-electric models (BEVs) among passenger cars on a quarterly basis; since 2021, the data has been available on a monthly basis. All fully electric models from Switzerland are counted together.

de: Ab 2015 weist das Bundesamt für Energie quartalsweise die beliebtesten vollelektrische Modelle (BEV) bei den Personenwagen aus, ab 2021 sind die Daten in monatlicher Auflösung verfügbar. Dabei werden alle vollelektrischen Modelle aus der Schweiz zusammengezählt.

it: Dal 2015 l'Ufficio federale dell'energia indica su base trimestrale i modelli più diffusi di automobili completamente elettriche (BEV); dal 2021 i dati sono disponibili con risoluzione mensile. Vengono conteggiati tutti i modelli completamente elettrici presenti in Svizzera.

fr:
Sur la base des données anonymisées des nouvelles immatriculations publiées par l’OFROU, l’Office fédéral de l’énergie évalue depuis 2015 des chiffres clés importants concernant les voitures de tourisme à propulsion alternative. Sont réputés véhicules à propulsion alternative les véhicules dont la propulsion ne se fait pas exclusivement avec un moteur à combustion à essence ou à diesel. Ce jeu de données comprend, outre les statistiques annuelles agrégées, les chiffres trimestriels et mensuels des parts de marché ainsi que des indications sur les différents cantons. L’Office fédéral de l’énergie évalue par ailleurs les modèles entièrement électriques et hybrides rechargeables les plus prisés.

Base légale: art. 11 de l’ordonnance sur les exigences relatives à l’efficacité énergétique (OEEE)

en:
On the basis of the anonymised data for new registrations published by FEDRO, the Swiss Federal Office of Energy has evaluated key figures for alternatively powered passenger cars since 2015. Alternatively powered vehicles are vehicles that are not solely powered by a petrol or diesel internal combustion engine. In addition to aggregated annual key figures, this data set also contains quarterly and monthly market share figures as well as information regarding the individual cantons. Also, the Swiss Federal Office of Energy ranks the most popular all-electric and plug-in car models.

Legal basis: Energy Efficiency Ordinance (EnEO), Art. 11

de:
Auf Basis der vom ASTRA publizierten, anonymisierten Neuzulassungsdaten wertet das Bundesamt für Energie seit 2015 wichtige Kennzahlen zu den alternativ angetriebenen Personenwagen (PW) aus. Als alternativ angetriebenen Fahrzeuge gelten Fahrzeuge, die nicht ausschliesslich über einen Benzin- oder Diesel-Verbrennungsmotor angetrieben werden. Dieser Datensatz enthält neben aggregierten jährlichen Kennzahlen auch Quartals- und Monatszahlen der Marktanteile sowie Angaben zu den einzelnen Kantonen. Zudem wertet das Bundesamt für Energie bei den PW die beliebtesten vollelektrischen und Plug-In Modellen aus.

Rechtsgrundlage: Energieeffizienzverordnung (EnEV) Art. 11

it:
Sulla base dei dati anonimizzati sulle nuove immatricolazioni pubblicati dall'Ufficio federale delle strade (USTRA), dal 2015 l'Ufficio federale dell'energia analizza importanti indicatori relativi alle automobili a propulsione alternativa. Per veicoli a propulsione alternativa si intendono veicoli che non sono mossi esclusivamente da un motore a combustione a benzina o diesel. Oltre a indicatori annuali aggregati, questo set di dati contiene anche dati trimestrali e mensili relativi alle quote di mercato e indicazioni sui singoli Cantoni. Inoltre l'Ufficio federale dell'energia analizza i modelli di automobili completamente elettriche e plug-in più diffusi.

Base legale: ordinanza sull’efficienza energetica (OEEne), nello specifico l'articolo 11

alternative-antriebe

display_name: alternative-antriebe

elektrische-fahrzeuge

display_name: elektrische-fahrzeuge

elektromobilitat

display_name: elektromobilitat

hybridfahrzeuge

display_name: hybridfahrzeuge

personenwagen

display_name: personenwagen

ener

fr: Énergie

de: Energie

en: Energy

it: Energia

tran

fr: Transports

de: Verkehr

en: Transport

it: Trasporti

de: Bundesamt für Energie BFE

bundesamt-fur-energie-bfe

fr: Office fédéral de l'énergie OFEN

en: Swiss Federal Office of Energy SFOE

it: Ufficio federale dell'energia UFE

fr: L'Office fédéral de l'énergie (OFEN) est le centre de compétences du Département fédéral de l'environnement, des transports, de l'énergie et de la communication (DETEC) pour les questions liées à l'approvisionnement en énergie et à son utilisation.

de: Das Bundesamt für Energie (BFE) ist das Kompetenzzentrum für Fragen der Energieversorgung und der Energienutzung im Eidgenössischen Departement für Umwelt, Verkehr, Energie und Kommunikation (UVEK).

en: The Swiss Federal Office of Energy (SFOE) is the country's competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (DETEC).

it: L'Ufficio federale dell'energia (UFE) è il centro di competenza in materia di approvvigionamento e di impiego dell'energia in seno al Dipartimento federale dell'ambiente, dei trasporti, dell'energia e delle comunicazioni (DATEC).


de: regierungsratswahlen nationalratswahlen ersatzwahl vorname wahlresultate geschlecht standeratswahlen jahrgang wahlarchiv name landratswahlen wahlergebnisse

de: turtle

media_type: text/turtle

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (turtle)

format: RDF Turtle

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (n3)

de: json

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (json)

de: jsonld

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (jsonld)

format: JSON-LD

de: xls

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (xls)

de: jsonl

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (jsonl)

de: csv

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (csv)

de: rdfxml

media_type: application/rdf+xml

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (rdfxml)

format: RDF XML

de: parquet

de: Eidgenössische und kantonale Wahlen (seit 2003): Kandidierendenresultate nach Gemeinde (parquet)

format: PARQUET

de: Kandidierendenresultate auf Ebene GemeindeZu weiteren Kandidierendenresultaten[Kandidierendenresultate auf Ebene Kanton (Nationalratswahlen) bzw. Wahlkreis (Landratswahlen)](https://data.bl.ch/explore/dataset/12770)[Herkunft der Kandidierendenstimmen auf Ebene Gemeinde](https://data.bl.ch/explore/dataset/12790)

ersatzwahl

display_name: ersatzwahl

geschlecht

display_name: geschlecht

jahrgang

display_name: jahrgang

landratswahlen

display_name: landratswahlen

name

display_name: name

nationalratswahlen

display_name: nationalratswahlen

regierungsratswahlen

display_name: regierungsratswahlen

standeratswahlen

display_name: standeratswahlen

vorname

display_name: vorname

wahlarchiv

display_name: wahlarchiv

wahlergebnisse

display_name: wahlergebnisse

wahlresultate

display_name: wahlresultate

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

de: kanton-basel-landschaft

kanton-basel-landschaft

fr: Canton de Bâle-Campagne

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

it: Cantone di Basilea-Campagna

en:
The Canton of Basel-Country publishes open datasets of cantonal offices and agencies.
Further information at https://ogd.bl.ch/

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

value: BL - DCAT


nutzungsplanung-planungszonen

regi

fr: Régions et villes

de: Regionen und Städte

en: Regions and cities

it: Regioni e città

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

title_for_slug: nutzungsplanung-planungszonen

de: bewilligungen eigentumsbeschrankungoreb nutzungsplanung raumplanung zonenplan

author: Kanton Luzern, Abteilung Geoinformation

fr: geocat.ch permalien

de: geocat.ch Permalink

en: geocat.ch permalink

it: geocat.ch link permanente

protocol: https

de: Datenshop

de: Produktansicht Geodatenshop

de: Mit Planungszonen wird sichergestellt, dass in den betroffenen Gebieten nur Vorhaben zulässig sind, die der geplanten künftigen Nutzung nicht widersprechen.

spatial: Kanton Luzern

de: Kanton Luzern, Abteilung Geoinformation

fr: Géoinformation du canton de Lucerne

de: Geoinformation Kanton Luzern

en: Geoinformation Canton of Lucerne

it: Geoinformazione del Cantone di Lucerna

fr: La géoinformation du canton de Lucerne est responsable de la collecte, du traitement et de la gestion des données à référence spatiale. Elle dirige, coordonne et surveille les travaux de la géoinformation et de la mensuration officielle.

en: Geoinformation of the Canton of Lucerne is responsible for the collection, processing and management of spatial data. It manages, coordinates and monitors the work of geoinformation and of the cadastral surveying.

de: Die Geoinformation des Kantons Luzern ist für die Erhebung, Verarbeitung und Verwaltung von raumbezogenen Daten zuständig. Sie leitet, koordiniert und überwacht die Arbeiten der Geoinformation und der amtlichen Vermessung.

it: La Geoinformation del Cantone di Lucerna è responsabile della raccolta, dell'elaborazione e della gestione dei dati territoriali. Gestisce, coordina e monitora il lavoro della geoinformazione e della misurazione ufficiale.

value: LU-Kt - Geocat Harvester

de: Nutzungsplanung: Planungszonen


weather-station-davos-wolfgang

maintainer: Jörg Wieder

title_for_slug: weather-station-davos-wolfgang

en: relative-humidity raclets weather pressure temperature

en: Weather Station Davos Wolfgang

en: The data file contains date and time (YYYY-MM-DD hh:mm:ss) in UTC, temperature (°C), relative humidity (%), pressure (hPa) at 10 m above ground and above sea level. The data was averaged over 10 minutes.

en: The dataset contains weather parameters measured at Davos Wolfgang (LON: 9.853594, LAT: 46.835577).

pressure

display_name: pressure

raclets

display_name: raclets

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

weather

display_name: weather

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport

envidat

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

it: EnviDat: il portale dei dati ambientali

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

value: Envidat Harvester


causal-effect-of-lup

maintainer: EnviDat Support

title_for_slug: causal-effect-of-lup

en: psm-did land-use-planning land-use-change annual-effect plan-evaluation

en: causal-effect-of-lup

media_type: application/zip

en:
Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities
PSM_DID.R can re-produce the results

format: ZIP

en:
Title: Does zoning contain built-up land expansion? Causal evidence from Zhangzhou City, China.

Research objective: Built-up land zoning is an imporatant policy measure of land use planning (LUP) to contain built-up land expansion in China. We used a difference-indifference model with propensity score matching to estimate the average and annual effect of built-up land zoning on built-up land expansion in Zhangzhou City, China between 2010 and 2020.

Data: Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020.
XZQDM2 is villages' unique administrative ID;
Area is the land area of village i;
Dis2water is the Euclidean distance from village i to the nearest waterbody;
Dis2coastl is the Euclidean distance from village i to the nearest coastline;
Dis2city is the the Euclidean distance from village i to the city center;
Dis2county is the the Euclidean distance from village i to the nearest county center;
Elevation is the the average elevation within village i;
Dis2road is the the Euclidean distance from village i to the nearest road;
Nei_Built_ is the the area of built-up land (Nei Built.upit) in the neighboring villages of village i in year t;
Treated is a binary variable, Treated = 1 to the villages that were partially or entirely located inside the development-permitted zones, and Treated = 0 to the villages that were entirely located outside the development-permitted zones;
Intensity is the percentage of land that was assigned to the development-permitted zones in village i;
Year represent the year in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020;
BuLE is the dependent variable, representing built-up land expansion in village i in year t;
Town is town' unique administrative ID.

Method: First, we employed propensity score matching to overcome the selection bias and satisfy the parallel trend
assumption. Second, we built four Difference-in-Difference models to estimate the average and annual effect.

annual-effect

display_name: annual-effect

land-use-change

display_name: land-use-change

land-use-planning

display_name: land-use-planning

plan-evaluation

display_name: plan-evaluation

psm-did

display_name: psm-did

en: Causal effect of LUP


en: community-structure climate-change environmental-dna fish arctic

en: Data and code to reproduce the analysis of "Community structure and range shifts in Arctic marine fish under climate change"

en: Zip file with data and code

en:
Data and code for the paper published in Ecography: Community structure and range shifts in Arctic marine fish under climate change
Abstract:
Arctic marine ecosystems are rapidly transforming due to climate change. Warming temperatures and shrinking sea ice are enabling boreal fish to expand northward, possibly disturbing cold-adapted Arctic species assemblages. Species range shifts have been documented in the Bering and Barents Seas, raising concerns about ecosystem restructuring. Range shifts are especially difficult to detect in the Arctic due to sparse and inconsistent data. Here, we studied fish composition from eDNA water samples taken in East Greenland, Svalbard, the Barents Sea, and the Kara Sea during the TOPtoTOP and Arctic Century expeditions. We examined the environmental drivers of fish community structure using global dissimilarity models. We calculated the decadal rate of temperature change to identify the fastest-changing areas. We compared fish detections from eDNA with published historical records for the Kara Sea to assess possible range expansions. We found that temperature was the main factor influencing the taxa turnover of fish communities, with Gadidae and Liparis sp. driving the greatest compositional differences. Over the past 30 years, temperatures increased by 0.2 to 0.6°C per decade at our study sites, with the highest increases in western Svalbard and the lowest in the eastern Kara Sea. Despite the apparent dependence on temperature, we identified only one species detected outside its known latitudinal range, and five species in the Kara Sea with recent occurrences or representing an extended distribution. Our study suggests that temperature, the main driver of fish community assembly, is increasing rapidly in the Arctic, and a few species have likely already shifted recently, or at least their detections are new in some areas. While these detections cannot be definitively linked to range shifts, our results highlight the need to improve monitoring of high-latitude fish communities to detect and predict future ecosystem changes.
Article:
Marques, V., Fopp, F., Jaquier, M., Ellingsen, K. E., Yoccoz, N., Jucker, M., ...Pellissier, L. (2025). Community structure and range shifts in Arctic marine fish under climate change. Ecography, e8014. doi: 10.1002/ecog.08014
Data:
The resource contains a zip file with the entire project structure.
Data README:
 Intro
This repo presents data and code associated with the paper "Community structure and range shifts in Arctic marine fish under climate change" published in Ecography
 Usage
Launch the `main.R` script to reproduce the entire analysis.
It executes code blocks to create the data necessary for the analysis and then creates the figures.
💣 attention, total size is expected ~20 Go and the script will query the CMEMS database to fetch environmental data
 Tools
To make the scripts run, you need R, R packages (see session info below), python3, and the copernicusmarine python tool (https://pypi.org/project/copernicusmarine/).

 SessionInfo
```
sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS 15.5
Matrix products: default
BLAS:  /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Zurich
tzcode source: internal
attached base packages:
[1] stats   graphics grDevices
[4] utils   datasets methods
[7] base
other attached packages:
 [1] lwgeom_0.2-14
 [2] metR_0.15.0
 [3] ggtext_0.1.2
 [4] scico_1.5.0
 [5] ggnewscale_0.5.0
 [6] colorspace_2.1-1
 [7] climetrics_1.0-15
 [8] rts_1.1-14
 [9] xts_0.14.0
[10] zoo_1.8-12
[11] ggpubr_0.6.0
[12] adespatial_0.3-23
[13] ggspatial_1.1.9
[14] colorplaner_0.1.4
[15] ape_5.8
[16] factoextra_1.0.7
[17] corrgram_1.14
[18] FactoMineR_2.11
[19] betapart_1.6
[20] gdm_1.5.0-9.1
[21] terra_1.7-78
[22] rnaturalearth_1.0.1
[23] ggrepel_0.9.5
[24] vegan_2.6-6.1
[25] lattice_0.22-6
[26] permute_0.9-7
[27] cowplot_1.1.3
[28] tidyterra_0.6.1
[29] sf_1.0-16
[30] egg_0.4.5
[31] gridExtra_2.3
[32] patchwork_1.2.0
[33] viridis_0.6.5
[34] viridisLite_0.4.2
[35] mgcv_1.9-1
[36] nlme_3.1-165
[37] MBA_0.1-0
[38] reshape2_1.4.4
[39] conflicted_1.2.0
[40] lubridate_1.9.3
[41] forcats_1.0.0
[42] stringr_1.5.1
[43] dplyr_1.1.4
[44] purrr_1.0.2
[45] readr_2.1.5
[46] tidyr_1.3.1
[47] tibble_3.2.1
[48] ggplot2_3.5.1
[49] tidyverse_2.0.0
[50] devtools_2.4.5
[51] usethis_2.2.3
loaded via a namespace (and not attached):
 [1] splines_4.4.0
 [2] later_1.3.2
 [3] bitops_1.0-7
 [4] minpack.lm_1.2-4
 [5] XML_3.99-0.16.1
 [6] lifecycle_1.0.4
 [7] rstatix_0.7.2
 [8] doParallel_1.0.17
 [9] MASS_7.3-60.2
 [10] flashClust_1.01-2
 [11] backports_1.5.0
 [12] magrittr_2.0.3
 [13] rmarkdown_2.27
 [14] yaml_2.3.8
 [15] remotes_2.5.0
 [16] httpuv_1.6.15
 [17] sp_2.1-4
 [18] sessioninfo_1.2.2
 [19] pkgbuild_1.4.4
 [20] mapproj_1.2.11
 [21] pbapply_1.7-2
 [22] DBI_1.2.3
 [23] RColorBrewer_1.1-3
 [24] ade4_1.7-22
 [25] maps_3.4.2
 [26] abind_1.4-5
 [27] pkgload_1.3.4
 [28] RCurl_1.98-1.14
 [29] itertools_0.1-3
 [30] yaImpute_1.0-34
 [31] rcdd_1.6
 [32] units_0.8-5
 [33] adegenet_2.1.10
 [34] codetools_0.2-20
 [35] xml2_1.3.6
 [36] adephylo_1.1-16
 [37] DT_0.33
 [38] tidyselect_1.2.1
 [39] RNeXML_2.4.11
 [40] raster_3.6-26
 [41] farver_2.1.2
 [42] jsonlite_1.8.9
 [43] e1071_1.7-14
 [44] phylobase_0.8.12
 [45] ellipsis_0.3.2
 [46] iterators_1.0.14
 [47] emmeans_1.10.4
 [48] systemfonts_1.1.0
 [49] foreach_1.5.2
 [50] progress_1.2.3
 [51] tools_4.4.0
 [52] ragg_1.3.2
 [53] snow_0.4-4
 [54] Rcpp_1.0.13
 [55] glue_1.8.0
 [56] xfun_0.44
 [57] withr_3.0.0
 [58] fastmap_1.2.0
 [59] boot_1.3-30
 [60] latticeExtra_0.6-30
 [61] fansi_1.0.6
 [62] spData_2.3.1
 [63] digest_0.6.35
 [64] timechange_0.3.0
 [65] R6_2.5.1
 [66] mime_0.12
 [67] estimability_1.5.1
 [68] wk_0.9.1
 [69] textshaping_0.4.0
 [70] jpeg_0.1-10
 [71] utf8_1.2.4
 [72] generics_0.1.3
 [73] data.table_1.15.4
 [74] class_7.3-22
 [75] prettyunits_1.2.0
 [76] httr_1.4.7
 [77] htmlwidgets_1.6.4
 [78] scatterplot3d_0.3-44
 [79] spdep_1.3-5
 [80] pkgconfig_2.0.3
 [81] gtable_0.3.5
 [82] picante_1.8.2
 [83] adegraphics_1.0-21
 [84] htmltools_0.5.8.1
 [85] carData_3.0-5
 [86] profvis_0.3.8
 [87] multcompView_0.1-10
 [88] scales_1.3.0
 [89] leaps_3.2
 [90] png_0.1-8
 [91] doSNOW_1.0.20
 [92] geometry_0.4.7
 [93] rnaturalearthhires_1.0.0.9000
 [94] knitr_1.47
 [95] rstudioapi_0.16.0
 [96] rncl_0.8.7
 [97] uuid_1.2-0
 [98] tzdb_0.4.0
 [99] checkmate_2.3.1
[100] coda_0.19-4.1
[101] magic_1.6-1
[102] proxy_0.4-27
[103] cachem_1.1.0
[104] KernSmooth_2.23-24
[105] parallel_4.4.0
[106] miniUI_0.1.1.1
[107] s2_1.1.6
[108] pillar_1.9.0
[109] grid_4.4.0
[110] vctrs_0.6.5
[111] urlchecker_1.0.1
[112] promises_1.3.0
[113] car_3.1-2
[114] xtable_1.8-4
[115] cluster_2.1.6
[116] evaluate_0.24.0
[117] mvtnorm_1.2-5
[118] cli_3.6.3
[119] compiler_4.4.0
[120] rlang_1.1.4
[121] crayon_1.5.2
[122] ggsignif_0.6.4
[123] labeling_0.4.3
[124] interp_1.1-6
[125] classInt_0.4-10
[126] plyr_1.8.9
[127] fs_1.6.4
[128] stringi_1.8.4
[129] deldir_2.0-4
[130] munsell_0.5.1
[131] Matrix_1.7-0
[132] hms_1.1.3
[133] seqinr_4.2-36
[134] shiny_1.8.1.1
[135] gridtext_0.1.5
[136] igraph_2.0.3
[137] broom_1.0.6
[138] memoise_2.0.1
[139] fastmatch_1.1-4
```
 Data content and reproducibility
Uncleaned raw table out of the bioinformatics pipeline can be found concatenated in `outputs/table_raw_before_cleaning.csv`, yet we caution readers to properly read the cleaning scripts should they wish to reproduce our analysis and this file is presently uncleaned.

arctic

display_name: arctic

climate-change

display_name: climate-change

community-structure

display_name: community-structure

environmental-dna

display_name: environmental-dna

fish

display_name: fish

en: Data and code for Community structure and range shifts in Arctic marine fish under climate change


alan-spongy-moth-laboratory-experiment

title_for_slug: alan-spongy-moth-laboratory-experiment

en: insect-development lab-experiment spongy-moth light-pollution alan

en: R code for the pupation analysis and producing the graphics.

format: OCTET

en: Raw data modified and used for the Bodymass Analysis

en: R code for the Cox hazard analysis and producing the Kaplan Meier survival curves for both Mortality and Pupation.

en: R code for the bodymass analysis and producing the graphics.

en: Raw data used for the Pupation and Cox Hazard/Kaplan Meier Analysis.

en:
 Data and Code for ALAN Spongy Moth lab experiment
In this repository you will find all the raw datasets used for the data analysis performed in our paper about the impacts of artificial light at night (ALAN) on the development of Spongy Moth caterpillars. The files are attached as a csv file.
Also attached is all the R-code later used for the statistical analysis and for generating the graphics displayed in the paper. This files are attached as an R.file.

alan

display_name: alan

insect-development

display_name: insect-development

lab-experiment

display_name: lab-experiment

light-pollution

display_name: light-pollution

spongy-moth

display_name: spongy-moth

en: ALAN Spongy Moth Laboratory Experiment


maintainer: Daniel Scherrer

en: gui treemig forest-model forest-dynamics r-package spatial-modelling forest land-use bioclimatic-variables species-interaction species-migration

en: Tutorial for using the TreeMig framework; updated

en: TreeMig Simulation Environment and Input Data

en:
The zip file consists of a R-script to provide the framework, an example simulation environment and a set of input data.
- The R-script installAndRunTreeMigWrapperAndGUI.R installs the R-package, links to the input data and starts the graphical user interface.
- The gridded input datasets in TMInputData are specifically tailored to Switzerland and have the same coordinate reference system and a congruent 200m spatial resolution. They consist of climate, topographic, land use and soil data. For details see TMInputDataDetails.pdf.
- TMEnvironment is an example simulation environment, i.e. a set of hierarchically structured folders. For the first example simulation of the tutorial it contains the
  - the TreeMig executables for MacOS, Linux and Windows
  - simulation control files that define the setup and input files of the simulation (in folder C)
  - species parameters (in folder P)
  - bioclimatic data (in folder E)
  - folder R for results
  - folder Plots for plots of the simulation results.
  - This environment can be also used for the subsequent simulations of the tutorial.
- Some additional R-scripts demonstrate more complex applications described in the tutorial, e.g. coupling to another model.

en: TreeMig Tutorial

en: Description input data

en: Details where the input data come from and how they have been processed

en:
Starter kit for the TreeMig framework that allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions.
The starter kit consists of a set of climate, land-use, topography and soil property input data for Switzerland, a script for installing the framework and running the GUI of the framework with the link to the input data, a tutorial covering a range of simulation examples for Switzerland and a transect through Europe, and an associated example simulation environment containing the model executables and other model inputs.

bioclimatic-variables

display_name: bioclimatic-variables

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-model

display_name: forest-model

gui

display_name: gui

land-use

display_name: land-use

r-package

display_name: r-package

spatial-modelling

display_name: spatial-modelling

species-interaction

display_name: species-interaction

species-migration

display_name: species-migration

treemig

display_name: treemig

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Starter Kit for the TreeMig framework v1 for easy simulation of spatio-temporal forest dynamics


modeling-snow-failure-with-dem

title_for_slug: modeling-snow-failure-with-dem

en: snow-failure snow-avalanche snow-micro-mechanics discrete-element-modelling snow

en: Dataset

en: The zip file contains the data underlying the figures presented in Bobillier et al. (2019). The figures can be reproduced with the python file, which is also provided.

mimetype: application/zip

en: Python file

en: Python file to reproduce the figures in Bobillier et al. (2019)

mimetype: text/x-python

en: Read-me

en: The read-me file contains a description of all the data provided in the zip file.

en: This data set includes the modeling results described in the research article by Bobiller et al. (2020). All the figures in the article can be reproduced with the data provided.

discrete-element-modelling

display_name: discrete-element-modelling

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-failure

display_name: snow-failure

snow-micro-mechanics

display_name: snow-micro-mechanics

en: Modeling snow failure with DEM


en: red-list range-size bryophytes endemic europe conservation-priority rarity

en: This dataset provides data on the occurrence of 672 European bryophyte species in European countries or territories. All species which are considered threatened or near threatened according to the European Red List (Hodgetts et al. 2019) are included (553 species). Further, all species evaluated in the European Red List assessed as LC, DD, NE and EX, which at the same time are either endemic, near endemic or globally rare, are included (119 species). Therefore, the list contains not only all European bryophyte species that are threatened or near threatened, but also all species endemic or near endemic to Europe as well as all globally rare species occurring in Europe. For each of the 553 threatened or near threatened species, we provide a conservation a priority score which was calculated based the Red List status and the proportion of the European population of the global population or the global rarity of the species. For details on the prioritisation approach see Bisang et al. (2025).

bryophytes

display_name: bryophytes

conservation-priority

display_name: conservation-priority

endemic

display_name: endemic

europe

display_name: europe

range-size

display_name: range-size

rarity

display_name: rarity

red-list

display_name: red-list

en: Priority ranking for the conservation of all European bryophyte species - dataset


en: colombia fish edna vert01 metabarcoding magdalena teleo

en: Data access

en: Please cyberduck to download for the moment

en:
Monitoring of vertebrates of the lower Magdalena river through eDNA metabarcoding

The Magdalena River basin harbors a large biodiversity of vertebrates, with numerous endemic species, many of which are threatened. Here, we used environmental DNA (eDNA) metabarcoding, with two primer sets targeting different regions of the mitochondrial DNA 12S ribosomal RNA gene, to detect vertebrate diversity in the Magdalena River. We detected a total of 159 vertebrate taxa, not only aquatic but also terrestrial, arboreal, and aerial. The diversity of these vertebrates increases in relation to the proximity to the river mouth with a change in the composition of the assemblage of aquatic vertebrates detected. We conclude that eDNA metabarcoding allows characterizing vertebrate assemblages in large rivers, assessing conservation status, and elucidating biodiversity patterns with minimal ecosystem disturbance. Samples were taken at the sides of the river or in the center using a boat. At each station, we performed two filtration replicates using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 1 hours, during which a maximum of 30 liters of water were filtered through each capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.

Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

colombia

display_name: colombia

edna

display_name: edna

fish

display_name: fish

magdalena

display_name: magdalena

metabarcoding

display_name: metabarcoding

teleo

display_name: teleo

en: Environmental DNA Freshwater Colombia Magdalena 2022


dataset-on-new-snow-water-equivalent

title_for_slug: dataset-on-new-snow-water-equivalent

en: snowfall new-snow precipitation data-assimilation snow-modelling

en: The .zip file contains all data as described in this repository and associated publication. The .zip file contains a readme file describing its content in detail.

en:
This dataset includes quality-controlled measurements of new snow depth (HN), new snow water equivalent (HNW), snow depth (HS), and snow water equivalent (SWE) from 41 stations located in Switzerland for the period from 2016-09-01 to 2022-08-31.
These data are the basis of the following publication: Magnusson J., Cluzet B., Quéno L., Mott R., Oberrauch M., Mazzotti G., Marty C., Jonas T., 2025, Evaluating methods to estimate the water equivalent of new snow from daily snow depth recordings, Cold Regions Science and Technology, https://doi.org/10.1016/j.coldregions.2025.104435.
Abstract
The water equivalent of new snow (HNW) plays a crucial role in various fields, including hydrological modeling, avalanche forecasting, and assessing snow loads on structures. However, in contrast to snow depth (HS), obtaining HNW measurements is challenging as well as time-consuming and is hence rarely measured. Therefore, we assess the reliability of two semi-empirical methods, HS2SWE and ΔSNOW, for estimating HNW. These methods are designed to simulate continuous water equivalent of the snowpack (SWE) from daily HS only, with changes in SWE yielding daily HNW estimates. We compare both parametric methods against HNW predictions from a physics-based snow model (FSM2oshd) that integrates daily HS recordings using data assimilation. Our findings reveal that all methods exhibit similar performance, with relative biases of less than ~3 % in replicating SWE observations commonly used for model evaluations. However, the ΔSNOW model tends to underestimate daily HNW by ~17 %, whereas HS2SWE and FSM2oshd combined with a particle filter data assimilation scheme provide nearly unbiased estimates, with relative biases below ~5 %. In contrast to the parsimonious parametric methods, we show that the physics-based approach can yield information about unobserved variables, such as total solid precipitation amounts, that may differ from HNW due to concurrent melt. Overall, our results underscore the potential of utilizing commonly available daily HS data in conjunction with appropriate modeling techniques to provide valuable insights into snow accumulation processes. Our study demonstrates that daily SWE observations or supplementary measurements like HNW are important for validating the day-to-day accuracy of simulations and should ideally already be incorporated during the calibration and development of models.
Acknowlegements
These data were recorded by SLF observers and staff members. Their contribution is gratefully acknowledged.

data-assimilation

display_name: data-assimilation

new-snow

display_name: new-snow

precipitation

display_name: precipitation

snow-modelling

display_name: snow-modelling

snowfall

display_name: snowfall

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Dataset on new snow water equivalent


maintainer: Yves Bühler

en: snow-depth-mapping dsm photogrammetry wingtra orthophoto uav drone-data

en: Data Access

en:
- DSM (10 cm resolution)
- Ortho (3 cm resolution)
- HS (10 cm resolution)
- original RGB drone images
- Agisoft Metashape Processing Report

All products are also available as a cloud optimized geotiff.

en: To map and assess snow depth on different dates, 9 flights were conducted in the winter season of 2020/21 at the Latschüelfurgga in Davos. The data was captured with a Sony RX1R II mounted on a Wingtra drone and was processed with the Agisoft Metashape software. High-resolution DSMs, orthomosaics and snow height rasters, as well as the original RGB images from each flight are available.

drone-data

display_name: drone-data

dsm

display_name: dsm

orthophoto

display_name: orthophoto

photogrammetry

display_name: photogrammetry

snow-depth-mapping

display_name: snow-depth-mapping

uav

display_name: uav

wingtra

display_name: wingtra

en: Photogrammetric Drone Data Latschuelfurgga


maintainer: Amelie Fees

en: glide-snow-avalanche avalanche avalanche-activity snowpack-simulation time-lapse-photography

en: SNOWPACK simulations

en: SNOWPACK simulations (.pro and .smet) covering season 2008/09 to 2021/22 at 10 virtual locations on Dorfberg. The locations correspond to the most common glide-snow avalanche paths.

en: README

en: README.txt explaining the dataset and columns of tables in more detail.

en: Glide distances for opening glide-cracks

en: This folder contains all glide-cracks where glide-distances were extracted from time-lapse photographs. Glide-distances were calculated in x-direction (width) and y-direction (downslope, length) by georeferencing the images.

en: Glide-snow avalanche activity

en: Table that contains all glide-snow avalanche events that were detected in time-lapse photographs (season 2008/09 to 2021/22). The columns are explained in the README.txt

en:
This dataset includes the processed data of the glide-snow avalanche activity and dynamics on Dorfberg (Davos, Switzerland) covering seasons 2008/09 to 2021/22. This dataset was described in the research article:

Fees, A., van Herwijnen A., Altenbach, M., Lombardo, M., Schweizer, J.: Glide-snow avalanche characteristics at different time-scales extracted from time-lapse photography, Annals of Glaciology, 91

We extracted the dynamics of opening glide-cracks and the glide-snow avalanche activity from time-lapse photographs. Glide-snow avalanches were separated into surface and interface events using the liquid water content which was simulated with SNOWPACK at 10 virtual stations on Dorfberg.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

glide-snow-avalanche

display_name: glide-snow-avalanche

snowpack-simulation

display_name: snowpack-simulation

time-lapse-photography

display_name: time-lapse-photography

en: Glide-snow avalanche activity on Dorfberg, Davos, Switzerland


photogrammetric-drone-data-schurlialp

title_for_slug: photogrammetric-drone-data-schurlialp

en: photogrammetry wingtra uav drone-data orthophoto dsm

en:
- 10 cm DSM
- 10 cm HS
- 3 cm orthophoto
- original RGB images
- Agisoft Metashape Processing Report

All of the products are also available as a cloud optimized geotiff.

en: The data was collected on 16.04.2021 and on 28.05.2021 with a Wingtra Gen II and a Sony RX1 II RGB sensor to obtain snow depth and distribution data. Following the data collection, the data was processed with Agisoft Metashape. A 10cm DSM, a 10cm snow depth raster, a 3mm orthophoto and the original drone images are available for download.

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Photogrammetric Drone Data Schürlialp


en: acclimation invasive-species respiration photosynthesis leaf spac-model

en: Thermal tolerance of T. fortunei.zip

en:
This dataset originates from a two-year transplant experiment conducted across a temperature gradient in Europe (mean annual temperatures: 8.4–21.8 °C). It includes physiological measurements of one invasive palm species (Trachycarpus fortunei) and two co-occurring native species (Ilex aquifolium and Tilia cordata). The dataset captures plant acclimation responses to air temperature, focusing on photosynthetic and respiratory traits that influence carbon balance.
Variables that can be extracted:
- Optimal temperature of photosynthesis (Topt)
- Photosynthetic rate at optimal temperature (Aopt)
- Thermal breadth of photosynthesis (T80)
- Respiration rate at 25 °C (R25)
- Temperature sensitivity of respiration (Q10)
Raw data are reported for all species across multiple sites and time points, enabling assessment of their acclimation capacity to warming. The dataset supports comparisons of functional plasticity between an invasive species and native taxa, providing insights into climate responses and invasion ecology.

acclimation

display_name: acclimation

invasive-species

display_name: invasive-species

leaf

display_name: leaf

photosynthesis

display_name: photosynthesis

respiration

display_name: respiration

spac-model

display_name: spac-model

en: Thermal acclimation fails to confer a carbon budget advantage to invasive species over natives


ceilometer-klosters

title_for_slug: ceilometer-klosters

en: cloud-base-height klosters ceilometer raclets vertical-visibility

en: Ceilometer data Klosters

en: Ceilometer installed at Klosters measuring cloud base height, cloud cover and backscatter profile. The time resolution is 30 seconds, with time given in number of days from January 0, 0000, UTC. More information on the variables in the manufacturer manual.

en: Cloud base height (m) and vertical visibility (m) were measured with the VAISALA Ceilometer CL31 in Klosters (LON: 9.880413, LAT: 46.869019). The CL31 is an instrument with constant reliability for all weather conditions and simultaneous detection of three cloud layers in heights up to 7.6 km.

ceilometer

display_name: ceilometer

cloud-base-height

display_name: cloud-base-height

klosters

display_name: klosters

raclets

display_name: raclets

vertical-visibility

display_name: vertical-visibility

en: Ceilometer Klosters


maintainer: Christoph Marty

en: hydrology snowfall water-cycle snow climate-change-impacts

en: Synthesis report chapter

en: DORA Persistent URL

en:
This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). An important feature of snow cover is the fact that its volume and duration is subject to large year-to-year fluctuations. As frozen precipitation, snow cover is nothing other than a natural water reservoir that delays precipitation to runoff and is thus of outstanding importance for the seasonal water balance in Switzerland. Over a whole year, approximately 40% (22 km3) of the annual runoff currently comes from snow melting and only 1% from glacier melting. Typically, the snow cover in the Alpine region builds up over the autumn and winter months, reaches its maximum between February and May, depending on the altitude, and dominates the runoff processes during melting in the following spring and summer months.
Due to the great dependence on minus temperatures and precipitation, the snow cover reacts sensitively to temperatures above 0° Celsius and more or less precipitation. Due to climate change and the associated warming, the proportion of precipitation that falls as snow decreases measurably. In addition to this reduction in snowfall, the warmer temperatures also cause the snow cover to melt more quickly. The decline in snowfall has so far mainly affected lower altitudes, where winter temperatures often reach positive levels.
As climate change progresses, this trend is likely to continue and above all affect higher zones. Even at higher altitudes, the snow cover will then start later, melt away earlier and is increasingly no longer permanently present. This development will also have an effect on the water bodies. Today nival regimes, i.e. regimes shaped by snow, are shifting towards pluvial regimes, i.e. regimes dominated by rain. Overall, winter runoff increases, summer runoff decreases. By the end of the century, the proportion of runoff from snowmelt will decrease throughout Switzerland, albeit to a lesser extent than the proportion from glacier melt.

climate-change-impacts

display_name: climate-change-impacts

hydrology

display_name: hydrology

snow

display_name: snow

snowfall

display_name: snowfall

water-cycle

display_name: water-cycle

en: Snow and the water cycle in a changing climate


en: air-temperature wind-speed precipitation shortwave-radiation relative-humidity time-series speed2zero meteo-station climate-change

en: Data link

en:
This dataset provides 50 years of seasonal synthetic hourly time series for five meteorological variables: incoming shortwave radiation, total precipitation, relative humidity, 2-meter air temperature and wind speed.

The data are generated from observational records (1990–present) from nine MeteoSwiss stations (ABO, BAS, BER, LUG, PUY, SCU, SIO, STG, WFJ). We use a sampling approach that preserves both the temporal structure and inter-variable dependencies. Specifically, the time series are constructed by drawing 7-day blocks from historical observations, ensuring realistic short-term variability and maintaining the physical coherence between variables.

The synthetic sequences are constrained to follow daily temperature change trajectories corresponding to three future climate scenarios for the period 2040–2070: RCP2.6, RCP8.5 and RCP0: a counterfactual scenario with no long-term warming trend, but with temperature variability consistent with the RCP2.6 one.
The temperature constraints are derived from projections downscaled at the staiton level, available at: https://www.envidat.ch/#/metadata/climate-change-scenarios-at-hourly-resolution

air-temperature

display_name: air-temperature

climate-change

display_name: climate-change

meteo-station

display_name: meteo-station

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

shortwave-radiation

display_name: shortwave-radiation

time-series

display_name: time-series

wind-speed

display_name: wind-speed

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

en: Meteorological Time Series Aligned with Projected Temperature Changes


maintainer: James W. Kirchner

en: de-mixing transfer-function irfnnhsr deconvolution arma-noise impulse-response-function time-series-analysis system-identification irf nonlinear-deconvolution greens-function

en: Benchmark demonstration scripts and results

en: README file for IRFnnhs.R and benchmark demonstration scripts

en: Impulse Response Function script

en:
The R script IRFnnhs.R, which efficiently estimates impulse response functions for environmental systems that are nonlinear, nonstationary, or heterogeneous, based on their input and output time series.

Scripts and results for a series of benchmark tests are also provided, to accompany Kirchner, J.W., Impulse response functions for heterogeneous, nonstationary, and nonlinear systems, estimated by deconvolution and demixing of noisy time series, _Sensors_, 22(9), 3291, https://doi.org/10.3390/s22093291, 2022.

arma-noise

display_name: arma-noise

de-mixing

display_name: de-mixing

deconvolution

display_name: deconvolution

greens-function

display_name: greens-function

impulse-response-function

display_name: impulse-response-function

irf

display_name: irf

irfnnhsr

display_name: irfnnhsr

nonlinear-deconvolution

display_name: nonlinear-deconvolution

system-identification

display_name: system-identification

time-series-analysis

display_name: time-series-analysis

transfer-function

display_name: transfer-function

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: Impulse response functions for nonlinear nonstationary and heterogeneous systems


maintainer: Matthias Haeni

en: long-term relative-humidity precipitation swiss-forest-lab meteorology par temperature meteo wind-speed climate-change

en: Data plot of the forest station (CLB)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Data plot of the field station (CLF)

en: Data file.

en: Site aerial photo (Celerina)

en: Site aerial photo from both Celerina stations. Source: Google. 2016. Site aerial photo from both Celerina stations. Retrieved November 11, 2016, from https://www.google.ch/maps

mimetype: image/jpeg

en: Site photo of the forest station (CLB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Site photo of the field station (CLF)

en: Site phote of the field station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Celerina in Switzerland where one station is located within a natural coniferous forest stand (CLB) with Swiss pine (_Pinus cembra_; 210-250 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, CLF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Celerina is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

en: Celerina, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards