fr: femme genre homme travail-et-remuneration

de: mann geschlecht arbeit-und-erwerb frau

en: woman gender man work-and-income

it: donna genere lavoro-e-reddito uomo

fr: Principaux indicateurs du marché du travail, évolution

fr: Ce dataset présente l'évolution des principaux indicateurs du marché du travail, depuis 1960.

de: Dieses Dataset präsentiert die Entwicklung der wichtigsten Arbeitsmarktindikatoren, seit 1960.

arbeit-und-erwerb

display_name: arbeit-und-erwerb

lavoro-e-reddito

display_name: lavoro-e-reddito

lavur-e-gudogn

display_name: lavur-e-gudogn

man

display_name: man

mann

display_name: mann

travail-et-remuneration

display_name: travail-et-remuneration

work-and-income

display_name: work-and-income

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

it: Economia e finanze

fr: Office fédéral de la statistique OFS

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.


fr: genre femme homme travail-et-remuneration

de: arbeit-und-erwerb frau mann geschlecht

en: woman gender work-and-income man

it: uomo genere lavoro-e-reddito donna

author: BFS/OFS

state: active

type: dataset

de: Nach ausgewählten Nationalitäten: Erwerbstätige nach Wirtschaftsabschnitten und Geschlecht

format: XLS

fr: Selon différentes nationalités: personnes actives occupées par sections économiques et sexe

media_type: text/html

format: HTML

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

uomo

display_name: uomo

woman

display_name: woman

spatial: Schweiz

en: Economy and finance

bundesamt-fur-statistik-bfs

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.

political_level: confederation

type: organization

approval_status: approved

key: guid

key: uri

value: BFS – DCAT Harvester


de: Durchschnittlicher Mietpreis pro m2 in Franken nach Gebäudekategorie und Anzahl Zimmer

it: Affitto medio per m2 in franchi secondo la categoria di efidifico e il numero di locali

fr: Loyer moyen par m2 en francs selon la catégorie de bâtiment et le nombre de pièces

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


it: Assicurazione complementare: Premi dell'assicurazione malattie complementare per prodotto, tassi di variazione e indici

fr: Assurance complémentaire: primes d'assurance-maladie par produit, variations et indices

de: Zusatzversicherung: Krankenversicherungsprämien nach Produkt, Veränderungsraten und Indizes

preise

display_name: preise

pretschs

display_name: pretschs

prezzi

display_name: prezzi

prices

display_name: prices

prix

display_name: prix


fr: Loyer moyen selon le nombre de pièces, l'époque de construction et la durée de la location

de: Durchschnittlicher Mietpreis nach Zimmerzahl, Bauperiode und Bezugsdauer der Wohnung

it: Affitto medio secondo il numero di locali, l'epoca di costruzione e il periodo d'affitto


fr: population genre homme femme

de: frau geschlecht bevolkerung mann

en: population woman gender man

it: donna uomo popolazione genere

en: Languages spoken at home by various socio-demographic characteristics in Switzerland

en: This dataset presents the annual figures for the languages spoken at work by gender, nationality (Switzerland, EU/EFTA), other European state, state outside Europe), age, migration background, current activity status (employed, unemployed, non-employed situation), socioeconomic group and highest completed education, since 2010. Descriptions of the variables in the CSV file are available in the Appendix.

fr: Langues parlées à la maison selon diverses caractéristiques socio-démographiques en Suisse

de: Zuhause gesprochene Sprachen nach verschiedenen soziodemografischen Merkmalen in der Schweiz

it: Lingue parlate a casa secondo diverse caratteristiche socio-demografiche in Svizzera

media_type: text/csv

fr: Ce dataset présente les chiffres annuels des langues parlées à la maison selon le sexe, la nationalité (Suisse, UE/AELE, autre pays européen, pays extra-européen), l'âge, le passé migratoire, le statut sur le marché du travail (personnes actives, personnes au chômage, personnes sans activité professionnelle), la catégorie socio-professionnelle et la formation achevée la plus élevée, depuis 2010. Les descriptions des variables du fichier CSV sont disponibles dans l’annexe.

de: Dieses Dataset präsentiert die jährlichen Zahlen der zuhause gesprochenen Sprachen nach Geschlecht, Staatsangehörigkeit (Schweiz, EU/EFTA, anderer europäischer Staat, aussereuropäischer Staat), Alter, Migrationshintergrund, Arbeitsmarktstatus (Erwerbstätige, Erwerbslose, Nichterwerbspersonen), sozioprofessioneller Kategorie und höchster abgeschlossener Ausbildung, seit 2010. Die Beschreibungen der Variablen in der CSV-Datei sind im Anhang verfügbar.

it: Questo dataset presenta le cifre annuali per le lingue parlate a casa secondo il sesso, la cittadinanza (Svizzera, UE/AELS, altro paese europeo, paese extraeuropeo), l'età, il passato migratorio, la posizione nel mercato del lavoro (occupati, disoccupati, persone senza attività professionale), categoria socio-professionale e la formazione più elevata conclusa, dal 2010. Per le descrizioni delle variabili del file CSV si rimanda all’allegato.

format: CSV

format: ODS

bevolkerung

display_name: bevolkerung

donna

display_name: donna

femme

display_name: femme

frau

display_name: frau

gender

display_name: gender

man

display_name: man

mann

display_name: mann

popolazione

display_name: popolazione

population

display_name: population

populaziun

display_name: populaziun


de: Bewohnte Wohnungen nach Bewohnertyp, nach Kanton

de: Dieses Dataset präsentiert die jährlichen Zahlen der bewohnten Wohnungen nach Kanton und Wohnverhältnis der Haushalte (Mieter/in oder Untermieter/in, Genossenschafter/in, Stockwerk-/Wohnungseigentümer/in, Eigentümer/in des Hauses, andere Situation), seit 2019. Die Beschreibungen der Variablen in der CSV-Datei sind im Anhang verfügbar.

fr: Logements occupés selon le statut d'occupation, par canton

en: Occupied dwellings by occupancy status and canton

it: Abitazioni occupate secondo il tipo di occupante, per Cantone

fr: Ce dataset présente les chiffres annuels du nombre de logements occupés selon le canton et le statut d'occupation des ménages (locataire ou sous-locataire, coopérateur/trice, propriétaire du logement / propriétaire par étage, propriétaire de la maison, autre situation), depuis 2019. Les descriptions des variables du fichier CSV sont disponibles dans l’annexe.

en: This dataset presents the annual figures for the number of occupied dwellings by canton and tenure status of households (tenant or sub-tenant, cooperative member, condominium/apartment owner, house owner, other situation), since 2019. Descriptions of the variables in the CSV file are available in the Appendix.

it: Questo dataset presenta le cifre annuali per il numero di abitazioni occupate secondo il Cantone e le condizioni abitativi delle economie domestiche (inquilino/a oppure subinquilino/a, socio/a di una cooperativa, proprietario/a dell'abitazione/proprietario/a per piani, proprietario/a della casa, altra situazione), dal 2019. Per le descrizioni delle variabili del file CSV si rimanda all’allegato.

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


de: Szenarien 2024-2033 für das Bildungssystem

de: Wie viele Lernende und Studierende werden die einzelnen Stufen des Schweizer Bildungssystems in den nächsten zehn Jahren zählen und wie viele Abschlüsse werden in jedem Bildungsfeld erteilt? Welche Faktoren beeinflussen die Zahlen der verschiedenen Bildungsgänge und wie werden sie sich entwickeln? Welche Folgen sind von der demografischen Dynamik und den festgestellten strukturellen Tendenzen zu erwarten? Diese Publikation versucht, diese für die Planung des Bildungssystems wichtigen Fragen anhand einer detaillierten Analyse der komplexen Prozesse zu beantworten, die sowohl in der obligatorischen Schule, der Sekundarstufe II, den Hochschulen oder der höheren Berufsbildung am Werk sind. Auf der Grundlage zahlreicher Quellen, einer detaillierten Modellierung der Übergänge von Schülern und Studierenden durch das Bildungssystem und einer Reihe spezifischer Hypothesen stellt sie drei Szenarien für das nächste Jahrzehnt vor. Zusätzlich zu den hier vorgestellten Elementen stehen Grafiken, Tabellen und detaillierte Würfel von Ergebnissen nach Kanton, Hochschule, Bildungsfeld usw. im Portal Statistik Schweiz unter der Adresse www.eduperspectives-stat.admin.ch zur Verfügung.

media_type: application/pdf

format: PDF

fr: Scénarios 2024-2033 pour le système de formation

fr: Combien d’élèves et d’étudiants compteront les divers degrés du système suisse de formation ces dix prochaines années et combien de titres seront délivrés dans chaque domaine de formation? Quels facteurs influencent les effectifs des différentes filières et comment évolueront-ils? Quels effets attendre de la dynamique démographique et des tendances structurelles observées? Cette publication tente de répondre à ces questions importantes pour la planification du système de formation à partir d’une analyse détaillée des processus complexes qui sont à l’œuvre à la fois dans l’école obligatoire, le degré secondaire II, les hautes écoles ou la formation professionnelle supérieure. Sur la base de nombreuses sources, d’une modélisation détaillée des transitions d’élèves et d’étudiants à travers le système de formation et d’une batterie d’hypothèses spécifiques, elle présente trois scénarios pour la prochaine décennie. En complément aux éléments exposés ici, des graphiques, des tableaux et des cubes de résultats détaillés par canton, par haute école, par domaine de formation, etc. sont publiés sur le Portail Statistique Suisse à l’adresse www.eduperspectives-stat.admin.ch.

bildung-und-wissenschaft

display_name: bildung-und-wissenschaft

education-and-science

display_name: education-and-science

education-et-science

display_name: education-et-science

formazione-e-scienza

display_name: formazione-e-scienza

furmaziun-e-scienza

display_name: furmaziun-e-scienza

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

en: Education, culture and sport

it: Istruzione, cultura e sport


de: Bezahlte Praktikanten

fr: Stagiaires rémunérés

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

econ

fr: Économie et finances

de: Wirtschaft und Finanzen


de: Phosphorgehalt in Seen

fr: Teneur en phosphore de quelques lacs

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

envi

fr: Environnement

de: Umwelt

en: Environment

it: Ambiente

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: Eau potable

fr: Ce dataset présente les chiffres annuels du captage de l'eau potable selon la source, de la consommation d'eau potable moyenne et maximale par habitant et par jour et de la répartition de l'utilisation d'eau potable, depuis 1945.

de: Trinkwasser

de: Dieses Dataset präsentiert die jährlichen Zahlen der Gewinnung von Trinkwasser nach Quelle, des mittleren und maximalen Trinkwasserverbrauchs je Einwohner und Tag und der Aufteilung des Trinkwasserverbrauchs, seit 1945.

odin-open-data-inventory

display_name: odin-open-data-inventory

de: Bundesamt für Statistik BFS

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.


it: Lingue principali secondo il Cantone

fr: Langues principales selon les cantons

de: Hauptsprachen nach Kantonen

bevolkerung

display_name: bevolkerung

popolazione

display_name: popolazione

population

display_name: population

populaziun

display_name: populaziun

spatial: Kantone

soci

fr: Population et société

de: Bevölkerung und Gesellschaft


fr: Ménages privés selon le groupe d'âge des membres du ménage et le statut d'occupation, par grandes régions

it: Economia domestica secondo la classe d'età dei membri dell'economia domestica e il tipo di occupante, per grandi regioni

de: Privathaushalte nach Altersgruppe der Haushaltsmitglieder und Bewohnertyp, nach Grossregionen

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


de: JSON-Struktur

format: SERVICE

de: Lernende der obligatorischen Schule nach Schulkanton, Unterrichtsart und Art der sonderpädagogischen Massnahmen

fr: Elèves de la scolarité obligatoire selon le canton de l'école, la forme d'enseignement et le type de mesures de pédagogie spécialisée

fr: Ce dataset présente les chiffres annuels des élèves de la scolarité obligatoire selon le canton de l'école, la forme d'enseignement (classes ordinaires, classes spéciales, classes des écoles spécialisées) et les mesures de pédagogie spécialisée, depuis 2017.

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden der obligatorischen Schule nach Schulkanton, Unterrichtsart (Regelklasse, Sonderklasse, Sonderschulklasse) und sonderpädagogischen Massnahmen, seit 2017.

fr: Structure JSON

bildung-und-wissenschaft

display_name: bildung-und-wissenschaft

education-and-science

display_name: education-and-science

education-et-science

display_name: education-et-science

formazione-e-scienza

display_name: formazione-e-scienza

furmaziun-e-scienza

display_name: furmaziun-e-scienza


fr: Ménages privés selon la catégorie de bâtiment, le groupe d'âge des membres du ménage et le statut d'occupation

de: Privathaushalt nach Gebäudekategorie, Altersgruppe der Haushaltsmitglieder und Bewohnertyp

it: Economia domestica secondo la categoria di edificio, la classe d'età dei membri dell'economia domestica e il tipo di occupante


it: Lingue principali secondo le grandi città

fr: Langues principales selon les grandes villes

de: Hauptsprachen nach grossen Städten

spatial: Sonstige Raumgliederungen

bundesamt-fur-statistik-bfs

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.


de: Neues Dashboard über die Metadatenqualität auf opendata.swiss zur Förderung von OGD

de: 25.02.2025 - Die Geschäftsstelle Open Government Data (OGD) lanciert ein Dashboard, mit dem die Qualität der auf opendata.swiss verfügbaren offenen Verwaltungsdaten beurteilt und verbessert werden kann. Datenanbietende erhalten so eine detaillierte Evaluation auf Basis der FAIR-Prinzipien. Dieses Projekt ist Teil des OGD-Masterplans 2024-2027 und wird vom Bundesamt für Statistik (BFS) umgesetzt. Offene Verwaltungsdaten (Open Government Data bzw. OGD) sind Daten der öffentlichen Verwaltung, die von allen frei und kostenlos genutzt, geteilt und wiederverwendet werden dürfen. In der Schweiz setzt sich der Bund für die Förderung dieser Daten ein, um Innovation, Forschung und Transparenz zu stärken. Zu diesem Zweck wurde ein neues Dashboard entwickelt. In Anlehnung an die von data.europa.eu verwendete Methode erfolgt die Beurteilung der Metadatenqualität nach den FAIR-Prinzipien Auffindbarkeit (Findability), Zugänglichkeit (Accessibility), Interoperabilität (Interoperability) und Wiederverwendbarkeit (Reusability). Das Dashboard dient den Anbietenden offener Daten in der Schweiz als Hilfsmittel, um die Qualität der Metadaten abzubilden und konkretes Verbesserungspotenzial zu ermitteln. Einfache und effiziente Evaluation für alle Datenanbietenden Das Dashboard umfasst zwei Analyseniveaus. Einerseits bietet es einen Überblick über die Metadatenqualität für das gesamte Portal opendata.swiss. Andererseits ist eine allgemein zugängliche Evaluation für die einzelnen Datenanbietenden bzw. Organisationen verfügbar, mit der sich die verbesserungsfähigen Aspekte ermitteln lassen. Hilfsmittel für eine laufende Verbesserung Das Dashboard ist nicht nur ein Diagnosetool, sondern hilft den Datenanbietenden auch dabei, sich laufend zu verbessern, indem es klare Empfehlungen abgibt: • Sichtbarkeit der Daten verbessern, z. B. durch Ergänzung ausführlicherer Beschreibungen oder relevanter Schlüsselwörter • Einhaltung von Qualitätsstandards gewährleisten, z. B. durch Anpassung der Formate oder Metadaten an Best Practices • Wiederverwendbarkeit erleichtern, z. B. durch eine bessere Zugänglichkeit und Verständlichkeit für externe Nutzende Indem das Dashboard zu einer hohen Datenqualität beiträgt und dafür sorgt, dass die Daten für die Forschung, die Medien und weitere interessierte Kreise einfach wiederverwendbar sind, erhöht es die Wirkung von OGD in der Schweiz. Ein weiterer Schritt für OGD in der Schweiz Die Qualität der Metadaten auf opendata.swiss wird mit 294 von 405 Punkten insgesamt als gut bewertet. Ende Februar zeigten die Ergebnisse eine gute Auffindbarkeit der Daten (70%) und vielversprechende Werte hinsichtlich Interoperabilität (75%), Wiederverwendbarkeit (99%), Kontext (65%) und Zugänglichkeit (55%). Die Einführung des Dashboards ist ein wichtiger Schritt bei der Umsetzung des OGD-Masterplans 2024-2027. Es unterstützt die Ziele des Bundes zur Förderung einer optimalen OGD-Verwaltung. Mit seinem einfachen und zugänglichen Ansatz trägt das Dashboard zur Verbesserung der Metadatenqualität und damit zur Aufwertung und Ausweitung der OGD in der Schweiz bei. Zugang zum Dashboard Das Dashboard ist bisher ausschliesslich auf Deutsch und Französisch verfügbar und kann unter folgendem Link aufgerufen werden: https://opendata.swiss/de/dashboard Zusätzliche Informationen finden Sie in der nachfolgenden PDF-Datei.

it: Un dashboard incentrato sulla qualità dei metadati di opendata.swiss per promuovere l'utilizzo dei dati aperti

it: 25.02.2025 - La Segreteria Open Government Data (Segreteria OGD) ha introdotto un dashboard progettato per valutare e migliorare la qualità dei metadati dei dati pubblici aperti su opendata.swiss. Questo strumento consente ai fornitori di dati di ottenere una valutazione dettagliata in linea con i principi FAIR. Tale progetto, parte della serie di misure previste nel masterplan OGD 2024-2027, è sviluppato dall'Ufficio federale di statistica (UST). Per dati pubblici aperti (detti anche open government data o OGD) si intendono le informazioni che le amministrazioni pubbliche mettono a disposizione della collettività in modo che possano essere utilizzate, condivise e riutilizzate dal maggior numero di persone possibile. In Svizzera, la Confederazione si impegna a promuovere la messa a disposizione di questi dati per incentivare l'innovazione, la ricerca e la trasparenza. È in questo contesto che è stato sviluppato il dashboard. Ispirato alla metodologia di valutazione della qualità dei metadati utilizzata da data.europa.eu, segue i principi FAIR (facile da reperire, accessibile, interoperabile e riutilizzabile). Questo strumento è destinato ai fornitori di dati pubblici in Svizzera e consente loro di vedere la qualità dei loro metadati, offrendo loro al contempo anche suggerimenti concreti per migliorarla. Valutazione semplice ed efficace per ogni fornitore di dati Il dashboard propone due livelli di analisi. Da una parte, fornisce una panoramica che consente di monitorare la qualità dei metadati nell'intero portale opendata.swiss. Dall'altra, tutte le persone che accedono al dashboard hanno a disposizione una valutazione di ogni organizzazione, fatto che consente loro di individuare con precisione gli aspetti con potenziale di miglioramento. Uno strumento mirato alla costante ottimizzazione Questo dashboard non è solo uno strumento di diagnostica, bensì aiuta anche i fornitori di dati a migliorare costantemente fornendo loro chiare raccomandazioni per... • ...migliorare la visibilità dei dati: ad esempio aggiungendo descrizioni più complete o parole chiave pertinenti. . • ...garantire la conformità agli standard di qualità: adeguando i formati o i metadati alle migliori pratiche.. • ...facilitare il riutilizzo: rendendo i dati più accessibili e comprensibili agli utenti esterni. Questo strumento consente così di aumentare l'impatto dei dati aperti in Svizzera, garantendo che siano di alta qualità e facilmente riutilizzabili da personale di ricerca, giornalisti e altri utenti interessati. Un ulteriore passo avanti per il settore svizzero dei dati aperti Con un punteggio totale di 294 su 405, la qualità dei metadati disponibili su opendata.swiss è valutata come buona. A fine febbraio 2025, dai risultati si evincono una buona facilità di reperimento dei dati (70%) nonché punteggi incoraggianti per l'interoperabilità (75%), il riutilizzo (99%), la contestualità (65%) e l'accessibilità (55%). Il lancio di questo dashboard segna un importante passo avanti nell'attuazione del masterplan OGD 2024-2027, in quanto contribuisce al raggiungimento dell'obiettivo della Confederazione di promuovere una gestione ottimale dei dati pubblici aperti. Offrendo un approccio semplice e accessibile, questo strumento partecipa attivamente all'incremento della qualità dei metadati e, di conseguenza, alla valorizzazione e all'accrescimento dei dati aperti in Svizzera. Come accedere al dashboard Per il momento il dashboard è disponibile solo in francese e in tedesco al link seguente: https://opendata.swiss/fr/dashboard Informazioni complementari si trovano nel PDF seguente.

fr: Un tableau de bord sur la qualité des métadonnées d'opendata.swiss pour dynamiser les données ouvertes

fr: 25.02.2025 - Le Secrétariat Open Government Data (Sécrétariat OGD) lance un tableau de bord destiné à évaluer et améliorer la qualité des métadonnées des données publiques ouvertes sur opendata.swiss. Cet outil permet aux fournisseurs de données d'obtenir une évaluation détaillée, en phase avec les principes FAIR. Ce projet, qui fait partie du Masterplan OGD 2024-2027, est élaboré par l'Office fédéral de la statistique (OFS). Les données ouvertes publiques (ou Open Government Data - OGD) désignent des informations mises à disposition gratuitement et librement par les administrations publiques pour être utilisées, partagées et réutilisées par le plus grand nombre. En Suisse, la Confédération s'engage à promouvoir l'ouverture de ces données pour stimuler l'innovation, la recherche et la transparence. C'est dans ce contexte que le tableau de bord a été développé. S'inspirant de la méthodologie d'évaluation de la qualité des métadonnées utilisée par data.europa.eu, il suit les principes FAIR (Facilité à trouver, Accessibilité, Interopérabilité et Réutilisation). Cet outil est conçu pour les fournisseurs de données publiques en Suisse et permet de visualiser la qualité des métadonnées tout en offrant des pistes concrètes pour leur amélioration. Une évaluation simple et efficace pour chaque fournisseur de données Le tableau de bord propose deux niveaux d'analyse. D'une part, il offre une vue d'ensemble qui permet de suivre la qualité des métadonnées sur l'ensemble du portail opendata.swiss. D'autre part, une évaluation par organisation est accessible à tous permettant ainsi d'identifier précisément les aspects à améliorer. Un outil qui guide vers l'amélioration continue Ce tableau de bord n'est pas seulement un outil de diagnostic, il aide aussi les fournisseurs de données à s'améliorer constamment en leur offrant des recommandations claires pour: • Améliorer la visibilité des données: Par exemple, en ajoutant des descriptions plus complètes ou des mots-clés pertinents. • Garantir la conformité avec les standards de qualité: En ajustant les formats ou les métadonnées pour répondre aux meilleures pratiques. • Faciliter la réutilisation: En rendant les données plus accessibles et compréhensibles pour les utilisateurs externes. Cet outil permet ainsi de renforcer l'impact des données ouvertes en Suisse, en assurant qu'elles soient à la fois de qualité et faciles à réutiliser par les chercheurs, les journalistes et tout autre utilisateur intéressé. Un pas de plus pour l'Open Data en Suisse Avec un score total de 294 sur 405, l'évaluation de la qualité des métadonnées sur opendata.swiss est jugée bonne. Fin février, les résultats montrent une bonne facilité à trouver (70%) les données et des scores encourageants en matière d'interopérabilité (75%), de réutilisation (99%), de contextualité (65%) et d'accessibilité (55%). Le lancement de ce tableau de bord marque une avancée importante dans la mise en oeuvre du Masterplan OGD 2024-2027. Il soutient les objectifs de la Confédération de promouvoir une gestion optimale des données publiques ouvertes. En offrant une approche simple et accessible, cet outil participe activement à l'amélioration de la qualité des métadonnées, et par conséquent, à la valorisation et à l'enrichissement des données ouvertes en Suisse. Accédez au tableau de bord Le tableau de bord est disponible pour le moment uniquement en français et en allemand sous le lien suivant: https://opendata.swiss/fr/dashboard Vous trouverez des informations complémentaires dans le document PDF ci-dessous.

en: A new dashboard on the quality of opendata.swiss metadata to boost access to open government data

en: 25.02.2025 - The Open Government Data (OGD) Office is launching a dashboard on opendata.swiss to evaluate and improve the quality of open government metadata. This tool allows providers to obtain a detailed evaluation of the quality of their metadata in line with FAIR principles. The project, which is part of the 2024‒2027 OGD Masterplan, was developed by the Federal Statistical Office (FSO). You can find further information in the press releases in German, French and Italian. The English version only contains the lead of the press release.

basas-statisticas-e-survistas

display_name: basas-statisticas-e-survistas

bases-statistiques-et-generalites

display_name: bases-statistiques-et-generalites

grundlagen-und-ubersichten

display_name: grundlagen-und-ubersichten

statistical-basis-and-overviews

display_name: statistical-basis-and-overviews

gove

fr: Gouvernement et secteur public

de: Regierung und öffentlicher Sektor

en: Government and public sector

it: Governo e settore pubblico

it: Ufficio federale di statistica UST


fr: Elèves de la scolarité obligatoire selon le canton de l'école, la forme d'enseignement et le type d'adaptation du programme d'enseignement

fr: Ce dataset présente les chiffres annuels des élèves de la scolarité obligatoire selon le canton de l'école, la forme d'enseignement (classes ordinaires, classes spéciales, classes des écoles spécialisées) et le type d'adaptation du programme d'enseignement, depuis 2017.

de: Lernende der obligatorischen Schule nach Schulkanton, Unterrichtsart und Art der Lehrplananpassung

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden der obligatorischen Schule nach Schulkanton, Unterrichtsart (Regelklasse, Sonderklasse, Sonderschulklasse) und Art der Lehrplananpassung, seit 2017.

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport


fr: Logements occupés selon l'époque de construction et le statut d'occupation

it: Abitazioni occupate secondo l'epoca di costruzione e il tipo di occupante

de: Bewohnte Wohnungen nach Bauperiode und Bewohnertyp

soci

it: Popolazione e società

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: femme homme genre education-et-science

de: bildung-und-wissenschaft frau geschlecht mann

en: education-and-science woman man gender

it: formazione-e-scienza genere donna uomo

fr: Elèves de la scolarité obligatoire selon la forme d'enseignement, le sexe, la nationalité (catégorie) et le type d'adaptation du programme d'enseignement

fr: Ce dataset présente les chiffres annuels des élèves de la scolarité obligatoire selon la forme d'enseignement (classes ordinaires, classes d'introduction, classes pour élèves de langue étrangère, classes spéciales, classes des écoles spécialisées), le sexe, la nationalité (Suisse, étranger) et le type d'adaptation du programme d'enseignement, depuis 2017.

de: Lernende der obligatorischen Schule nach Unterrichtsart, Geschlecht, Staatsangehörigkeit (Kategorie) und Art der Lehrplananpassung

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden der obligatorischen Schule nach Unterrichtsart (Regelklasse, Einführungsklasse, Klasse für Fremdsprachige, Sonderklasse, Sonderschulklasse), Geschlecht, Staatsangehörigkeit (Schweiz, Ausland) und Art der Lehrplananpassung, seit 2017.

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

uomo

display_name: uomo

woman

display_name: woman

de: Bundesamt für Statistik BFS

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.


it: Lingue principali dal 1910

fr: Langues principales depuis 1910

de: Hauptsprachen seit 1910

bevolkerung

display_name: bevolkerung

popolazione

display_name: popolazione

population

display_name: population

populaziun

display_name: populaziun

soci

fr: Population et société

de: Bevölkerung und Gesellschaft

bundesamt-fur-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.


de: Erwerbslose gemäss ILO, registrierte Arbeitslose und registrierte Stellensuchende

fr: Chômeurs au sens du BIT, chômeurs inscrits et demandeurs d'emploi inscrits

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

econ

fr: Économie et finances

de: Wirtschaft und Finanzen

it: Economia e finanze


de: Klimadaten: Sonnenscheindauer, Niederschlag, Temperatur und Neuschnee

fr: Données climatiques: ensoleillement, précipitations, température et neige fraîche

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

envi

fr: Environnement

de: Umwelt


de: Witterung in der Schweiz

fr: Le temps en Suisse


fr: genre education-et-science femme homme

de: geschlecht frau mann bildung-und-wissenschaft

en: education-and-science woman gender man

it: donna uomo genere formazione-e-scienza

fr: Structure JSON

de: Höhere Berufsbildung: Lernende nach Bildungstyp, Schulkanton, Geschlecht und Staatsangehörigkeit (Kategorie)

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden nach Bildungstyp, Schulkanton, Geschlecht und Staatsangehörigkeit (Schweiz, Ausland), seit 1999.

fr: Formation professionnelle supérieure: étudiants selon le type de formation, le canton de l'école, le sexe et la nationalité (catégorie)

de: JSON-Struktur

fr: Ce dataset présente les chiffres annuels des étudiants de la formation professionnelle supérieure selon le type de formation, le canton de l'école, le sexe et la nationalité (Suisse, étranger), depuis 1999.

bildung-und-wissenschaft

display_name: bildung-und-wissenschaft

donna

display_name: donna

education-and-science

display_name: education-and-science

education-et-science

display_name: education-et-science

femme

display_name: femme

formazione-e-scienza

display_name: formazione-e-scienza

frau

display_name: frau

furmaziun-e-scienza

display_name: furmaziun-e-scienza

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


de: Klimadaten: Eistage, Frosttage, Sommertage, Hitzetage, Tropennächte und Niederschlagstage

fr: Données climatiques: jours d'hiver, jours de gel, jours d'été, jours tropicaux, nuits tropicales et jours de précipitations

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


fr: femme education-et-science genre homme

de: geschlecht mann bildung-und-wissenschaft frau

en: gender woman education-and-science man

it: formazione-e-scienza uomo donna genere

de: Sekundarstufe II - Berufsmaturität (BM2): Lernende nach Richtung, Geschlecht und Staatsangehörigkeit (Kategorie)

fr: Degré secondaire II - maturité professionnelle (MP2): élèves selon l'orientation, le sexe et la nationalité (catégorie)

fr: Ce dataset présente les chiffres annuels des élèves du degré secondaire II, niveau maturité professionnelle (MP2), selon l'orientation (technique, architecture et sciences de la vie, économie et services, arts visuels et arts appliqués, nature, paysage et alimentation, santé et social), le sexe et la nationalité (Suisse, étranger), depuis 1999.

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden der Sekundarstufe II, Stufe Berufsmaturität (BM2), nach Richtung (Technik, Architektur, Life Sciences, Wirtschaft und Dienstleistungen, Gestaltung und Kunst, Natur, Landschaft und Lebensmittel, Gesundheit und Soziales), Geschlecht und Staatsangehörigkeit (Schweiz, Ausland), seit 1999.

bildung-und-wissenschaft

display_name: bildung-und-wissenschaft

donna

display_name: donna

education-and-science

display_name: education-and-science

uomo

display_name: uomo

woman

display_name: woman

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


fr: education-et-science femme genre homme

de: geschlecht bildung-und-wissenschaft mann frau

en: man education-and-science gender woman

it: uomo donna formazione-e-scienza genere

fr: Degré secondaire II, formation générale et maturité professionnelle: élèves et étudiants selon le type de formation

de: Sekundarstufe II, allgemeinbildende Ausbildungen und Berufsmaturität: Lernende nach Bildungstyp

fr: Ce dataset présente les chiffres annuels des élèves et étudiants de degré secondaire II en formation générale et maturité professionnelle selon le type de formation ainsi que les parts en pourcents d'élèves et étudiants selon le statut de l'établissement (public/privé subventionné, privé non subventionné), le sexe et la nationalité (Suisses, étrangers), depuis 1999.

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden der Sekundarstufe II in allgemeinbildenden Ausbildungen und Berufsmaturität nach Bildungstyp sowie die Anteile der Lernenden in Prozent nach Charakter der Bildungsinstitution (öffentlich/privat subventioniert, privat nicht subventioniert), Geschlecht und Staatsangehörigkeit (Schweizer, Ausländer), seit 1999.

education-et-science

display_name: education-et-science

femme

display_name: femme

formazione-e-scienza

display_name: formazione-e-scienza

frau

display_name: frau

furmaziun-e-scienza

display_name: furmaziun-e-scienza

de: Bundesamt für Statistik BFS

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.


fr: homme genre odin-open-data-inventory education-et-science femme

de: odin-open-data-inventory frau mann bildung-und-wissenschaft geschlecht

en: gender education-and-science man woman odin-open-data-inventory

it: genere donna uomo formazione-e-scienza odin-open-data-inventory

fr: Elèves et étudiants selon le degré de formation, le canton de l'école, le sexe et la nationalité (catégorie) (sans les hautes écoles)

de: Lernende nach Bildungsstufe, Schulkanton, Geschlecht und Staatsangehörigkeit (Kategorie) (ohne Hochschulen)

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden nach Bildungsstufe (obligatorische Schule, Sekundarstufe II, Tertiärstufe und unbestimmt, ohne Hochschulen), Schulkanton, Geschlecht und Staatsangehörigkeit (Schweiz, Ausland), seit 1999. Die Daten werden aus Datenschutzgründen nicht auf der Ebene der Gemeinden veröffentlicht.

fr: Ce dataset présente les chiffres annuels des élèves et des étudiants selon le degré de formation (scolarité obligatoire, degré secondaire II, tertiaire et indéfini, sans les hautes écoles), le canton de l'école, le sexe et la nationalité (Suisse, étranger), depuis 1999. Les données ne sont pas publiées au niveau communal pour des raisons de protection des données.

gender

display_name: gender

genere

display_name: genere

genre

display_name: genre

geschlecht

display_name: geschlecht

homme

display_name: homme

odin-open-data-inventory

display_name: odin-open-data-inventory

bundesamt-fur-statistik-bfs

en: Federal Statistical Office FSO

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.


de: Exporte von Sonderabfällen nach Ländern

fr: Exportations de déchets spéciaux par pays

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: International

envi

fr: Environnement

de: Umwelt

it: Ambiente

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.


fr: education-et-science genre femme homme

de: bildung-und-wissenschaft mann frau geschlecht

en: education-and-science gender woman man

it: genere donna formazione-e-scienza uomo

fr: Degré secondaire II, formation professionnelle initiale: élèves et étudiants selon la grande région, le canton de l'école, le sexe, la nationalité et le statut de l'école

de: Sekundarstufe II, Berufliche Grundbildung: Lernende nach Grossregion, Schulkanton, Geschlecht, Staatsangehörigkeit und Charakter der Schule

bildung-und-wissenschaft

display_name: bildung-und-wissenschaft

donna

display_name: donna

education-and-science

display_name: education-and-science

man

display_name: man

mann

display_name: mann

uomo

display_name: uomo

woman

display_name: woman


fr: homme genre femme education-et-science

de: geschlecht frau bildung-und-wissenschaft mann

it: donna uomo formazione-e-scienza genere

fr: Degré secondaire II, formation professionnelle initiale: élèves et étudiants selon le domaine de formation, la nationalité, le statut de l'école ainsi que l'année de programme, la durée de la formation et le mode d'enseignement

de: Sekundarstufe II, berufliche Grundbildung: Lernende nach Ausbildungsfeld, Staatsangehörigkeit, Schulcharakter sowie Ausbildungsjahr, -dauer und -form

fr: Ce dataset présente les chiffres annuels des élèves et étudiants de degré secondaire II en formation professionnelle initiale selon le domaine de formation, l'année de programme, la durée de la formation et le mode d'enseignement ainsi que les parts en pourcents d'élèves et étudiants selon le statut de l'établissement (public/privé subventionné, privé non subventionné), le sexe et la nationalité (Suisses, étrangers), depuis 1999.

de: Dieses Dataset präsentiert die jährlichen Zahlen der Lernenden der Sekundarstufe II in beruflicher Grundbildung nach Ausbildungsfeld, Programmjahr, Ausbildungsdauer und Ausbildungsform sowie die Anteile der Lernenden in Prozent nach Charakter der Bildungsinstitution (öffentlich/privat subventioniert, privat nicht subventioniert), Geschlecht und Staatsangehörigkeit (Schweizer, Ausländer), seit 1999.

education-et-science

display_name: education-et-science

femme

display_name: femme

formazione-e-scienza

display_name: formazione-e-scienza

frau

display_name: frau

furmaziun-e-scienza

display_name: furmaziun-e-scienza

gender

display_name: gender

genere

display_name: genere

bundesamt-fur-statistik-bfs

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.


fr: Ménages privés selon le type de communes et le statut d'occupation

it: Economia domestica secondo il tipo di Comuni e il tipo di occupante

de: Privathaushalt nach Gemeindetypen und Bewohnertyp

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


fr: Température et teneur en nitrates et en phosphates de quatre cours d'eau

de: Temperatur, Nitrat- und Phosphatgehalt von vier Flüssen

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

bundesamt-fur-statistik-bfs

fr: Office fédéral de la statistique OFS


it: Economia domestica secondo il tipo di economia domestica e il tipo di occupante

de: Privathaushalt nach Haushaltstyp und Bewohnertyp

fr: Ménages privés selon le type de ménage et le statut d'occupation


it: Abitazioni occupate secondo il tipo di occupante e la fonte d'energia di riscaldamento

de: Bewohnte Wohnungen nach Bewohnertyp und Energiequelle der Heizung

fr: Logements occupés selon le statut d'occupation du ménage et la source d’énergie du chauffage

it: Ufficio federale di statistica UST


en: sea-ice drone snow-roughness antarctica snow-temperature uav irra snow

media_type: application/zip

format: ZIP

en:
This dataset accompanies the publication "How Flat is Flat? Investigating the spatial variability of snow surface temperature and roughness on landfast sea ice using UAVs in McMurdo Sound, Antarctica".
The dataset consists of 1) processed orthomosaic of RGB values, snow topography (digital elevation model), and surface temperature, 2) topography-dependent irradiance map, and 3) point data of measured radiation and atmospheric parameters in the McMurdo Sound, October-December 2022. The data was collected as part of the New Zealand Marsden Fund Research Grant 21-VUW-103 "Can Snow Change the Fate of Antarctic Sea Ice?". Unprocessed data associated with this field campaign are published in 10.16904/envidat.633.
For the airborne measurements, we used a DJI Matrice 30T, a multi-rotor (quadcopter) UAV with self-heating batteries, suitable for operations in polar conditions (temperature range from -20 to +50 °C). The UAV has a wide-angle camera (12 megapixels) for RGB images and a thermal camera (Uncooled Vox Microbolometer, long-wave infrared spectrum 8-14 µm, 1.31 megapixels) for TIR images with an accuracy of ±2 °C or ± 2 %.
GNSS data includes high-precision location information (latitude, longitude, ellipsoidal height, receiver clock offset, and timestamps formatted in decimal hours and day-of-year notation).
WE calculated the distribution of received solar irradiance over the sea-ice surface using a terrain-corrected radiative transfer model and measured shortwave radiation components, accounting for surface roughness, aspect, slope, and solar position during the flight, while applying terrain shading and measured diffuse radiation.
The broadband radiation station data consists of shortwave (Sw) and longwave (Lw) radiation measurements (Kipp & Zonen CMP22 pyranometers and CGR4 pyrgeometers).
Surface temperature readings from cold, sediment, and hot targets were recorded using Apogee SI-121-SS sensors.
This dataset also contains automated weather station (AWS) data (air and snow surface temperatures, relative humidity, wind direction, and wind speed).
For detailed information, please use the README file.

antarctica

display_name: antarctica

drone

display_name: drone

irra

display_name: irra

sea-ice

display_name: sea-ice

snow

display_name: snow

snow-roughness

display_name: snow-roughness

snow-temperature

display_name: snow-temperature

uav

display_name: uav

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und 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.

political_level: other

wsl

capacity: public

value: Envidat Harvester

en: Snow On Antarctic Sea Ice - McMurdoSound 2022 - UAV Retrievals of Snow Topography and Snow Surface Temperature


maintainer: Yael Frischholz

en: winter-electricity snow bifaciality alps photovoltaic

en:
Title: Monitoring data set at A1 (test-site of Totalp), years 2018-2022
Provider: ZHAW - EKZ
Edition: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
Last edition: 17.01.2024
File name structure:
The test site contains 6 segments named from A to F. The six files provided in the data/ subfolder follow the same naming convention (e.g. for segment A, the file name is: “A1_A.csv”). Refer to the publication for further details on the setups of the segments.
File format:
All files are provided in the CSV format.
Column headings:
	•	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	•	poa_front (double): front plane-of-array irradiation (W/m**2)
	•	poa_back (double): rear plane-of-array irradiation (W/m**2)
	•	mod_temp (double): module’s temperature (°C)
	•	P_AC (double): output AC power (W)
Preprocessing:
	Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.
	Missing data:
	⁃	Data holes of less than 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).
	Wiring losses :
	⁃	As described in [1] , the test-site setup caused abnormally large wiring losses, mainly due to the distance to optimisers and to the low installed power per DC-wire.
	⁃	The wiring losses comprised between 10% and 15%, are averaged hourly and added to the measured DC power.

	Misc.:
	⁃	P_AC is computed for each segment based on the measured DC power and the average inverter’s efficiency (96.1%).
	⁃	As described in [1], the peak power of the installed module, used to compute the final yield is slightly different from the values announced by the manufacturer.
Mean uptime:
	Raw:
	⁃	95.2%
	Processed:
	⁃	100%
References:
[1] 	D. Anderegg, S. Strebel, and J. Rohrer, “Alpine Photovoltaik Versuchsanlage Davos Totalp : Erkenntnisse aus 5 Jahren Betrieb,” de, Sep. 	2023, Accepted: 2023-09-29T09:13:16Z Publisher: ZHAW Zürcher Hochschule für Angewandte Wissenschaften.DOI: 10.21256/	zhaw-2524. [Online]. Available: https://digitalcollection.zhaw.ch/handle/11475/28797 (visited on 12/15/2023).

en:
Title: Monitoring data set at A2 (utility-scale power-plant Muttsee), months 10.2022-09.2023
Provider: AXPO - IWB Industrielle Werke Basel
Last edition: 17.01.2024
Editor: Y.Frischholz, Laboratory of Cryospheric Sciences, EPFL
File name structure:
The power-plant is made of 23 string boxes (GAK) and inverters (WR) named after their given number. One file per device is provided in the data/ subfolder, following the same naming convention (e.g. for the string box number 1, the file name is: “A2_GAK01.csv” and for the corresponding inverter, the file name is “A2_WR01.csv”). Refer to the publication for further details on the setup of the power plant.
File format:
All files are provided in the CSV format.
Column headings:
	String boxes and inverters (GAK & WR):
	⁃	device_name (string): name of the device (same as file name)
	⁃	timestamp (datetime64): time stamp in format “YYYY-MM-DD HH:mm:ss”, time-zone: UTC
	String boxes (GAK):
	⁃	I_ (double): input current from the substring number (W)
	⁃	I_SUM (double): output current of string box (A)
	⁃	U_DC (double): output voltage of string box (V)
	⁃	P_DC_ (double): input DC power from the substring number (W)
	⁃	P_DC (double): output DC power of string box (W)
	⁃	$S$_T#_$T$ (double): temperature from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S) of table T. Two types of temperature measurements (#) are available: 1=standard cell temperature (°C) , 2=module temperature on the rear side (°C) .
	⁃	$S$_SRAD_T (double): poa irradiation (W/m**2) from the sensor connected to the string box (empty if not existing), placed on the “front” or “back” side (S) of table T.
		Inverters (WR):
	⁃	I_DC (double): input DC current(A)
	⁃	U_DC(double): input DC voltage(V)
	⁃	P_DC (double): input DC power (W)
	⁃	P_AC (double): output AC power (W)
Preprocessing:
	1. Outliers:
	⁃	Quantiles Q1 and Q99 are computed for each variable
	⁃	Values below Q1 and above Q99 are considered outliers
	⁃	Outliers are replaced by NaNs.

	2. Missing data:
	⁃	Data holes of less or equal to 3 hours are interpolated linearly for all variables
	⁃	Data holes of more than 3 hours are replaced using the monthly nan-mean of the considered hour if more than 50% of the qualifying data points are available. For instance, if the data point 2022-12-12 12:12:00, is missing for a given variable and is part of a data hole larger than 3 hours, then it is replaced by the mean of all data points with hour = 12 of the month of December 2022, if 50% of all the qualifying data points are not NaN. In case more than 50% of the qualifying points are missing, the data point remains as missing (NaN).
	3. Wiring losses:
	⁃	To be consistent with A1, wiring losses are corrected at A2. The wiring loss between the string boxes and the inverters is removed by multiplying the value of input P_DC at the inverter level (P_DC,inv) by the mean ratio P_DC,inv / P_DC,arr.
	⁃	The computed mean wiring loss is 2.3\%. It is computed from 2023-02-01 to 2023-09-30, after the long data hole in the data sets of the string boxes.

Mean uptime:
	Raw:
	⁃	WR: 98.2%
	⁃	GAK*: 38.5%
	Processed:
	⁃	WR: 99.6%
	⁃	GAK*: 56.4%

	*The uptime at the string box level (GAK) is low because PMUs at this level shut down during steady and low signal leading to unavailable data at night. In addition, the 23 days downtime of 	January 2023 could not be interpolated nor replaced.

en:
On this repository you can find the monitoring data of the 3 PV power-plants analysed in the article _"Confirmation of the power gain for solar photovoltaic systems in alpine areas"_ (doi: 10.3389/fenrg.2024.1372680) . Each folder contains the following two elements:
1. **README.txt** : describes the content of the folder. Especially it describes the plant's monitoring system's architecture and relates it to the various files included in the data sub-folder. It also provides a detailed description of all processing steps leading to the data sets as available in the data sub-folder and used in the pre-cited article.
3. **data/** : sub-folder containing the file(s) used in the referenced article.

alps

display_name: alps

bifaciality

display_name: bifaciality

photovoltaic

display_name: photovoltaic

winter-electricity

display_name: winter-electricity

educ

en: Education, culture and sport

en: Monitoring data sets of alpine photovoltaic power-plants


maintainer: Jana von Freyberg

en: stable-water-isotopes snowpack-outflow snowmelt-lysimeter snowmelt-rate solutes

en: The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution. 10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.

en:
This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland. The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.
The dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.

snowmelt-lysimeter

display_name: snowmelt-lysimeter

snowmelt-rate

display_name: snowmelt-rate

snowpack-outflow

display_name: snowpack-outflow

solutes

display_name: solutes

stable-water-isotopes

display_name: stable-water-isotopes

en: Daily data of the volumes, solutes and isotopes in snowpack outflow measured at three locations in the southern Alp catchment


automatic-classification-of-avalanches

maintainer: Alec van Herwijnen

title_for_slug: automatic-classification-of-avalanches

en: seismic machine-learning monitoring localization avalanche

en:
This tar file contains classification results for two seismic geophone arrays deployed above Davos, Switzerland. The of the first array located at the Dischma Valley was used to automatically identify all seismic events produced by avalanches, whereas the classification perfomed at the second array located at the Wannengrat field site was used to identify airplanes and earthquakes.
Furthermore, this tar file also contains the median back-azimuth of all classified events at the Dischma field site.

mimetype: application/x-tar

en: This dataset contains the classification and localization results obtained during the automatic classification of avalanches during the winter season 2017.

avalanche

display_name: avalanche

localization

display_name: localization

machine-learning

display_name: machine-learning

monitoring

display_name: monitoring

seismic

display_name: seismic

en: Automatic Classification of Avalanches


maintainer: EnviDat Support

en: mobile-laser-scanning 3d-point-cloud structure-from-motion terrestrial-laser-scanning lidar terrestrial-photogrammetry forest-inventory unmanned-aerial-vehicle-laser-scanning

en:
Close Range Remote Sensing Benchmark for different LiDAR and photogrammetric Sensors in a mixed temperate forest.
Benchmarks are needed to evaluate the performance of different close-range remote sensing devices and approaches, both in terms of efficiency as well as accuracy. In this study we evaluate the performance of two terrestrial (TLS), one handheld mobile (PLS) and two drone based (UAVLS) laser scanning systems to detect trees and extract the diameter at breast height (DBH) in three plots with a steep gradient in tree and understorey vegetation density. As a novelty, we also tested the acquisition of 3D point-clouds using a low-cost action camera (GoPro) in conjunction with the Structure from Motion (SfM) technique and compared its performance with those of the more costly LiDAR devices.

forest-inventory

display_name: forest-inventory

lidar

display_name: lidar

mobile-laser-scanning

display_name: mobile-laser-scanning

structure-from-motion

display_name: structure-from-motion

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

terrestrial-photogrammetry

display_name: terrestrial-photogrammetry

unmanned-aerial-vehicle-laser-scanning

display_name: unmanned-aerial-vehicle-laser-scanning

envidat

en: EnviDat: the Environmental Data Portal

en: Ramerenwald Close Range Remote Sensing Benchmark


en: uetliberg plant-species occurrence zurich flora-change

en:
The list gives the clearly identifiable plant species from Schinz (1775). Die Reise auf den Uetliberg. Verlag des Waysenhauses, Zürich). Several species given in Schinz (1775) are not identifiable to the species level and are not included in the list. Similarly, Vicia pisiformis, Erbsenartige Wicke, given by Schinz (1775) is probably a misidentification and also not included in the list.

Latin plant species name Schinz 1775: Latin plant name (if) given by Schinz (1775); na: not available
German plant species name Schinz 1775: German plant name given by Schinz (1775)
Latin plant species name Info Flora 2024: Latin plant name according to www.infoflora.ch in 2024
German plant species name Info Flora 2024: German plant name according to www.infoflora.ch in 2024
Plant species still occurring in 2020: Plant species given in Schinz (1775) still occurring at the Uetliberg in 2020 (Zürcherische Botanische Gesellschaft. 2020. Flora des Kanton Zürich. Haupt, Bern); occurrence of Thesium alpinum, Alpen-Bergflachs, according to floristic knowledge of Rolf Holderegger and Michèle Büttner; 1: still occurring; 0: no longer occurring / extinct.

en:
The list gives the clearly identifiable plant species from Schinz (1775). Die Reise auf den Uetliberg. Verlag des Waysenhauses, Zürich). Several species given in Schinz (1775) are not identifiable to the species level and are not included in the list. Similarly, *Vicia pisiformis*, Erbsenartige Wicke, given by Schinz (1775) is probably a misidentification and also not included in the list.
Latin plant species name Schinz 1775: Latin plant name (if) given by Schinz (1775); na: not available
German plant species name Schinz 1775: German plant name given by Schinz (1775)
Latin plant species name Info Flora 2024: Latin plant name according to www.infoflora.ch in 2024
German plant species name Info Flora 2024: German plant name according to www.infoflora.ch in 2024
Plant species still occurring in 2020: Plant species given in Schinz (1775) still occurring at the Uetliberg in 2020 (Zürcherische Botanische Gesellschaft. 2020. Flora des Kanton Zürich. Haupt, Bern); occurrence of *Thesium alpinum*, Alpen-Bergflachs, according to floristic knowledge of Rolf Holderegger and Michèle Büttner; 1: still occurring; 0: no longer occurring / extinct.

flora-change

display_name: flora-change

occurrence

display_name: occurrence

plant-species

display_name: plant-species

uetliberg

display_name: uetliberg

zurich

display_name: zurich

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: Plant species list from 1775 and 2020 for Uetliberg Zürich


en: traffic-noise urban-landscape field-data forest restoration

en: This SPSS data file includes the data used for analysis in paper 2 (Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial) and paper 3 ("The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial").

format: OCTET

en: 01_Studyprotocol_Locations of the starting points of the walking routes in the test settings.pdf

en: This document includes GPS coordinates of the starting points of the walking routes in the test sites.

en: 07_Studyprotocol_Test site pictures.zip

en: This folder includes two pictures of each test site. The locations for the two pictures on each route were chosen to be as characteristic as possible in terms of the visual and acoustical impressions of the walk.

en: 03a_Studyprotocol_Data on evaluation of acoustic impression of the test settings_Studyprotocol.sav

en: This data file includes information for an additional post hoc classification of the sound environment of the test sites. This evaluation was conducted in the afternoons of the same week in 2023 at two locations within each test site by a civil servant who was not familiar with the study's research questions.

en: This file contains the informed consent document that participants signed to participate in the study.

en: This document includes the questionnaire for Papers 2 and 3, administered at the second measurement time point (after the walk).

en: 11_P4_S1_Instructions for individual mindful walking.pdf

en: This document contains the booklet with instructions for mindful walking, which participants in the mindfulness condition were encouraged to take with them and use during their individual walks over the 10 days following on-site participation.

en: 12_P4_S2_Description of mindful walking intervention on site.pdf

en: This file includes the guided mindful walking instructions provided to participants in the mindfulness condition during the on-site walks.

en: This document includes the questionnaire for Papers 2 and 3, administered at the first measurement time point (before the walk began).

en: 09_P2_Fotos Noise ROS paper.zip

en: This folder included the example pictures of the conditions included in paper 2 ("Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“).

en: 02_Studyprotocol_Data on Laeq from noise recordings of walking routes_Studyprotocol.sav

en: This data file contains information on the LAeq levels recorded along the final walking routes between September 2021 and March 2022, prior to the commencement of data collection.

en: 03b_Studyprotocol_Script_Analysis stationary noise evaluation.sps.sps

en: This SPSS syntax file contains a script for analyzing data related to the stationary evaluation of the acoustic impressions at the test sites, which is numbered 03a in this repository.

en: This document includes the questionnaire for Papers 2 and 3, administered at the third measurement time point (10 days after participation on site).

en: 06_Studyprotocol_GPS tracks of the walking routes.zip

en: This folder contains the GPS tracks of the walking routes in the test sites.

en: This file includes the information sheet provided to participants before they consented to take part in the study.

en:
This repository contains data related to the field experiments of the RESTORE project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and the Swiss Federal Laboratories for Materials Science & Technology (EMPA). It has received funding from the Swiss National Science Foundation. The overall objective of the RESTORE project was to assess the effects of green spaces as facilitators and noise as impediment to recover from stress in people's daily environments across Switzerland.
We conducted a randomized, controlled field study to compare the psychophysiological benefits of exposure to forests and urban built environments with different levels of road traffic noise in healthy adults during 30-minute walks in Zürich, Switzerland to explore:
1) The psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure
2) The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world
3) The effects of a mindful walking intervention in urban forests for healthy adults
Accordingly, this repository includes data and documentation for the 3 scientific articles:
Scientific article 1. “Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial", BMC Psychology, 2024. https://doi.org/10.1186/s40359-024-01720-x
Scientific article 2. "Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: A randomized controlled trial“. Journal of Environmental Psychology, 2025.
Scientific article 3. “The effects of walking in urban forests and urban built environments with disparate road traffic noise exposure on repetitive negative thinking and connectedness with the non-human world: A randomized controlled trial". To be submitted to PLOS One, 2025.
Scientific article 4: "Effects of a mindful walking intervention in urban forests for healthy adults". To be submitted to Current Psychology.

field-data

display_name: field-data

forest

display_name: forest

restoration

display_name: restoration

traffic-noise

display_name: traffic-noise

urban-landscape

display_name: urban-landscape

educ

en: Education, culture and sport


data-set-on-snow-instability

title_for_slug: data-set-on-snow-instability

en: snow-stability-evaluation failure-initiation rutschblock slab-tensile-support avalanche-forcasting propgatoin-saw-test crack-propagation slab weak-layer snow-avalanche

en: data set on snow instability

mimetype: text/csv

en: Read-me file on snow instability data

mimetype: application/pdf

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

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: Data set on snow instability


maintainer: Ionuț Iosifescu Enescu

en: map preview 0.5MB

mimetype: image/jpeg

en: Bulk Data Access

en: Link to the S3 bucket where all the data resources can be downloaded in bulk

format: GeoTIFF

en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.

Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)


en: dischma snow-hydrology davos avalanches snow-depth-distribution photogrammetry

en: Snowdepth maps

en:
The available datasets are snow depth maps with a spatial resolution of 0.5 m derived from images of the survey camera Vexcel Ultracam mounted on a piloted airplane. Image acquisition was carried out during the approximately peak of winter (time when the thickest snowpack is expected) in spring. The snow depth maps are calculated by the subtraction of a summer-DTM from the processed winter- DSM of the corresponding date. The summer-DTM used was derived from a point cloud of an airborne laser scanner from 2020.

Due to the occurrence of inaccuracies of the calculated snow depth values caused by the photogrammetric method, we applied different masks to significantly increase the reliability of the snow depth maps. We masked out settled areas, high-frequented streets and technical constructions, pixels with high vegetation (height > 0.5 m) , outliers and unrealistic snow depth values. In addition, we modified the snow depth values of snow-free pixels to 0.
The information on buildings and infrastructure comes from the exactly classified ALS point cloud and the TLM dataset from Swisstopo (https://www.swisstopo.admin.ch/de/geodata/landscape/tlm3d.html#links). High vegetation is also derived from the classification and the calculated object height from the point cloud.
Outliers and unrealistic snow depth values are defined as negative snow depth values and snow depths exceeding 10 m. The classification of each pixel of the corresponding orthophoto into snow-covered or snow-free is based on the application of a threshold of the NDSI or manually determined ratios of the RGB values.

An extensive accuracy assessment proves the high accuracy of the snow depth maps with a root mean square error of 0.25 m for the year 2017 and 0.15 m for the following snow depth maps.

The work is published in:

avalanches

display_name: avalanches

davos

display_name: davos

dischma

display_name: dischma

photogrammetry

display_name: photogrammetry

snow-depth-distribution

display_name: snow-depth-distribution

snow-hydrology

display_name: snow-hydrology

en: Snow depth mapping by airplane photogrammetry (2017 -  ongoing)


maintainer: Camille Albouy

en: bay-biscay fish-composition dna-metabarcoding edna atlantic-region teleo chondrichthyes actinopterygii

en: Data access

en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2020)

In October 2020 we chose 16 sites from the 2020 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is carried out annually during autumn in the BoB to monitor demersal fish resources. All sites were located on the continental shelf (26–170 m depth), except one on the upper slope with a depth of 1045 m. To perform eDNA sampling, we collected water samples at 15 sites (Figure 1a). At each site, we sampled seawater using Niskin bottles deployed with a circular rosette. There were nine bottles on the rosette, each of them able to hold ∼5 l of water. At each site, we first cleaned the circular rosette and bottles with freshwater, then lowered the rosette (with bottles open) to 5 m above the sea bottom, and finally closed the bottles remotely from the boat. The 45 l of sampled water was transferred to four disposable and sterilized plastic bags of 11.25 l each to perform the filtration on-board in a laboratory dedicated to the processing of eDNA samples. To speed up the filtration process, we used two identical filtration devices, each composed of an Athena® peristaltic pump (Proactive Environmental Products LLC, Bradenton, Florida, USA; nominal flow of 1.0 l min–1 ), a VigiDNA 0.20 μm filtration capsule (SPYGEN, le Bourget du Lac, France), and disposable sterile tubing. Each filtration device filtered the water contained in two plastic bags (22.5 l), which represent two replicates per sampling site. We followed a rigorous protocol to avoid contamination during fieldwork, using disposable gloves and single-use filtration equipment and plastic bags to process each water sample. At the end of each filtration, we emptied the water inside the capsule that we replaced by 80 ml of CL1 conservation buffer and stored the samples at room temperature following the specifications of the manufacturer (SPYGEN, Le Bourget du Lac, France). We processed the eDNA capsules at SPYGEN, following the protocol proposed by Polanco-Fernández et al., (2020). We performed library preparation and sequencing at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. We carried out paired-end sequencing using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analysed the sequence reads using the OBITools package (http:
//metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).

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)

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bay-biscay

display_name: bay-biscay

chondrichthyes

display_name: chondrichthyes

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

fish-composition

display_name: fish-composition

teleo

display_name: teleo

educ

en: Education, culture and sport

en: Environmental DNA Marine France Evhoe 2020


disdrometer-data-davos-wolfgang

title_for_slug: disdrometer-data-davos-wolfgang

en: fall-velocity davos disdrometer precipitation raclets

en: Disdrometer Data Davos Wolfgang

en:
The zip folder contains one netCDF file per day for Davos Wolfgang from February 8 to March 19 2019 with a temporal resolution of 30 seconds (time in UTC) and includes:

- characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...)
- precipitation rate
- radar reflectivity
- visibility range
- weather codes
- instrument performance

mimetype: application/zip

en: The dataset contains information on precipitation amount and type for Davos Wolfgang (LON: 9.853594, LAT: 46.835577) from February 8 to March 19 2019. It includes: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

disdrometer

display_name: disdrometer

fall-velocity

display_name: fall-velocity

precipitation

display_name: precipitation

raclets

display_name: raclets

envidat

en: EnviDat: the Environmental Data Portal


maintainer: Paraskevi Georgakaki

en: swiss-alps wrf ice-water-content jungfraujoch liquid-water-content blowing-snow secondary-ice-production ice-crystal-number-concentration

en: Observational data

en:
The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

Acknowledgment: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en: WRF outputs

en:
The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf

envidat

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: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"


en: microstructure compression-experiments snow-mechanics x-ray-tomography snow

en: Snowmicroquakes Data

en: Compression experiments, X-ray images and simulation data with supplemented README file

en: README

media_type: text/plain

en: README file explaining the organization of the data

format: TXT

en:
When snow is compressed with a certain speed, micro-snowquakes are triggered in the porous structure of bonded crystals. The present dataset covers uniaxial compression experiments of snow at different strain rates and concurrent X-ray tomography imaging documenting this feature.

The experiments were conducted in a micro-compression stage operated in the X-ray tomography scanner in the SLF cold laboratory. The dataset comprises the compression force data of 17 compression experiments, the 3D image data from 4 X-ray tomography scans and the results of numerical simulations.

compression-experiments

display_name: compression-experiments

microstructure

display_name: microstructure

snow

display_name: snow

snow-mechanics

display_name: snow-mechanics

x-ray-tomography

display_name: x-ray-tomography

en: Compressive stick slip and snow-micro-quakes


maintainer: Marcus Schaub

en: irrigation diameter-at-breast-height tree drought scots-pine tree-species dbh lwf swiss-forest-lab crown-condition forest

en: Shapefile	of measurement location

en: Long-term Irrigation	Experiment Pfynwald homepage

mimetype: text/html

en: Site photo 3

en: Swiss Forest Health Inventory

en: Site photo 2

en: Site photo 1

en: Dataset

en: To study the performance of mature Scots pine (_Pinus sylvestris_ L.) under chronic drought conditions in comparison to their immediate physiological response to drought release, a controlled long-term and large-scale irrigation experiment has been set up in 2003. The experiment is located in a xeric mature Scots pine forest in the Pfynwald (46° 18' N, 7° 36' E, 615 m a.s.l.) in one of the driest inner-Alpine valleys of the European Alps, the Valais (mean annual temperature: 9.2°C, annual precipitation sum: 657 mm, both 1961-1990). Tree age is on average 100 years, the top height is 10.8 m and the stand density is 730 stems ha-1 with a basal area of 27.3 m2 ha-1. The forest is described as _Erico Pinetum sylvestris_ and the soil is a shallow pararendzina characterized by low water retention. The experimental site (1.2 ha; 800 trees) is split up into eight plots of 1'000 m2 each. During April-October, irrigation is applied on four randomly selected plots with sprinklers of 1 m height at night using water from an adjacent water channel. The amount of irrigation corresponds to a supplementary rainfall of 700 mm year-1. Trees in the other four plots grow under naturally dry conditions. Soil moisture has been monitored since the beginning of the project at 3 soil depths (10, 20 and 60 cm). The crown condition of each tree is being assessed each year since 2003. Tree measurement data such as diameter at breast height, tree height, and social status were assessed in 2002, 2009 and 2014. The duration of the irrigation experiment is planned for 20 years.

crown-condition

display_name: crown-condition

dbh

display_name: dbh

diameter-at-breast-height

display_name: diameter-at-breast-height

drought

display_name: drought

forest

display_name: forest

irrigation

display_name: irrigation

lwf

display_name: lwf

scots-pine

display_name: scots-pine

swiss-forest-lab

display_name: swiss-forest-lab

tree

display_name: tree

tree-species

display_name: tree-species

educ

en: Education, culture and sport

en: Tree measurements 2002-2016 from the long-term irrigation experiment Pfynwald, Switzerland


maintainer: Athanasios Nenes

en: weissfluhjoch sigma-w raclets supersaturation hygroscopicity ccn dmt-ccn-chamber cloud-droplets cloud-modeling

en: Predicted cloud droplet number concentrations Weissfluhjoch

en:
In-situ measurements of aerosol size distributions along with updraft velocities collected from a wind Doppler Lidar are coupled with a state-of-the art droplet activation parameterization (Morales and Nenes, 2014) to determine the cloud droplet number and maximum in-cloud supersaturation that can potentially form over the Weissfluhjoch station between February 24 and March 8 2019. For this, a hygroscopicity parameter of 0.25 is assumed, according to the CCN-derived values. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The wind-lidar derived standard deviation of updraft velocities (sigma-w) in m/s, used to apply the parameterization employing a single characteristic velocity (Morales and Nenes, 2010)
* The maximum predicted cloud parcel supersaturation (Smax%)
* The total in-situ aerosol number concentration (Naer) in cmˉ³, measured by the SMPS
* The predicted cloud droplet numbers (Nd) in cmˉ³
* The activation fraction (%)

en: CCN data Weissfluhjoch

en:
In-situ CCN measurements were conducted between February 24 and March 8 2019 at Weissfluhjoch. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* Filtered CCN number concentrations (in cmˉ³) measured at 6 discrete supersaturations (SS) ranging from 0.09% to 0.74%. The name of each CCN column is indicative of the SS developed within the instrument.
* Instrument characteristics such as sample temperature (in °C) and pressure (in mbar)
* A code that refers to the reason of filtering.

Missing or filtered CCN values are indicated by "-999", while a declaration of each "Error_code" can be found in the following list:

_Error_code_:

0000: Measurements without error

1000: Period of transient operation after a supersaturation change

2000: Sharp change (decrease) in the room temperature housing the instrument, which induces a reset in column temperature

3000: Irregular values in the room temperature housing the instrument

9999: Missing data

en: Hygroscopicity parameter Weissfluhjoch

en:
The aerosol hygroscopicity parameter is derived combining the CCN and SMPS size distribution data collected between February 24 and March 8 2019 at Weissfluhjoch. The data file contains:

* Date and time (DD/MM/YYYY hh:mm:ss) in UTC
* The instrument supersaturation (SS%)
* The calculated hygroscopicity parameter (kappa)
* The calculated critical dry diameter of the particles (Dcr) in nm.

Missing values are indicated by "-999".

en:
Cloud Condensation Nuclei (CCN) data: A Droplet Measurement Technologies (DMT) single-column continuous-flow streamwise thermal gradient chamber (CFSTGC; Roberts and Nenes, 2005) was deployed at the measurement site Weissfluhjoch (2700 m a.s.l., LON: 9.806475, LAT: 46.832964) to record the in-situ CCN number concentrations between February 24 and March 8 2019 for different supersaturations (SS). To account for the difference between the ambient (~735 mbar) and the calibration pressure (~800 mbar), the SS reported by the instrument is adjusted by a factor of 0.92. The CFSTGC was cycled between 6 discrete SS values ranging from 0.09% to 0.74%, producing a full CCN spectrum every hour. The raw CCN measurements are filtered to discount periods of transient operation and whenever the room temperature housing the instrument changed sufficiently to induce a reset in column temperature. Additional information can be found in Section 2.1.2 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

Hygroscopicity data: The CCN number concentration measurements were directly related to the size distribution and total aerosol concentration data measured by the Scanning Mobility Particle Size Spectrometer (SMPS) instrument at the same station (https://www.envidat.ch/dataset/aerosol-data-weissfluhjoch) to infer the particles hygroscopicity parameter (kappa). For each SMPS scan, the particles critical dry diameter (Dcr) is estimated by integrating backward the SMPS size distribution, until the aerosol number matches the CCN concentration observed for the same time period as the SMPS scan. Assuming the particle chemical composition is internally mixed, the kappa is determined from Dcr and SS, applying Köhler theory. Additional information can be found in Section 2.2 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

Predicted cloud droplet numbers: Droplet calculations are carried out with the physically based aerosol activation parameterization of Morales and Nenes (2014), employing the “characteristic velocity” approach of Morales and Nenes (2010). Aerosol size distribution observations required to predict the cloud droplet numbers and maximum in-cloud supersaturation are obtained from the SMPS instrument deployed at Weissfluhjoch. The required vertical velocity measurements are derived from the wind Doppler Lidar (https://www.envidat.ch/dataset/lidar-wind-profiler-data) deployed at Davos Wolfgang and are extracted for the altitude of interest, being 1100 m above ground level for Weissfluhjoch. Additional information can be found in Section 2.3 [here](https://acp.copernicus.org/preprints/acp-2020-1036/).

ccn

display_name: ccn

cloud-droplets

display_name: cloud-droplets

cloud-modeling

display_name: cloud-modeling

dmt-ccn-chamber

display_name: dmt-ccn-chamber

hygroscopicity

display_name: hygroscopicity

raclets

display_name: raclets

sigma-w

display_name: sigma-w

supersaturation

display_name: supersaturation

weissfluhjoch

display_name: weissfluhjoch

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: CCN, hygroscopicity, predicted cloud droplet numbers Weissfluhjoch