Description
Enregistrements de données
Les données de cette ressource occurrence ont été publiées sous forme d'une Archive Darwin Core (Darwin Core Archive ou DwC-A), le format standard pour partager des données de biodiversité en tant qu'ensemble d'un ou plusieurs tableurs de données. Le tableur de données du cœur de standard (core) contient 3 865 enregistrements.
1 tableurs de données d'extension existent également. Un enregistrement d'extension fournit des informations supplémentaires sur un enregistrement du cœur de standard (core). Le nombre d'enregistrements dans chaque tableur de données d'extension est illustré ci-dessous.
Cet IPT archive les données et sert donc de dépôt de données. Les données et métadonnées de la ressource sont disponibles pour téléchargement dans la section téléchargements. Le tableau des versions liste les autres versions de chaque ressource rendues disponibles de façon publique et permet de tracer les modifications apportées à la ressource au fil du temps.
Versions
Le tableau ci-dessous n'affiche que les versions publiées de la ressource accessibles publiquement.
Comment citer
Les chercheurs doivent citer cette ressource comme suit:
MINKA. EMBIMOS research group, Institut de Ciències del Mar (ICM-CSIC). Medusa a la vista citizen science project. ICM-CSIC: MINKA_Medusa_a_la_vista observatorio de ciencia ciudadana. Version 1.0. Occurrence dataset.
Droits
Les chercheurs doivent respecter la déclaration de droits suivante:
L’éditeur et détenteur des droits de cette ressource est Institut de Ciències del Mar (CSIC). Ce travail est sous licence Creative Commons Attribution Non Commercial (CC-BY-NC) 4.0.
Enregistrement GBIF
Cette ressource a été enregistrée sur le portail GBIF, et possède l'UUID GBIF suivante : 247fd45a-0dd7-415d-9f47-699090f39cf5. Institut de Ciències del Mar (CSIC) publie cette ressource, et est enregistré dans le GBIF comme éditeur de données avec l'approbation du GBIF Spain.
Mots-clé
Occurrence; Observation
Contacts
- Créateur
- Originator
- Platform coordinator
- Fournisseur Des Métadonnées ●
- Personne De Contact
- Platform coordinator
- Curateur Des Données
- Curateur Des Données
- Conservateur
- Programmeur
- Chercheur Principal
Couverture géographique
Coastline of Catalonia
| Enveloppe géographique | Sud Ouest [40,527, 0,128], Nord Est [42,436, 3,389] |
|---|
Couverture taxonomique
Biodiversity of jellyfish and other pelagic organisms on the coast of Catalonia.
| Class | Scyphozoa |
|---|---|
| Order | Siphonophorae |
| Family | Aeginidae, Aequoreidae, Rhopalonematidae, Pandeidae, Blackfordiidae, Carybdeidae, Corymorphidae, Cuninidae, Mitrocomidae, Eirenidae, Geryoniidae, Bougainvilliidae, Laodiceidae, Olindiasidae, Oceaniidae, Moerisiidae, Porpitidae |
Couverture temporelle
| Date de début / Date de fin | 2008-04-05 / 2025-05-10 |
|---|
Données sur le projet
The AMRIT project brings together 26 leading European institutions with a shared mission: to strengthen European Marine Research Infrastructures (MRIs) and enhance ocean observation capabilities. With over €5 million in funding from the EU, AMRIT is spearheading the harmonisation, standardisation, and advancement of ocean observing activities to support the development of the European Ocean Observing System (EOOS). At the heart of AMRIT’s efforts is the development of the EOOS Technical Support Centre (EOOS TSC), a comprehensive digital ecosystem designed to streamline operations at sea and improve data collection and monitoring. A critical component of AMRIT is modernising the flow of ocean observation data. Work Package 8 focuses on building APIs to automate metadata transfer from in situ instruments to the EOOS TSC dashboard. This work will expand existing data pipelines in European MRIs, extend coverage to previously unsupervised coastal nodes, and ensure standardisation across platforms. This harmonisation will foster collaboration between networks, enhance operational efficiency, and improve data accessibility. AMRIT will also address Essential Ocean Variables (EOVs) readiness through WP13-15. By examining the pathways from in situ observations to EOVs, the project will identify gaps in blended EOVs (data derived from multiple platforms) and develop best practices to enhance their usability. These improvements will bolster EOOS’s capacity to deliver actionable insights for ocean observation and research.
| Titre | AMRIT Project |
|---|---|
| Identifiant | 101132013 |
| Financement | AMRIT is funded by the European Union’s Horizon Europe INFRA 2023-DEV-01 Programme under Grant Agreement No. 101132013 |
Les personnes impliquées dans le projet:
- Auteur
Méthodes d'échantillonnage
Sampling Methodology: The Medusa a la Vista project employs a participatory, unstructured sampling approach, leveraging the power of citizen science to gather data. This method involves the opportunistic collection of observations by volunteers across the coast of Catalonia. Sampling Description: Volunteers participating in the project contribute data through direct observations of jellyfish and other pelagic organisms on the coast of Catalonia. These contributions are critical for creating a comprehensive dataset that reflects the biodiversity and ecological conditions of the area. Data Validation Process: To ensure the reliability and accuracy of the dataset, each observation submitted by volunteers undergoes a rigorous quality control procedure. This validation process is designed to verify the correctness and relevance of the data collected, adhering to established standards for scientific data quality. Further details on the specific criteria and steps involved in the quality control procedure are described in the corresponding field.
| Etendue de l'étude | Sampling Area: the coast of Catalonia. |
|---|---|
| Contrôle qualité | Observations submitted to MINKA can qualify for Research Grade status if they are accompanied by a photo, the date of observation, and geographical coordinates. This status is conferred when a consensus on the species identification is reached within the MINKA community. When there's a division in opinion regarding the species observed, MINKA selects a consensus taxon from the suggestions, provided it garners agreement from over two-thirds of participating members. The methodology for determining the consensus taxon involves evaluating each suggested species and any broader categories it falls under. This evaluation calculates a score based on the proportion of identifications for that species against the total of all identifications, inclusive of later, more reserved identifications and those for unrelated species. The species with a score exceeding the two-thirds threshold, and with a minimum of two identifications, is deemed the community’s chosen taxon. In the case of observations at the gender level, those that are determined as "cannot be improved", and have two-thirds parts of the community in favor of the gender, will acquire Research Grade. Research Grade status may be withdrawn if community feedback indicates concerns on several fronts, including the authenticity of the organism's natural setting, the precision of the provided location and date, and adherence to MINKA's ethical standards, such as compliance with its terms of service and copyright laws. It's crucial to understand that data points such as observation dates and locations are primarily sourced from the observers and the collaborative efforts of the community for taxonomic identifications, without direct verification from MINKA's custodians. Therefore, the reliability of such information is not guaranteed. Specifically, while MINKA's system defaults to the WGS84 datum for geographical coordinates, observers have the flexibility to adjust these, raising the possibility of inaccuracies due to manual entries or alternate datum usage. |
Description des étapes de la méthode:
- Data Collection: The MINKA citizen observatory platform serves as the primary tool for data collection within the Medusa A la Vista project. Participants utilize this open platform to submit their observations, adhering to the stringent data quality control measures embedded in MINKA to ensure the accuracy and reliability of the data collected. Data Collaborative Validation: The MINKA platform employs a collaborative and standardized validation procedure. Observations that meet specific criteria are granted a "research grade" status, a designation that denotes their high quality and reliability. It is these research-grade observations that are subsequently published on GBIF. Data Sharing: In addition to the collaborative validation process, the project's dataset undergoes a rigorous review against established data quality standards, focusing on taxonomy, geography, and temporal accuracy, before its publication on GBIF. This ensures that the shared data meets the high-quality expectations of the global biodiversity data community.
Métadonnées additionnelles
| Identifiants alternatifs | 10.15470/7tuxwt |
|---|---|
| https://ipt.gbif.es/resource?r=minka_medusa_a_la_vista |