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Enregistrement W2898776429 · doi:10.17027/isric-wdcsoils.20180001

World Soil Information Service (WoSIS) - Towards the standardization and harmonization of world soil data. Procedures Manual 2018

2018· article· en· W2898776429 sur OpenAlex

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Notice bibliographique

RevueSocio-Environmental Systems Modeling · 2018
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueSoil Geostatistics and Mapping
Établissements canadiensnon disponible
Organismes subventionnairesNuclear Safety and Security CommissionAgriculture and Agri-Food CanadaGovernment of Canada
Mots-clésStandardizationComputer scienceDatabaseData qualityData scienceService (business)Business

Résumé

récupéré en direct d'OpenAlex

To better address the growing demand for soil information ISRIC - World Soil Information has developed a centralized database for the shared benefit of the international community. This database, hereafter referred to as WoSIS (World Soil Information Service), has been designed in such a way that, in principle, any type of soil data (point, polygon, and grid) may be accommodated. However, WoSIS will only provide quality-assessed data in a consistent format, with detailed information on data lineage and conditions for use. Data derived from WoSIS may be used to address pressing challenges of our time including food security, land degradation, water resources, and climate change. At present, the focus in WoSIS is on developing consistent procedures for standardizing and harmonizing soil analytical data as submitted by a wide range data providers. The general procedure for processing profile data in WoSIS is as follows. First, new source data are imported ‘as is’ into a PostgreSQL database, with the original naming and coding conventions, abbreviations, domains, lineage and data licence; thereby copies of the source materials are safeguarded at ISRIC. Second, the source databases are imported into WoSIS proper, forming the first major step of data standardization (into a single data model). The next step of data standardization, applied to the values for the various soil properties as well as to the naming conventions themselves, is needed to make the data queryable and useable. Special attention has been paid to the standardization of analytical method descriptions, focusing on the list of soil attributes considered in the GlobalSoilMap (GSM, 2013) specifications (e.g. organic carbon, soil pH, soil texture (sand, silt, and clay), coarse fragments, cation exchange capacity, bulk density, and water holding capacity), to which we have added electrical conductivity. Further, we checked and added the soil classification (FAO, WRB and USDA Soil Taxonomy) and horizon designations as provided in the source databases. During the standardization of the analytical method descriptions, major characteristics of commonly used methods for determining a given soil property are identified first. For soil pH, for example, these are the sample pretreatment, extractant solution (water or salt solution), and in case of salt solutions the salt concentration (molarity), as well as the soil/solution ratio; a further descriptive element is the type of instrument used for the actual laboratory measurement. Similar schemes were developed for the other soil properties under consideration here, with accompanying flowcharts. A third step in the standardization / harmonization process will require data harmonization to make the analytical data comparable that is as ’if assessed by a single given (reference) method’. Such work will require further international collaboration and data sharing to the benefit of the international user community as foreseen in the framework of Pillar 5 of the Global Soil Partnership. Inherently, the present standardization procedures are only applied to soil profiles flagged as having adequate permissions (i.e. ’shared’ profiles with at least a Creatice Commons Licence type CC BY or CC BY-NC). The resulting standardized data can be accessed through our GeoNetwork instance (http://data.isric.org/). The latest, dynamic dataset is available through a web feature service (WFS); the corresponding data layers are referred to as ‘WoSIS latest’. For consistent citation purposes, we also produce ‘static’ snapshots of the standarized data in comma delimited format (CSV), most recently ‘WoSIS snapshot - July 2016’ (Batjes et al., 2017). WoSIS forms an important building block of ISRIC‘s Spatial Data Infrastructure (SDI). Further developments will allow for the fulfilment of future demands for global soil information, and enable further incorporation of soil data shared by third parties in an inter-operable way, within a federated system. www.isric.org

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,242
Score d'incertitude au seuil0,697

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,242
Écart entre enseignants0,217 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle