@prefix cc: . @prefix void: . @prefix ssd: . @prefix owl: . @prefix xsd: . @prefix skos: . @prefix rdfs: . @prefix version: . @prefix qb: . @prefix dgu: . @prefix dct: . @prefix ui: . @prefix rdf: . @prefix reg: . @prefix ldp: . @prefix time: . @prefix api: . @prefix vann: . @prefix vs: . @prefix prov: . @prefix foaf: . @prefix dc: . a skos:Concept , ; rdfs:label "1. Application ready"@en ; dct:description "Application-ready data is warrantied: available to be used in products and services aimed at less environmentally expert consumers. It is well described and discoverable – this being oriented towards the consumer perspective of application and use, with managed provenance, wide applicability and a high degree of quality control. Data conforms to common standards and formats for publicly available tools.\nThere is a high degree of supporting documentation and human support available on the use and understanding of the data. Data support is provided by people who are not the producers of the data.\nApplication-ready data consumers are typically people operating products and services for domain specific customers, where Met Office data is sometimes only a portion of the data domain. These operators maybe be the Met Office or external 3rd parties. \nThere is a contractual understanding between the producer and the consumer which is warrantied and requires high degrees of co-ordination.\nThe inherent risks in use of this data is that they may not be properly understood by the consumer and changes may have downstream impacts. Mitigation is to provide clear documentation and support, and to warranty the content so that they can rely upon it and be notified when changes occur to the structure or meaning. "@en ; dct:notation "Application-ready" ; skos:broader ; skos:inScheme . a skos:Concept , ; rdfs:label "4. Experimental"@en ; dct:description "Experimental data is created in the process of conducting domain specific research and developing new techniques and approaches. It is used to explore new and niche ideas. It is often highly customised and specific. It does not have to be generally useful, nor well described or discoverable outside of the small group of specialists who are collaborating around it. It is often in the process of being validated and verified and not in a state to be shared with people who are not experts in the area of interest.\nIt is only appropriate to use within the scope of the research activities.\nExperimental data consumers are often both the producers and consumers of the data – so change is driven by extremely short and rapid feedback loops.\nThe inherent risks in use of this data are that they are experimental, change rapidly, maybe misleading, and may not be valid in the context of use. Mitigation is that it is narrowly shared with experts.\nExperimental is the default data readiness category. In the absence of definitive labelling, the Experimental category may be assumed. "@en ; dct:notation "Experimental" ; skos:inScheme . a reg:Register , skos:ConceptScheme , ldp:Container ; rdfs:label "Environmental Data Readiness Categories"@en ; dct:description "Environmental Data Readiness Categories for Appropriate Use of Data."@en ; dct:modified "2022-06-01T08:23:07.017Z"^^xsd:dateTime ; owl:versionInfo 5 ; ldp:isMemberOfRelation skos:inScheme . a skos:Concept , ; rdfs:label "2. Decision ready"@en ; dct:description "Decision-ready data is validated: available to be used for making decisions by others outside of the group that produce it. It is well described and discoverable, with managed provenance, wide applicability and a high degree of quality control. The methods of production have been validated and the content is guaranteed to be correct and not been tampered with by bad actors. It is available in a timely manner.\nDecision-ready data consumers are expert in the understanding and use of the data, but not necessarily in the methods of the production of the data.\nThe inherent risks in use of this data are that may not be valid in the context of use. Mitigation is that it is qualified and shared with experts on a limited basis."@en ; dct:notation "Decision-ready" ; skos:broader ; skos:inScheme . a skos:Concept , ; rdfs:label "3. Analysis ready"@en ; dct:description "Analysis-ready data is unvalidated: available to others outside of the group that produces the data. It is well described and discoverable. It has no guarantee of validity to particular usage contexts and is only appropriate for use by experts who can validate the content themselves. Indeed, the act of analysis can be part of the process of validation. It conforms to some standard of meta-data description and structure, such that consumers can use shared standard tooling to explore and use the content.\nMetadata on the source and provenance of the data becomes important, as the ways of working require direct interaction between producer to consumer as the data may not be fully documented and the subtleties of the context in which the data is valid may not be clear.\nThere is no guarantee that the content is correct from an environmental science perspective.\nThe inherent risks in use of this data are that they are unvalidated, may be misleading, and may not be valid in the context of use. Mitigation is that it is qualified and shared with experts on a limited basis. "@en ; dct:notation "Analysis-ready" ; skos:inScheme .