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Entry: 4. Experimental
URI: http://reference.metoffice.gov.uk/DataCategories/data-readiness/Experimental
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. It is only appropriate to use within the scope of the research activities. Experimental data consumers are often both the producers and consumers of the data – so change is driven by extremely short and rapid feedback loops. The 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. Experimental is the default data readiness category. In the absence of definitive labelling, the Experimental category may be assumed.
Core metadata
is a | Concept | data readiness |
submitted by | mo-marqh |
accepted on | 14 Jun 2022 08:02:47.835 |
Download formats available
RDF ttl | plain | with metadata |
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All metadata properties
date accepted |
14 Jun 2022 08:02:47.835
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date submitted |
1 Jun 2022 08:23:07.015
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definition |
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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.
It is only appropriate to use within the scope of the research activities.
Experimental data consumers are often both the producers and consumers of the data – so change is driven by extremely short and rapid feedback loops.
The 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.
Experimental is the default data readiness category. ...
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item class |
Concept
| data readiness
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label |
4. Experimental
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notation |
Experimental
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register |
data readiness
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status |
status stable
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submitter |
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type |
register item
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version info |
3
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Definition
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.
It is only appropriate to use within the scope of the research activities.
Experimental data consumers are often both the producers and consumers of the data – so change is driven by extremely short and rapid feedback loops.
The 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.
Experimental is the default data readiness category. ...
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label |
4. Experimental
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notation |
Experimental
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type |
Concept
| Data Readiness
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