Myths - Revision history

Valerias at 10:52, 16 March 2022

2022-03-16T10:52:14Z

← Older revision		Revision as of 10:52, 16 March 2022
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	# '''FAIR data equals open data.''' Both concepts are different. FAIR data can be offered as a paid service. However, metadata has to be open. Consequently, as long as ISOs are not availably open and for free, data cannot be FAIR.		# '''FAIR data equals open data.''' Both concepts are different. FAIR data can be offered as a paid service. However, metadata has to be open. Consequently, as long as ISOs are not availably open and for free, data cannot be FAIR.
	# '''FAIR is just a label.''' No, substantial effort is needed to make data FAIR. Data governance requires highly skilled resources - not on a project base but continuously.		# '''FAIR is just a label.''' No, substantial effort is needed to make data FAIR. Data governance requires highly skilled resources - not on a project base but continuously.
			# '''To make data FAIR is of the interest of a researcher.''' No, it is beyond the capability of a researcher.
	# '''Markets for FAIR and open data exist.''' No, if then only in the form of niche markets if at all. (See how long it takes to enter mainstream markets).		# '''Markets for FAIR and open data exist.''' No, if then only in the form of niche markets if at all. (See how long it takes to enter mainstream markets).

Valerias at 10:50, 16 March 2022

2022-03-16T10:50:37Z

← Older revision		Revision as of 10:50, 16 March 2022
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	# '''FAIR data is when humans can find, access, and reuse data.''' Wrong, because FAIR data is about machine-actionability (at the service for humans).		# '''FAIR data is when humans can find, access, and reuse data.''' Wrong, because FAIR data is about machine-actionability (at the service for humans).
	# '''FAIR data equals open data.''' Both concepts are different. FAIR data can be offered as a paid service. However, metadata has to be open. Consequently, as long as ISOs are not availably open and for free, data cannot be FAIR.		# '''FAIR data equals open data.''' Both concepts are different. FAIR data can be offered as a paid service. However, metadata has to be open. Consequently, as long as ISOs are not availably open and for free, data cannot be FAIR.
	# '''FAIR is just a label.''' No, substantial effort is needed to make data FAIR. Data governance requires highly skilled resources - not on a project base but ~~continously~~.		# '''FAIR is just a label.''' No, substantial effort is needed to make data FAIR. Data governance requires highly skilled resources - not on a project base but continuously.
			# '''Markets for FAIR and open data exist.''' No, if then only in the form of niche markets if at all. (See how long it takes to enter mainstream markets).

Valerias at 10:43, 16 March 2022

2022-03-16T10:43:26Z

← Older revision		Revision as of 10:43, 16 March 2022
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	Myths around FAIR data		Myths around FAIR data

	# FAIR data is when humans can find, access, and reuse data		# '''FAIR data is when humans can find, access, and reuse data.''' Wrong, because FAIR data is about machine-actionability (at the service for humans).
	# FAIR data equals open data		# '''FAIR data equals open data.''' Both concepts are different. FAIR data can be offered as a paid service. However, metadata has to be open. Consequently, as long as ISOs are not availably open and for free, data cannot be FAIR.
	# FAIR is just a label		# '''FAIR is just a label.''' No, substantial effort is needed to make data FAIR. Data governance requires highly skilled resources - not on a project base but continously.

Valerias: Created page with "Myths around FAIR data # FAIR data is when humans can find, access, and reuse data # FAIR data equals open data # FAIR is just a label"

2022-03-16T10:34:27Z

Created page with "Myths around FAIR data # FAIR data is when humans can find, access, and reuse data # FAIR data equals open data # FAIR is just a label"

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Myths around FAIR data

# FAIR data is when humans can find, access, and reuse data
# FAIR data equals open data
# FAIR is just a label